CN109873853B - Equipment key parameter early warning system, implementation method thereof and electronic device - Google Patents

Equipment key parameter early warning system, implementation method thereof and electronic device Download PDF

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CN109873853B
CN109873853B CN201711269792.2A CN201711269792A CN109873853B CN 109873853 B CN109873853 B CN 109873853B CN 201711269792 A CN201711269792 A CN 201711269792A CN 109873853 B CN109873853 B CN 109873853B
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equipment
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CN109873853A (en
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郭梅芳
于宁
温晓宇
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Beijing Xushui Interconnection Technology Co ltd
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Beijing Xushui Interconnection Technology Co ltd
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Abstract

The invention discloses an equipment key parameter early warning system and an implementation method thereof, which solve the problem that in the prior art, equipment key parameters are judged and early warned by equipment, so that the equipment key parameters need to be manually attended and reported to be abnormal, and the efficiency is low. In addition, the system transmits the key parameter data of the equipment to the system platform through the data acquisition module, the system platform can be deployed at any place, and the data acquisition module can be connected with the equipment, so that the system platform can be used for simultaneously detecting and early warning the key parameters of a plurality of pieces of equipment at different places, and the processing efficiency is high. The system is applied to early warning of key parameters of the equipment, only the system platform needs to be deployed on a corresponding server or other carriers, and the data acquisition module is connected with the corresponding equipment, so that the internal transformation of the equipment is not needed, and the early warning of the key parameters of the equipment is simple and rapid to deploy.

Description

Equipment key parameter early warning system, implementation method thereof and electronic device
Technical Field
The invention relates to the technical field of equipment management, in particular to the technical field of medical equipment management, and specifically relates to an early warning system for key parameters of equipment, an implementation method of the early warning system, and an electronic device or a product bearing the early warning system.
Background
At present, in the field of medical equipment, the monitoring of the key parameters of the equipment is realized through manual watching and telephone reporting, for example, the nuclear magnetic resonance equipment is taken as an example, liquid helium pressure is the key parameter in the nuclear magnetic resonance equipment, once the liquid helium pressure fluctuates abnormally, the liquid helium is likely to leak, even the serious consequences such as quench and the like, and huge loss is caused to hospitals. Therefore, it is necessary to alarm in time when the pressure of the liquid helium is abnormal, so as to inform relevant personnel to take treatment measures in time, thereby avoiding serious consequences and loss. At present, the method for alarming the abnormal pressure of the liquid helium of the nuclear magnetic resonance equipment is mainly realized by alarming in the form of sound, light or characters on the equipment. The mode realizes the alarm reminding of the abnormal pressure of the liquid helium, but the alarm information on the equipment is observed manually, then a telephone is informed to a maintenance person when the alarm reminding is observed, and the maintenance person judges the equipment condition according to the description of the informing person and the experience of the maintenance person so as to decide which treatment measures are taken, such as whether to go to the field for maintenance immediately or observe for a period of time again, and the like. Therefore, the existing treatment mode needs to be observed by people on duty and also needs to be subjected to contact reporting, so that the labor cost is high, and the treatment efficiency is not high. Therefore, there is a need in the art to provide a more efficient, timely and labor-saving solution.
Disclosure of Invention
According to one aspect of the invention, the invention provides an equipment key parameter early warning system, which is used for solving the problem that in the prior art, equipment key parameters are judged and early warned by equipment, so that the equipment key parameters need to be manually attended and reported to be abnormal, and the efficiency is low. The system comprises a data acquisition module and a system platform for carrying out abnormity analysis and early warning on key parameters of equipment, wherein the data acquisition module is connected with corresponding equipment and is used for acquiring the key parameter data of the equipment in real time and sending the key parameter data to the system platform; the system platform comprises a threshold setting module, a key parameter information record generating module, an abnormality detection module, an alarm module and a storage unit, wherein the threshold setting module is used for generating abnormality configuration information according to the received threshold information and storing the abnormality configuration information in the storage unit; the key parameter information record generating unit is used for generating an equipment key parameter information database according to the key parameter data; the abnormality detection module is used for carrying out abnormality judgment on the key parameters of the equipment according to the key parameter information database and the abnormality configuration information, and outputting a judgment result to the alarm module when the judgment result is abnormal; the alarm module is set to generate alarm information according to the judgment result output by the abnormity detection module and output the alarm information. Therefore, the system can be used for automatically detecting and analyzing the abnormal conditions of the key parameters of the equipment, and outputting alarm information to remind a user when abnormality occurs. The system transmits the key parameter data of the equipment to the system platform through the data acquisition module, the system platform can be deployed at any place, and the system platform can be used for simultaneously detecting and early warning the key parameters of a plurality of pieces of equipment at different places by connecting the data acquisition module to the equipment, so that the processing efficiency is high. The system is applied to early warning of key parameters of the equipment, only the system platform needs to be deployed on a corresponding server or other carriers, and the data acquisition module is connected with the corresponding equipment, so that the internal transformation of the equipment is not needed, and the early warning of the key parameters of the equipment is simple and rapid to deploy.
In some embodiments, the system further comprises a user terminal, the system platform further comprises a user management module and a terminal binding module, and the user management module is used for allocating account information for the user and associating corresponding device information with the allocated account information; the terminal binding module is used for associating the user terminal with the matched account information according to the binding request of the user terminal and the account information distributed by the user management module; the alarm module is further configured to output the generated alarm information to the associated user terminal. Therefore, the equipment can be allocated to the corresponding user name according to the requirement, and the corresponding user monitors the allocated equipment, so that the task allocation and the task scheduling are facilitated. Moreover, the alarm information can be directly pushed to communication equipment commonly used by the user through the binding of the user terminal, so that the user can check the alarm information in time. When the user is a maintenance engineer or manufacturer, the abnormal condition of the key parameters of the equipment can be known in real time without watching and reporting, so that the maintenance or other treatment can be conveniently and timely carried out, and the loss is avoided. Moreover, by the method, one user can monitor a plurality of devices at the same time, and the processing efficiency is very high.
In some embodiments, the user terminal is one or a combination of two or more of WeChat, SMS, email, and client APP.
In some embodiments, the system platform further includes an alarm policy setting module, configured to receive input alarm policy information, generate abnormal configuration information including the alarm policy information, and store the abnormal configuration information in the storage unit; and the abnormity detection module is also used for carrying out corresponding abnormity detection processing on each key parameter of the equipment according to the set alarm strategy. Therefore, the abnormity detection and alarm can be carried out on the key parameters of the equipment according to the alarm strategy. The method has the advantages that the key parameter data of some devices are many, the abnormal conditions of the data are relatively many, some abnormal conditions are not processed urgently or are not influenced a little temporarily, some users may monitor a plurality of devices simultaneously, abnormal messages are many under the conditions, if each abnormal message is detected and early-warned, noise interference is caused, important abnormal messages are submerged, and the value of early-warning messages is reduced.
In some embodiments, the device is a medical device and the system platform is deployed on a cloud server or a dedicated server within a hospital. Therefore, monitoring and early warning of medical equipment can be achieved, all medical equipment can be monitored and early warned when the system is deployed at the cloud end, monitoring and early warning of the medical equipment of a specific hospital can be achieved when the system is deployed on a server inside the hospital, maintenance efficiency of the medical equipment is improved, and great loss is avoided.
According to another aspect of the present invention, an implementation method of the foregoing device critical parameter early warning system is further provided, including: configuring threshold information for key parameters of each device, and generating abnormal configuration information for storage; acquiring an equipment log of the equipment, analyzing, and generating and storing key parameter information of the equipment; and carrying out abnormity judgment on the key parameters of the equipment according to the stored key parameter information and the abnormal configuration information, and generating alarm information to output when the judgment result is abnormal. Therefore, the detection and judgment of the abnormity of the key parameter data can be realized based on the set key parameter threshold and the key parameter real-time data acquired through the equipment log, and early warning is realized when the abnormity is judged.
In some embodiments, the key parameter of the device is determined to be abnormal according to the stored key parameter information and abnormal configuration information, and when the determination result is that an abnormality occurs, the alarm information output is generated by: acquiring the current maximum value and the current minimum value of each key parameter according to the stored key parameter information, and acquiring the upper limit threshold value and the lower limit threshold value of each key parameter according to the abnormal configuration information; and judging whether the abnormality occurs according to the obtained current maximum value and minimum value of each key parameter and the upper limit threshold value and the lower limit threshold value, and generating alarm information to output when the judgment result is that the abnormality occurs and the current abnormality is not early-warning abnormality. Because the current most value is obtained for judgment every time, and the early warning is carried out again when the early warning is not abnormal, the alarm is carried out only when the condition is worsened, the interference of unimportant information can be reduced, the major abnormality is highlighted, the noise interference is reduced, and the efficiency is improved.
In some embodiments, the method further comprises: allocating user account information, configuring associated equipment for the allocated account information, and generating user information for storage; receiving a binding request, configuring a related user terminal for the allocated account information according to the binding request and the stored user information, and generating user information storage simultaneously containing related equipment and the related user terminal; and when the alarm information is output, acquiring a user terminal associated with the abnormal equipment according to the user information, and outputting the generated alarm information to the user terminal associated with the equipment. Therefore, the method and the device can realize that the terminal commonly used by the user is bound according to the requirement, the message is directly output to the terminal, and realize that one user can bind any equipment according to the requirement and monitor any equipment, so that the efficiency is very high, and the realization is simple.
According to another aspect of the present invention, there is provided another implementation method of the foregoing device critical parameter early warning system, where the method includes: configuring threshold information and an alarm strategy for key parameters of each device, and generating and storing abnormal configuration information; acquiring an equipment log of the equipment, analyzing, and generating and storing key parameter information of the equipment; and acquiring an alarm strategy corresponding to each key parameter of the equipment, performing abnormity detection according to the alarm strategy, key parameter information and abnormity configuration information of the corresponding key parameter, and generating alarm information according to a detection result and outputting the alarm information. The method can not only perform abnormity judgment and early warning based on the actual condition of the equipment, but also perform abnormity detection and early warning according to the alarm strategy, can adapt to different key parameter data conditions and equipment conditions, can filter abnormal information, reduce noise and improve the value of alarm information.
In some embodiments, the alarm strategy configured for each critical parameter includes one of a continuous deterioration alarm strategy, a period-defined alarm strategy, and a fluctuation range-defined alarm strategy, or a combination of both. The continuous deterioration alarm strategy can realize alarm when data is continuously deteriorated, highlight important messages and ensure real-time performance; noise interference can be reduced through a period limited alarm strategy, and the method is suitable for key parameters with small data change frequency; the fluctuation range limiting alarm strategy is optimization of a continuous deterioration alarm strategy, and is not only used for judging the maximum value at a certain moment, but also used for judging abnormality based on the fluctuation range, so that the abnormal condition of data can be more accurately reflected.
In some embodiments, when the alarm policy of the corresponding key parameter is a persistent worsening alarm policy, obtaining key parameter dataset information and abnormal configuration information of the corresponding key parameter according to the alarm policy to perform abnormal detection, and generating alarm information output according to the detection result includes: acquiring the current maximum value and the current minimum value of the corresponding key parameter according to the stored key parameter information, and acquiring the upper limit threshold value and the lower limit threshold value of the corresponding key parameter according to the abnormal configuration information; and judging whether the abnormality occurs according to the acquired current maximum value and minimum value of the corresponding key parameter and the upper limit threshold value and the lower limit threshold value, and generating alarm information to output when the judgment result is that the abnormality occurs and the current abnormality is not early-warning abnormality. Therefore, whether the current maximum value is abnormal or not and whether the abnormal maximum value is early-warned or not are judged every time, if the abnormal maximum value is abnormal and the early-warned maximum value is not obtained, the alarm is given out, the early warning of continuous deterioration data is realized, the noise is effectively reduced, and the realization is simple.
In some embodiments, when the alarm policy corresponding to the key parameter is a fluctuation range limited alarm policy, obtaining key parameter dataset information and abnormal configuration information of the corresponding key parameter according to the alarm policy to perform abnormal detection, and generating alarm information according to a detection result to output includes: acquiring an upper limit threshold, a lower limit threshold, a fluctuation range and an alarm period of corresponding key parameters according to the abnormal configuration information; timing according to the alarm period, and acquiring the maximum value and the minimum value of the corresponding key parameter in the alarm period time interval from the stored key parameter information every other alarm period time interval; calculating the fluctuation value of the corresponding key parameter in the corresponding alarm period according to the maximum value and the minimum value in the time interval; calculating a fluctuation range threshold corresponding to the corresponding key parameter according to the upper limit threshold, the downlink threshold and the fluctuation range; and carrying out abnormity judgment according to the fluctuation value and the fluctuation range threshold value, and generating alarm information to output when the abnormity is judged to occur. Therefore, the data fluctuation based on the key parameters in the specified time is detected in an abnormal mode, and the data fluctuation condition can reflect the abnormal probability and degree substantially, so that the method can realize more accurate abnormal detection, early warning is carried out when the fluctuation range exceeds the threshold value in the specified period, the early warning is not carried out on each abnormal record, the noise pollution can be effectively reduced, and the result is more accurate.
In some embodiments, when the alarm policy corresponding to the key parameter is a period-limited alarm policy, obtaining key parameter dataset information and abnormal configuration information of the corresponding key parameter according to the alarm policy to perform abnormal detection, and generating alarm information output according to the detection result includes: acquiring an upper limit threshold, a lower limit threshold and an alarm period of corresponding key parameters according to the abnormal configuration information; timing according to the alarm period, and acquiring the latest data value of the corresponding key parameter when the information is acquired from the stored key parameter information at intervals of the alarm period; and carrying out abnormity judgment according to the latest data value, the upper limit threshold value and the downlink threshold value, and generating alarm information to output when the abnormity is judged to occur. By setting the alarm period and carrying out abnormity detection and early warning according to the alarm period, the problem of noise pollution caused by alarming on abnormity recorded every time can be avoided.
In some embodiments, the step of periodically limiting the alarm period corresponding to the alarm policy to include a first alarm period and a second alarm period, where a duration of the first alarm period is longer than the second alarm period, and when the alarm policy corresponding to the key parameter is the periodically limited alarm policy, the step of obtaining key parameter dataset information and abnormal configuration information of the corresponding key parameter according to the alarm policy to perform abnormal detection, and generating an alarm information output according to the detection result further includes: when a period limited alarm strategy is adopted for carrying out abnormity detection for the first time, setting the alarm period of the corresponding key parameter as a first alarm period; when abnormality occurs, counting the output frequency of the alarm information, and switching the alarm period of the corresponding key parameter between a first alarm period and a second alarm period according to the output frequency of the alarm information when abnormality detection is not performed by adopting a period limited alarm strategy for the first time. In the implementation mode of the change alarm period, after the alarm occurs, if the alarm continuously exceeds the threshold, the short alarm period is adopted for carrying out abnormal detection so as to monitor the parameter change condition in real time, and if the individual number exceeding the threshold appears occasionally, the abnormal detection can be immediately recovered to the long-period abnormal detection through switching, so that frequent early warning is avoided.
In some embodiments, the method further comprises: allocating user account information, configuring associated equipment for the allocated account information, and generating user information for storage; receiving a binding request, configuring a related user terminal for the allocated account information according to the binding request and the stored user information, and generating user information storage simultaneously containing related equipment and the related user terminal; and when the alarm information is output, acquiring a user terminal associated with the abnormal equipment according to the user information, and outputting the generated alarm information to the user terminal associated with the equipment. From this, can realize binding between user, equipment and the user terminal three for same user can monitor a plurality of equipment, and alarm message can send the user terminal that the user bound, and convenience of customers in time looks over, thereby realizes timely processing, avoids the loss, and is simple high-efficient.
According to still another aspect of the present invention, there is also provided an electronic apparatus, which includes a storage medium and a control unit, wherein the storage medium stores an application program for implementing the foregoing device key parameter early warning system, and the control unit is configured to execute the application program.
Drawings
FIG. 1 is a schematic diagram of a frame structure of a critical parameter early warning system of an embodiment of the present invention;
FIG. 2 is a schematic diagram of a frame structure of a critical parameter early warning system of an apparatus according to another embodiment of the present invention;
FIG. 3 is a schematic diagram of a frame structure of a critical parameter early warning system of an apparatus according to another embodiment of the present invention;
fig. 4 is a schematic flow chart of a method of an apparatus key parameter early warning method according to an embodiment of the present invention;
FIG. 5 is a flowchart illustrating a method for pre-warning a key parameter of a device according to another embodiment of the present invention;
fig. 6 is a flowchart illustrating an implementation method for outputting alarm information to a user terminal according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a system for abnormal analysis and early warning of key parameters of equipment and an implementation method of the system, which are used for realizing automatic abnormal analysis and early warning of the key parameters of the equipment and solving the problems of low efficiency and high labor cost in the conventional abnormal analysis and early warning mode. In the embodiment of the present invention, the device may be any device capable of acquiring real-time data of a key parameter, especially a medical device, such as a nuclear magnetic resonance device, CT, ultrasound, and the like. The key parameters are factors that may have a significant impact on the operating condition or quality condition of the equipment, and taking nuclear magnetic resonance equipment as an example, the key parameters may be a liquid helium pressure value, a liquid helium level, a water flow, a water temperature, a shielding layer temperature, a cold head temperature, and the like. The system of the embodiment of the invention mainly realizes the abnormity analysis by setting the threshold value for various key parameters of each device according to the actual condition and the empirical data of the device and comparing the key parameter information of the device acquired in real time with the set threshold value. This analytic process is through the key parameter numerical value of long-range collection equipment to carry out the analysis realization at the server end, need not carry out the analysis on each equipment, because can realize carrying out analysis and monitoring to multiple and a plurality of equipment simultaneously, efficiency is very high. In addition, in a preferred embodiment, the system of the present invention can also generate an abnormal analysis result as alarm information to be output to a user terminal set by a user, so as to realize direct pushing of the abnormal information to the user, and a manual guard device is not needed to monitor the abnormal and alarm conditions, thereby improving the efficiency, reducing the labor cost, and enabling maintenance personnel to more directly grasp the abnormal conditions, and conveniently and timely perform appropriate processing. In the preferred embodiment, the system can also set an alarm strategy to filter the pushed alarm information, so that the value of the alarm information is improved, one maintenance worker can effectively monitor a plurality of devices at the same time, the efficiency is greatly improved, and the labor cost is greatly reduced.
The following description will focus on the example in which the equipment is nuclear magnetic resonance equipment and the key parameter is liquid helium pressure value, and will be described in detail with reference to the accompanying drawings.
Fig. 1 schematically shows a framework structure of an abnormality analysis and warning system for key parameters of equipment according to an embodiment of the present invention. As shown in fig. 1, the system 2 includes a data acquisition module 20 for acquiring information of key parameters of the equipment and a system platform 21 for performing anomaly analysis and early warning on the key parameters, wherein the data acquisition module 20 is connected to each nuclear magnetic resonance equipment 1, and is configured to acquire real-time data values of the key parameters of the equipment 1 and upload the real-time data values to the system platform 21. The system platform 21 in the embodiment of the present invention includes a storage unit 210, a key parameter information record generating module 211, an anomaly detecting module 212, an alarm module 213, and a threshold configuring module 217. The threshold configuration module 217 is configured to generate and store the device abnormal configuration information according to the received threshold information, where the setting of the threshold information is provided by a maintenance engineer in combination with an actual situation of the device and a manufacturer technical specification, for example, the setting of the liquid helium pressure threshold of the nuclear magnetic resonance device may be set according to a liquid helium amount of the corresponding device and a technical specification of a nuclear magnetic manufacturer, and may be set directly through a user page by the maintenance engineer or an administrator, and after the setting is completed, the threshold configuration module 217 in the system platform 21 according to the embodiment of the present invention stores the setting as a device abnormal configuration information data record, where the set threshold information may include a device ID, a threshold type, an upper threshold and a lower threshold, and the generated abnormal configuration information at this time also includes a device ID, a threshold type, an upper threshold and a lower threshold. In a specific implementation, the key parameter information uploaded by the data acquisition module 20 may be an equipment log stored on the equipment acquired by the data acquisition module, or may be real-time key parameter data acquired by sensor data. When the device log is collected, the device log uploaded by the data collection module 20 is first sent to the storage unit 210 for storage, and the key parameter information record generation module 211 is configured to traverse the storage unit 210, obtain the device log from the storage unit 210 for analysis, and generate a key parameter information database of the device according to an analysis result. When the real-time key parameter data is acquired, the data acquisition module 20 directly sends the data to the key parameter information record generation module 211, the key parameter information record generation module 211 analyzes the key parameter data, and generates and stores a key parameter information database of the device according to an analysis result (for example, which key parameter the data belongs to, what specific data is, time information, and the like). The anomaly detection module 212 is configured to obtain a history record of key parameter information of a corresponding device from a key parameter information database, and determine whether an anomaly occurs according to key parameter data in the history record and a preset threshold, where a process of selecting key parameter data in the history record may be implemented according to different requirements, for example, in some embodiments, the key parameter data used for comparison may be a latest data value, and in other embodiments, the obtained key parameter data used for comparison may be a maximum value and/or a minimum value of each key parameter at a current time since the day. The alarm module 213 is configured to generate an alarm information output when receiving the determination result of the abnormality detection module 212 and the determination result is that an abnormality occurs. The device log in this embodiment may be in the form of a file stored in a storage system of the device itself, or in other forms, as long as the device log is continuously updated and in an extractable state as the device is used, and can be accessed and utilized by an external device, which is not limited in this embodiment of the present invention.
The data collection module 20 in the embodiment of the present invention may be a data collection box, which is directly disposed on a device that needs to collect the device log, reads the device log on the device through a data collection function of the data collection box, and sends the device log to the system platform 21 through a network. The system platform 21 may be implemented by software programming and deployed on a server (which may be deployed on a cloud server or a server local to a hospital). After receiving the device log through the network, the system platform 21 first stores the device log in the storage unit 210, and then the key parameter information record generating module 211 traverses the device log in the storage unit 210 to analyze the device log. The method for analyzing may be to extract required key information, such as time and liquid helium pressure data, through a feature matching algorithm (e.g., a screening algorithm based on a regular expression), where the key information may be customized according to needs and types of devices, but at least needs to include a time keyword and a keyword corresponding to a certain key parameter. After the key information is analyzed, extracting the key information, associating the extracted key information with the equipment ID, generating a minimum index unit of equipment ID-time-key parameter data and storing the minimum index unit as a data record of a database. After the data collection module 20 uploads the device log and the key parameter information record generation module 211 completes parsing, the key parameter information record generation module 211 notifies the anomaly detection module 212 that the data is updated, in a preferred embodiment, the anomaly detection module 212 extracts the maximum and minimum values of the current day by the current time of each key parameter of the current device from the key parameter information database through database operations, and will obtain the threshold information corresponding to each key parameter of the device from the abnormal configuration information through database operation, including the threshold type, the upper threshold and the lower threshold, and then the abnormal detection module 212 compares the maximum value with the corresponding upper threshold according to the type of the key parameter, and comparing the minimum value with a corresponding lower limit threshold value, and judging whether the abnormity occurs according to the comparison result. For example, when the key parameter is the liquid helium pressure, the abnormality detection module 212 compares the maximum value of the acquired liquid helium pressure with an upper threshold value whose threshold type is the liquid helium pressure, compares the minimum value of the acquired liquid helium pressure with a lower threshold value whose threshold type is the liquid helium pressure, determines that an abnormality occurs if the maximum value is greater than the upper threshold value or the minimum value is less than the lower threshold value as a result of the comparison, and outputs a determination result of the occurrence of the abnormality to the alarm module 213. The alarm module 213 first determines whether the abnormality has been alarmed according to the output result of the abnormality detection module 212, and generates an alarm information output according to the abnormality result if the abnormality has not been alarmed, where the generated alarm information includes a device ID or name, a key parameter, an abnormal value, and time, and the output may be output to a display device or a user page, which is not limited in the embodiments of the present invention. Therefore, monitoring and early warning of key parameters of equipment, such as liquid helium pressure data of nuclear magnetic resonance equipment, can be performed through the system of the embodiment of the invention, the equipment log acquisition module in the system of the embodiment of the invention is directly connected with corresponding equipment, such as the nuclear magnetic resonance equipment, acquires the equipment logs, performs log analysis and abnormality detection through a system platform, and outputs the logs to corresponding display equipment or a user page when abnormality is detected, without arranging personnel to watch the equipment, such as the nuclear magnetic resonance equipment, so that remote monitoring and early warning of the equipment are realized, and the labor cost is reduced. In addition, the anomaly detection of the embodiment of the invention is judged according to the threshold values set aiming at different equipment conditions and the real-time analysis result of the equipment log, the detection result is more accurate, and the threshold values are provided by a maintenance engineer in combination with the actual conditions of the equipment and the technical specifications of equipment manufacturers, for example, the threshold values of the liquid helium pressure are provided according to the liquid helium amount of the corresponding equipment and the technical specifications of nuclear magnetism manufacturers, so that the reference value is high, and the problems of low efficiency and high cost caused by the fact that the existing mode needs to depend on guard and real-time telephone reporting are solved.
Fig. 2 schematically shows a framework structure of a critical parameter abnormality analysis and warning system for equipment in another embodiment of the present invention. As shown in fig. 2, the system in the embodiment of the present invention is different from the system shown in fig. 1 in that the system platform 21 in the embodiment of the present invention further includes a user management module 214 and a terminal binding module 215, and the system 2 in the embodiment of the present invention is connected to each device through the data acquisition module 20, and is further bound to the corresponding user terminal 3 through the terminal binding module 215, so that the system in the embodiment of the present invention simultaneously realizes communication between each device and the user terminal, and provides a more convenient implementation scheme for monitoring and early warning of key parameters of the device. In order to implement communication between the system 2 and the user terminal 3, as shown in fig. 2, in the embodiment of the present invention, a user management module 214 needs to be arranged in the system platform 21 to allocate account information to a user and associate the allocated account information with corresponding device information, and a terminal binding module 215 needs to be arranged in the system platform 21 to receive a binding request sent by the user terminal 3 and associate the user terminal 3 with the account information allocated by the user management module 214 according to the binding request. The account information allocated by the user management module 214 to the user includes a user name and a password, the account information is generated as a user information database and stored in the storage unit 210, and associating the allocated account information with the corresponding device information means that a device ID associated with the user name is set in a record corresponding to the user name to designate each user as its allocated device (e.g., a nuclear magnetic resonance device), so that the alarm information of the device can be sent to the designated user, and the designated user performs subsequent processing, such as maintenance and the like, on the device. The terminal binding module 215 obtains the user name and password information input by the user and the terminal information carried in the request, such as the terminal ID, from the binding request sent by the user from the user terminal 3, and performs identity verification through the user name and password information, and after the verification is passed, associates and binds the user sending the request (i.e., the account corresponding to the user name and password contained in the request) with the corresponding user terminal 3, where the association binding may be to store the obtained user terminal information, such as the terminal ID, in a user information database record of the corresponding user, for example, to generate a user information database record including a user name-password-associated device ID-associated user terminal ID database structure. When a user uses the terminal 3 to initiate a binding request to the system platform 21, account information (such as a user name and a password) assigned to the user by the user management module 214 needs to be provided on the user terminal 3. After receiving the request of the user terminal 3, the system platform 21 first automatically resolves the terminal ID in the user terminal 3 from the request by the terminal binding module 215 (this resolving method can be implemented by the prior art, for example, resolving according to the protocol of the HTTP request in the HTTP request), and meanwhile obtains the user name and password input by the user from the request, then the terminal binding module 215 sends the user name and password to the user management module 214, the user management module 214 verifies the user name and password (this verification can also be implemented by the terminal binding module 215 itself, at this time, it needs to obtain the user information from the user management module 214 or the storage unit 210), if the verification is passed (i.e. the user name and password are both matched with the user name and password assigned by the user management module 214), then the terminal binding module 215 associates the terminal ID with the user name that has passed the verification included in the request, the generated data structure information including the user name-password-associated device ID-associated user terminal ID is stored in the storage unit 210, and if the verification fails, the binding request is rejected. Thus, when an abnormality occurs, the alarm module 213 can find the corresponding user and the user terminal thereof according to the abnormal device ID, so as to output the generated alarm information to the user page or the user terminal of the user, thereby outputting the alarm prompt of the corresponding device to the designated user. Therefore, through the system provided by the embodiment of the invention, the account information can be distributed to the user and the administered equipment can be appointed for the corresponding user according to the requirement, and then the user can bind the commonly used user terminal to the system platform provided by the embodiment of the invention according to the convenience of the user, so that the alarm information can be output to the bound user terminal, the user can check the alarm information at any time conveniently, and the timely supervision and maintenance of the equipment can be realized.
Fig. 3 schematically shows a frame structure of a system for critical parameter early warning of equipment in still another embodiment of the present invention. As shown in fig. 3, the system according to the embodiment of the present invention is similar to the system shown in fig. 2, and the difference is that an alarm policy setting module 216 is further provided in the system platform 21, so as to set an alarm policy according to a requirement, so that the abnormality detection module 212 performs corresponding abnormality detection processing according to the alarm policy, and further the alarm module 213 can generate alarm information according to the set alarm policy and output the alarm information. The alarm policy setting module 216 stores the set alarm policy into a corresponding record of an abnormal configuration information database corresponding to the device ID according to the device ID after receiving the setting of the user through the user page, that is, the abnormal configuration information generated at this time includes the device ID, the threshold type, the upper limit threshold, the lower limit threshold, the alarm policy, and parameter information corresponding to the alarm policy. The alarm strategy in the embodiment of the invention can be set to comprise a continuous deterioration alarm strategy, a period limit alarm strategy and a fluctuation range limit alarm strategy, and the parameter information corresponding to the alarm strategy in the embodiment of the invention is a fluctuation range and an alarm period. In other embodiments, other alarm strategies may be set based on actual requirements according to the characteristics and actual conditions of the devices and the key parameters, which are not limited in the embodiments of the present invention, and modifications and improvements made based on the concept of setting a certain optimization strategy to filter alarm points so as to achieve the effect of reducing the noise of the alarm message are all considered to be within the scope of the present invention. The embodiment of the invention is mainly elaborated based on a continuous deterioration alarm strategy, a period limit alarm strategy and a fluctuation range limit alarm strategy.
The continuous deterioration alarm strategy refers to that an abnormal value is compared with a last alarm value, and an alarm is given only when the abnormal value is deteriorated, and for example, the continuous deterioration alarm strategy can be realized as follows: when the pressure anomaly detection module 212 detects an anomaly again, the alarm module 213 firstly compares the current anomaly value with the previous early-warning value to judge whether deterioration occurs according to the comparison result, and generates alarm information to output if the deterioration occurs, namely, if the anomaly value is greater than the upper limit threshold and the current anomaly value is higher than the previous early-warning value, the abnormal condition is deteriorated, and then an alarm is given; if the abnormal value is smaller than the lower limit threshold value and the abnormal value is lower than the early warning value of the last time, the abnormal condition is worsened, and an alarm is given at the moment; and if not, no alarm is given.
The period limit alarm strategy refers to designating an alarm period, performing anomaly detection once in each period, and alarming if a key parameter value during detection exceeds a threshold value, and for example, the method can be realized as follows: setting an alarm period for a period limit alarm strategy, timing by the abnormality detection module 212 according to the alarm period, acquiring the latest key parameter value from the storage unit by the abnormality detection module 212 when the time interval of the alarm period is reached, respectively comparing the key parameter value with an upper limit threshold value and a lower limit threshold value, and alarming if the key parameter value is greater than the upper limit threshold value or less than the lower limit threshold value. Taking the liquid helium pressure of the nmr as an example, the specific implementation of the strategy may be, for example: setting a period limit alarm strategy for key parameters of liquid helium pressure of certain nuclear magnetic resonance equipment, setting an alarm period to be 30 minutes, acquiring the alarm strategy by the abnormity detection module 212 for judgment, acquiring a threshold period for timing when the period limit alarm strategy is judged, reading a liquid helium pressure value from the storage unit every 30 minutes, acquiring the latest primary liquid helium pressure data value from the liquid helium pressure value, comparing the value with an upper limit threshold value and a lower limit threshold value corresponding to the set liquid helium pressure respectively, and generating alarm information for alarming immediately when the value exceeds the threshold value. In a preferred embodiment, the period-limited alarm strategy may also be implemented to perform anomaly detection based on a changed alarm period, for example, two alarm periods are set, namely a first alarm period and a second alarm period, the first alarm period is set to a longer time interval, such as 30 minutes, the second alarm period is set to a shorter time interval, such as 5 minutes, and anomaly detection of the key parameter is switched between the first alarm period and the second alarm period, namely anomaly detection is performed for a period of time based on the time interval defined by the first alarm period, and anomaly detection is performed for a subsequent period of time based on the time interval defined by the second alarm period. The switching method may be based on the alarm frequency, and when the alarm frequency is higher, the anomaly detection is performed through a shorter alarm period, and when the alarm frequency is lower, the anomaly detection is performed through a longer alarm period. For example, the method can be implemented such that for a certain key parameter, abnormality detection is performed based on a first alarm period at the beginning, that is, abnormality is detected every 30 minutes, and if the latest data value at that time is abnormal, an alarm is performed; when the alarm occurs (namely after the alarm is given for the first time), switching to abnormal detection based on a second alarm period, namely detecting the abnormality every 5 minutes, and if the latest data value at that time is abnormal, giving an alarm; and when the alarm is not needed for a plurality of times, such as three times, under the short alarm period (namely the latest data values detected for three times are not abnormal values), switching to the first alarm period to perform the abnormal detection, and so on. Therefore, the short-period abnormity detection is adopted when the alarm is frequent, and the long-period abnormity detection is adopted when the alarm is sparse. Under the implementation mode of the change period, after the alarm occurs, if the alarm continuously exceeds the threshold value, the parameter change condition can be monitored in real time, and if the alarm only occasionally exceeds the threshold value by a certain number, the parameter change condition can be immediately recovered to a long period, so that frequent early warning is avoided.
The fluctuation range limiting alarm strategy is to alarm when the fluctuation of the key parameter in a specified period exceeds a fluctuation range threshold value. The policy may be implemented, for example, as: when an alarm strategy is limited by a fluctuation range, alarm strategy parameter information of an alarm period and the fluctuation range is set, an abnormality detection module acquires parameters of the alarm period and the fluctuation range after acquiring an identifier of the alarm strategy, timing is carried out according to the alarm period, when a time interval of the alarm period is reached, an abnormality detection module 212 acquires a maximum value and a minimum value of key parameters in the time interval range of the alarm period from a storage unit, calculates a fluctuation value of the key parameters according to the maximum value and the minimum value, compares the fluctuation value with the fluctuation range, and alarms when the fluctuation value exceeds a threshold value limited by the fluctuation range. Taking the liquid helium pressure of the nmr as an example, the specific implementation of the strategy may be, for example: setting a fluctuation range limited alarm strategy for key parameters of liquid helium pressure of certain nuclear magnetic resonance equipment, setting an alarm period of 30 minutes and a fluctuation range of 10 percent, obtaining the alarm strategy by an abnormality detection module for judgment, obtaining the alarm period for timing when the fluctuation range limited alarm strategy is judged, carrying out abnormality detection every 30 minutes according to the timing result, specifically obtaining the maximum value Amax and the minimum value Amin of the liquid helium pressure data within 30 minutes from a storage unit, subtracting the maximum value Amax and the minimum value Amin to obtain the absolute value of the fluctuation value which is a fluctuation value, then obtaining the fluctuation range, the upper limit threshold value and the lower limit threshold value corresponding to the liquid helium pressure of the equipment by the abnormality detection module, calculating the fluctuation range threshold value set for the liquid helium pressure of the equipment to be (upper limit threshold value-lower limit threshold value) × 10 percent, and then comparing the fluctuation value with the fluctuation range threshold value, and if the fluctuation value is larger than the fluctuation range threshold value, namely | Amax-Amin | > (upper limit threshold value-lower limit threshold value) × 10%, generating alarm information to alarm.
Because the user receives a plurality of alarm messages exceeding the threshold value in a mode of immediately alarming if the threshold value is exceeded every time, and some alarm messages just exceeding the threshold value are sometimes not serious alarms, especially under the condition that the user binds a great number of devices, the alarm messages received by the user are many, and the alarm messages which are not serious become noise, and the really useful alarm messages are submerged, the embodiment of the invention is additionally provided with the alarm strategy setting module, so that the user can select or set the alarm strategy according to the actual needs to reduce the noise through the limitation of the alarm strategy. In order to reduce noise, besides setting an alarm strategy, the method can also be realized by increasing the threshold range (i.e. modifying the threshold range, increasing the upper threshold limit, decreasing the lower threshold limit), however, this approach results in a reduction in the real-time nature of the alarm (i.e., real-time detection is not possible), and therefore the noise reduction scheme in the preferred embodiment is implemented by setting the alarm strategy described above, the most preferred implementation is by setting a continuously deteriorating alarm strategy, namely, only under the condition that the key parameter data of the equipment is continuously deteriorated, the alarm is given, so that the continuous deterioration value can be reported in time, the equipment which needs attention urgently is highlighted in the alarm message, namely, the important alarm message is highlighted, so that the noise interference is reduced to the maximum extent on the premise of not compromising the real-time performance. The alarm policy setting module 216 may store the alarm policy in the form of a character identifier, for example, a "1" identifier stored in a database record is used to continuously deteriorate the alarm policy, a "2" identifier fluctuation range defines the alarm policy, and a "3" identifier cycle defines the alarm policy, and the alarm module stores the alarm time and the alarm value in the record of the alarm information database of the corresponding device each time the alarm module generates an alarm message, so that, when the anomaly detection module receives a data update message, the alarm policy of each key parameter of the current device is first obtained from the anomaly configuration information, the anomaly detection is started according to the obtained alarm policy, and the alarm module is notified to alarm when the anomaly conforming to the alarm policy is detected, therefore, the alarm module does not directly generate an alarm message to output for each anomaly value, but performs judgment according to the alarm policy, when the corresponding conditions under the set alarm strategy are met, the alarm message is generated and output, and the noise is effectively reduced.
Fig. 4 schematically shows a flow of a method for anomaly analysis and early warning of a critical parameter of a device according to an embodiment of the present invention, taking the device as a nuclear magnetic resonance device and taking the critical parameter as liquid helium pressure as an example, as shown in fig. 4, the method includes:
step S401: and presetting a liquid helium pressure threshold of the equipment, and storing the preset liquid helium pressure threshold.
And receiving the setting of the liquid helium pressure threshold value by the user through a page, and generating a liquid helium pressure threshold value information record according to the setting of the user so as to obtain a data table structure shown in the following table.
Device ID Upper threshold value Lower threshold
TABLE 2
As shown in table 2, the liquid helium pressure threshold includes an upper threshold and a lower threshold, the upper threshold is used to represent an upper limit value of the liquid helium pressure value, the lower threshold is used to represent a lower limit value of the liquid helium pressure value, and when the actually acquired liquid helium pressure value exceeds the upper threshold or is lower than the lower threshold, it indicates that the liquid helium pressure is abnormal.
Step S402: and collecting the device log.
The nuclear magnetic resonance device is connected with a data acquisition module (i.e., the device log acquisition module shown in fig. 1), so that the device log is read from the device through the data acquisition module and uploaded (e.g., sent through a network) to the system platform. The device log collection module can be set as a data collection box, each device is provided with the data collection box, device logs in the device are read through the data collection box, and then the read device logs are sent to a storage unit of a system platform deployed on a cloud server through a network communication module (such as a 3G/4G module) of the data collection box to be stored. The device log may be obtained in real time by detecting a file change flag bit of the device log through software (e.g., filehead, rsync, tail, flash, etc.), or may be obtained in a cycle manner according to a set time period by setting an obtaining time period. The embodiment of the present invention is described by taking cyclic acquisition according to a set time period as an example, for example, the set time period is 15 seconds, then after the device log is acquired last time, the following steps are performed, when the following steps of processing the device log are completed, a timer is started to start timing, when the 15 seconds of timing are completed, the next device log acquisition processing is performed, that is, the acquisition processing of the step is started again, and after the acquisition is completed, the following steps are performed, so that cyclic acquisition and analysis and judgment of the device log are performed according to the set waiting time period.
Step S403: and analyzing the equipment log to generate an equipment liquid helium pressure information database.
The method comprises the steps of traversing an equipment log transmitted by an acquisition module for analysis, extracting key information in the equipment log mainly through a feature matching algorithm, wherein the content of the key information is defined according to specific equipment, for example, for a liquid helium Pressure value of nuclear magnetic resonance equipment, the key information can be Time and the liquid helium Pressure value, so that the equipment log is subjected to feature matching through keywords of the Time (such as Time _ Stamp) and the liquid helium Pressure value (such as He _ Pressure), values of the key information, namely the Time and the liquid helium Pressure value are obtained, and then the extracted key information is stored in a database as an index unit to generate a liquid helium Pressure information database of each nuclear magnetic resonance equipment. The concrete implementation is as follows: reading the device log uploaded by the acquisition module from the cloud server, forming a database structure with the key information as an index unit according to preset key information, analyzing the device log through a feature matching algorithm, acquiring historical records related to the key information, including time and liquid helium pressure values, from the device log, and forming liquid helium pressure information of corresponding devices to be stored in a database. Thus, a table structure of the magnetic resonance device is formed with the device ID (the device ID is a unique identifier assigned when the device is registered on the system platform), the time and the liquid helium pressure value as fields, and the contents of the corresponding fields extracted from the device log are stored in the table structure, so that a liquid helium pressure information database of the magnetic resonance device is formed, for example, the contents of the database shown in the following table:
device ID Time Liquid helium pressure value
TABLE 1
Step S404: and acquiring the maximum value and the minimum value of the liquid helium pressure at the current time of the day from the equipment liquid helium pressure information database, and acquiring a threshold value.
And acquiring the maximum value and the minimum value of the liquid helium pressure of each equipment from the current day to the current time according to the history of the liquid helium pressure values stored in the equipment liquid helium pressure information database, and acquiring the upper limit threshold value and the lower limit threshold value of the liquid helium pressure threshold value of the equipment from the liquid helium pressure threshold value information record according to the equipment ID of the current equipment. The method can be realized through database operation, and therefore, the specific implementation mode is not described in detail. It should be noted that, after the processing of step S401 and step S402, the history information of the liquid helium pressure value is the latest at present, and therefore, the obtained maximum value and minimum value are also the latest in real time maximum value and minimum value of the liquid helium pressure until the current is cut.
Step S405: and judging whether the current equipment is abnormal or not according to the maximum value and the minimum value of the liquid helium pressure and the liquid helium pressure threshold.
After the maximum value and the minimum value of the liquid helium pressure at the current cut-off and the liquid helium pressure threshold of the equipment are obtained, the maximum liquid helium pressure value is compared with the upper limit threshold of the liquid helium pressure threshold, the minimum liquid helium pressure value is compared with the lower limit threshold, and according to the comparison result, when the maximum liquid helium pressure value is larger than the upper limit threshold or the minimum liquid helium pressure value is smaller than the lower limit threshold, the liquid helium pressure of the current equipment is judged to be abnormal. If it is determined that an abnormality has occurred, step S406 is performed, and if it is determined that an abnormality has not occurred, step S401 is performed, and the collection of the log is started again.
Step S406: and judging whether the time value is the pre-warned past time value.
When the judgment result is that the abnormality occurs, comparing the time and pressure value information corresponding to the equipment ID with the abnormality and the liquid helium pressure value with the stored alarm information, judging whether the current abnormal value and the occurrence time are the alarm information, that is, whether the alarm has been given for the abnormality, if the alarm has been given, the alarm is not repeated, so that the operation of collecting the log is started again in step S401, and if the alarm has not been given for the current abnormality, at this time, the operation of step S407 is performed. Because the embodiment of the invention analyzes and judges the abnormity by obtaining the minimum value and the maximum value of the current time cut off the current day in the historical record, the minimum value and the maximum value of the current time cut off the current day can be the information values which are already alarmed, and the information which is already alarmed is not alarmed again, so the embodiment of the invention filters the information by the step, and avoids the repeated alarming of the same abnormity.
Step S407: and generating liquid helium pressure alarm information and outputting the alarm information.
When the judgment result is that the alarm information is abnormal, liquid helium pressure alarm information is generated and output according to the equipment ID with the abnormality and the time and pressure value information corresponding to the liquid helium pressure value with the abnormality, wherein the alarm information at least comprises the equipment ID, the abnormal liquid helium pressure value and the occurrence time thereof, and can also comprise other contents such as equipment name or address. The time and pressure value information corresponding to the abnormal liquid helium pressure value can be obtained by obtaining the liquid helium pressure value and the corresponding time at the same time when obtaining the maximum value and the minimum value, and when judging that the maximum value or the minimum value is an abnormal value (namely the maximum value is greater than the upper limit threshold value or the minimum value is less than the lower limit threshold value), generating alarm information directly according to the abnormal value and the corresponding time; when the maximum value or the minimum value is judged to be an abnormal value, corresponding time (the time is the time when the corresponding liquid helium pressure value occurs) is acquired from the liquid helium pressure information database through the equipment ID and the abnormal value, and alarm information is generated.
By the method, the monitoring of the liquid helium pressure of the nuclear magnetic resonance equipment based on the equipment log and the alarming when the abnormality occurs according to the monitoring result can be realized. In addition, in the embodiment of the invention, the abnormality judgment is carried out through the maximum value and the minimum value every time, and the alarm is carried out as long as the abnormality is not alarmed, so that the alarm is carried out when the deterioration is continued, and the noise is reduced on the basis of ensuring the timeliness. In the embodiment of the invention, the device log is uploaded to the cloud, namely, the analysis and the early warning of the data can be processed at the cloud instead of the traditional processing and display at the device, so that the monitoring and the early warning of a plurality of devices can be realized at the same time, the remote monitoring and the early warning can be realized, the labor cost is reduced, and the efficiency is improved. It should be noted that, in other embodiments, the abnormality determination may also be performed not by the maximum value and the minimum value, but by traversing the real-time data in the acquired liquid helium pressure information database, and when the value exceeds the threshold, an alarm message is generated to alarm, which is only one preferred implementation manner shown in fig. 4.
In other embodiments, the equipment factor detected in the embodiments of the present invention may not be limited to the liquid helium pressure value, and may also be, for example, the liquid helium level, the cold head temperature, the shield layer temperature, and the like. The apparatus may not be limited to a nuclear magnetic resonance apparatus, and may be other medical apparatuses such as CT, DR, mammary machine, vascular machine, and ultrasound. When the medical equipment is other medical equipment, the early warning element of the liquid helium pressure in the embodiment of the invention can be correspondingly changed into the key parameter corresponding to each piece of equipment, and the specific method for acquiring and analyzing the equipment log, setting the threshold value and judging based on the threshold value can be adaptively adjusted according to the specific description of the embodiment of the invention. In an optimal embodiment, the method and the system of the embodiment of the invention can not only monitor and early warn the key parameters of a single device, but also monitor and early warn a plurality of key parameters of the device simultaneously.
Fig. 5 schematically shows a flow of a method for warning key parameters of a device in another embodiment of the present invention, in an embodiment of the present invention, an alarm policy is further set for an alarm message, and the method of this embodiment performs anomaly detection and alarm according to the set alarm policy, so as to avoid the disadvantage of message noise caused by excessive alarm information. Taking equipment as nuclear magnetic resonance equipment, and taking key factors of monitoring and early warning simultaneously as examples, the key factors comprise liquid helium pressure, liquid helium level, cold head temperature, shielding layer temperature, water flow and water temperature, as shown in fig. 5, the method comprises the following steps:
step S501: presetting a threshold value and an alarm strategy for key parameters of equipment, and generating and storing abnormal configuration information.
Receiving the setting of the threshold and the alarm policy of the device by the user through the user page, wherein the setting of the threshold is the same as the method in the step S403, but the difference is that the type of the threshold needs to be set when the threshold is set in the embodiment of the present invention, that is, the threshold corresponds to which key parameter, so that the information included in the setting of the threshold includes the threshold type, the specific threshold and the corresponding device ID. The setting of the alarm policy may be input or selected through a user page, and the embodiment of the present invention is described by taking selection as an example. In embodiments of the present invention, alternative alarm strategies are configured to include a continuous deterioration alarm strategy, a period-limited alarm strategy, and a fluctuation range-limited alarm strategy, wherein the meaning of the various alarm strategies is as described above. After the set threshold information and alarm strategy are obtained, the threshold and alarm strategy are stored as the abnormal configuration information database of the corresponding device, that is, the threshold information and alarm strategy are respectively generated as the fields of the abnormal configuration information database of the corresponding device according to the device ID, and the values thereof are stored in the corresponding fields, wherein the alarm strategy can be stored as characters for respectively identifying different strategies, for example, the continuous deterioration alarm strategy is stored as a character "1", the cycle limit alarm strategy is stored as a character "2", and the fluctuation range limit alarm strategy is stored as a character "3". Meanwhile, according to the definition of the alarm policy, alarm period and fluctuation range fields are also generated in the abnormal configuration information database of the device, that is, the table information of the abnormal configuration information database generated in this embodiment is shown in the following table:
Figure BDA0001495338830000171
TABLE 4
Therefore, according to the condition of each key parameter of different equipment, a threshold value and an alarm strategy are set, and the abnormal configuration information can be generated and stored to be used as a reference for judging whether the corresponding key parameter of the different equipment is abnormal or not and whether an alarm is given or not.
Step S502: and collecting device log storage.
In this step, the method for acquiring device log storage is the same as the method shown in fig. 4, and may still be implemented by setting a data acquisition box on the device and uploading the data acquisition box to the cloud.
Step S503: and acquiring and analyzing the stored equipment log to generate an equipment key parameter information database.
In this step, the method for analyzing the device log is the same as the log analysis method shown in fig. 4, but different from the method for analyzing the log in the embodiment of the present invention, the method for analyzing the device log simultaneously analyzes a plurality of key parameters of the nmr device to obtain a data record containing a plurality of key parameter information, the key parameter information for matching and resolving includes a liquid helium level, a liquid helium pressure, a water flow, a water temperature, a shielding layer temperature, and a cold head temperature, and taking analyzing the log at a certain time of the device with the device ID MR _000af77b8aa5 as an example, the generated key parameter information data record may be as shown in the following table:
Figure BDA0001495338830000181
TABLE 3
The device ID is an ID of the current device, and is a unique device identifier assigned when the device is registered in the system according to the embodiment of the present invention, and the time is a recording time of corresponding data analyzed from the device log.
Step S504: and acquiring an alarm strategy corresponding to each key parameter of the equipment, and performing corresponding abnormal alarm processing according to the alarm strategy.
Firstly, according to the ID of the current detected equipment, key parameters corresponding to the current equipment and alarm strategies corresponding to the key parameters are obtained from an abnormal configuration information database, then abnormal detection is carried out according to the alarm strategies, and alarm information is generated and output when the abnormal condition is judged. The method for acquiring the alarm strategy is realized through database operation, namely, the device ID is matched with the device ID in the abnormal configuration information, so that the threshold type and the alarm strategy are acquired, wherein the threshold type corresponds to the corresponding key parameter of the device. And performing corresponding abnormal alarm processing according to the alarm strategy, specifically, firstly, judging according to the obtained identification content of the alarm strategy, and executing the abnormal alarm processing of the corresponding strategy according to the judgment result, wherein the abnormal alarm processing comprises the following three conditions: in case one, if the acquired alarm policy content is "1", that is, it represents a persistent deterioration alarm policy, the process of step S505 is executed; in case two, if the identification content of the alarm policy is "2", that is, the cycle limit alarm policy, then the processing of step S507 is executed; case three: if the identification content of the alarm policy is "3", that is, the alarm policy is defined for the fluctuation range, the process of step S509 is executed.
Step S505: and acquiring the maximum value and the minimum value of each current key parameter on the current day, and acquiring the corresponding upper threshold and lower threshold according to the equipment ID and the key parameters.
If the alarm policy is a key parameter of the continuous deterioration alarm policy, the maximum value and the minimum value of each current key parameter of the current equipment on the current day are obtained from the key parameter information database of the current equipment, specifically, the maximum value and the minimum value of each current key parameter of the current equipment on the current day are obtained through traversing the key parameter information database generated in step S502 and a database retrieval formula, taking the currently detected equipment ID as MR _000af77b8aa5 as an example, the key parameters corresponding to the policy are respectively liquid helium pressure, water flow and cold head temperature, and then the maximum value and the minimum value of the current time of the liquid helium pressure on the current day, the maximum value and the minimum value of the current time of the water flow on the current day and the maximum value and the minimum value of the current time of the cold head temperature on the current day are obtained. Meanwhile, according to the ID of the current equipment and the key parameter information, threshold value information of each key parameter of the current equipment is obtained from the equipment abnormal configuration information, wherein the key parameter information corresponds to the threshold value type in the abnormal configuration information, so that an upper threshold value and a lower threshold value corresponding to each key parameter of the equipment, namely an upper threshold value and a lower threshold value of liquid helium pressure, an upper threshold value and a lower threshold value of water flow, and an upper threshold value and a lower threshold value of cold head temperature, are obtained.
Step S506: and judging whether the current equipment is abnormal or not according to the maximum value and the minimum value of each key parameter at the current time of the day and the corresponding threshold value.
The maximum value of each key parameter of the current equipment (namely, the alarm strategy is the key parameter of the continuous deterioration alarm strategy) is compared with the upper threshold corresponding to the key parameter, the minimum value of each key parameter of the current equipment is compared with the lower threshold corresponding to the key parameter, and when the comparison result shows that the maximum value is larger than the upper threshold or the minimum value is smaller than the lower threshold, the abnormal condition is judged to occur, namely, the abnormal condition occurs at the recording time corresponding to the corresponding maximum value or/and the minimum value of the key parameter. For example, taking table 3 and table 4 as an example, the current device ID is MR _000af77b8aa5, the maximum value and the minimum value of the liquid helium pressure at the end of the current day of 10 months and 1 day of 2017 of the key parameters acquired through step S504 are 3.976 and 3.94, the maximum value and the minimum value of the water flow are both 0.054, and the maximum value and the minimum value of the coldhead temperature are 4.353 and 4.304, and by matching the device ID with the abnormal configuration information, i.e., the device ID in table 4, and matching the key parameters with the threshold types, the threshold values of the key parameters of the current device, i.e., the device ID MR _000af77b8aa5, can be obtained as follows: the upper threshold of the liquid helium pressure is 4.1, the lower threshold is 3.9, the upper threshold of the water flow is 10, the lower threshold is 4.2, the upper threshold of the cold head temperature is 4.5, and the lower threshold is 3.9. Comparing the maximum value and the minimum value of the liquid helium pressure with an upper limit threshold value and a lower limit threshold value of the liquid helium pressure respectively, wherein 3.976<4.1 and 3.94>3.9 results in that the liquid helium pressure is not abnormal by the current time of the day; similarly, the maximum value and the minimum value of other key parameters, namely the water flow and the cold head temperature, are respectively compared with the upper limit threshold and the lower limit threshold corresponding to each key parameter, so that the current time of the ending day can be obtained, the liquid helium level and the cold head temperature are not abnormal, and the water flow is abnormal because the minimum value is smaller than the lower limit threshold.
Because the maximum value and the minimum value of the current key parameter are acquired under the strategy, the maximum value and the minimum value are possible to be alarmed, namely, the abnormity which occurs before is not the abnormity which occurs newly, at the moment, in order to avoid the repeated alarming of the same abnormity, whether the alarming reminding is performed aiming at the abnormity needs to be judged, if the alarming reminding is performed, the log collection is continued, the new round of abnormity detection is started according to the collected log, and if the alarming reminding is not performed, the step S511 is performed. The judgment of whether the repeated alarm is performed may be storing the information of each alarm, performing matching judgment when an abnormality occurs, or performing status marking on the alarm record. The method detects the abnormity by comparing the current maximum value and the current minimum value cut off on the same day with the threshold value, and can meet the strategy requirement of early warning only after continuous deterioration because the current extreme value on the same day is detected every time, and can also meet the real-time requirement of abnormity warning because the abnormity detection, namely the acquisition and judgment of data, is based on real-time data, thereby reducing the alarm noise under the condition of not compromising the real-time.
Step S507: and acquiring an upper threshold, a lower threshold and an alarm period corresponding to each key parameter.
And limiting key parameters of the alarm strategy as a period for the alarm strategy, and acquiring an upper limit threshold, a lower limit threshold and an alarm period corresponding to each key parameter from an abnormal configuration information database according to the currently detected equipment ID. For example, taking a magnetic resonance apparatus with the apparatus ID of MR _000af77b8aa5 currently being examined as an example, if the key factor for acquiring the alarm policy as the alarm period limit is the shield layer temperature, the alarm period of the shield layer temperature is 30, the upper threshold is 50, and the lower threshold is 40.
Step S508: and acquiring the latest key parameter data value at that time according to the alarm period, and judging whether the current equipment is abnormal or not according to the latest data value, the upper threshold and the lower threshold.
And after the alarm period is obtained, carrying out abnormity detection based on the alarm period, specifically carrying out abnormity detection once in each alarm period, and judging that the abnormity occurs if the data value of the current key parameter exceeds the threshold value. For example, if the alarm period for acquiring the shield temperature of the nuclear magnetic resonance apparatus with the apparatus ID MR _000af77b8aa5 is 30, the key parameter information database is read once every 30 minutes, the latest shield temperature data value is acquired therefrom, the acquired latest shield temperature data value is compared with the upper threshold and the lower threshold of the shield temperature, and if the latest data value is greater than the upper threshold or less than the lower threshold, it is determined that an abnormality occurs. The calculation mode of the time interval of each alarm period can be realized by setting a timer for timing. When it is determined that an abnormality occurs, performing step S511; if no abnormity occurs, the method can return to the step of collecting the log to restart a round of equipment detection, or the collected log is set to be an asynchronous process to continuously collect data, and after the judgment is finished, a timer is started to start the timing of the alarm period, and the step S507 is carried out after the timing is finished. In a preferred embodiment, the set alarm period may include a long alarm period and a short alarm period, and the alarm period may be switched between the long period and the short period, for example, based on the alarm frequency, and the specific implementation may refer to the foregoing description.
Step S509: acquiring an upper threshold, a lower threshold, an alarm period and a fluctuation range corresponding to each key parameter, and respectively calculating the fluctuation value and the fluctuation range threshold of each key parameter.
And limiting key parameters of the alarm strategy for the fluctuation range of the current equipment, and acquiring an upper limit threshold, a lower limit threshold, an alarm period and a fluctuation range corresponding to each key parameter from the abnormal configuration information database. And timing according to the alarm period, when the time interval of the alarm period is reached, acquiring the maximum value and the minimum value of the corresponding key parameter in the time interval of the alarm period from the key parameter information database, performing difference on the maximum value and the minimum value to obtain the absolute value of the difference, and taking the absolute value as the fluctuation value of the key parameter in the time range of the alarm period. And after the fluctuation value is obtained, calculating the fluctuation range threshold of the key parameter according to the obtained upper limit threshold, lower limit threshold and fluctuation range of the corresponding key parameter by a formula (upper limit threshold-lower limit threshold) and the fluctuation range. For example, the critical parameters of the water temperature and the liquid helium level of the nuclear magnetic resonance equipment with the equipment ID of MR _000af77b8aa5 correspond to the fluctuation range limit alarm strategy, the alarm period, the upper limit threshold, the lower limit threshold and the fluctuation range of the two critical parameters are obtained according to the equipment ID and the threshold type (i.e. corresponding critical parameters), which are respectively: the upper limit threshold value of the water temperature is 28, the lower limit threshold value is 4, the fluctuation range is 10%, and the alarm period is 10%; the upper threshold of the liquid helium level is 100, the lower threshold is 60, the fluctuation range is 25%, and the alarm period is 15%. Therefore, the abnormal detection is respectively carried out according to the alarm periods of the water temperature and the liquid helium level, and specifically, a fluctuation value is calculated every 10 minutes for the key parameters of the water temperature: and acquiring the maximum value and the minimum value of the water temperature in the key parameter information database within 10 minutes, taking the maximum value-the minimum value and the absolute value to obtain the fluctuation value of the water temperature within 10 minutes, and acquiring the fluctuation range threshold value of (upper threshold value-lower threshold value) × 10%, namely (28-4) × 10%. Similarly, the fluctuation value calculation was performed every 15 minutes for the liquid helium level, and the fluctuation range threshold value corresponding to the liquid helium level was calculated to be (100-60) × 25%.
Step S510: and judging whether the current equipment is abnormal or not according to the calculated fluctuation value of the key parameter and the fluctuation range threshold value corresponding to the key parameter.
And comparing the fluctuation value of the corresponding key parameter with a fluctuation range threshold value, and if the fluctuation value exceeds, namely is larger than, the fluctuation range threshold value, judging that the abnormality occurs. As in the above example, the calculated fluctuation value of the water temperature is compared with the fluctuation range threshold value thereof, and the calculated fluctuation value of the liquid helium level is compared with the fluctuation range threshold value thereof, thereby determining whether or not an abnormality has occurred. When the abnormality is judged to occur, step S511 is performed, and if the abnormality does not occur, the step of collecting the log is performed to start the next detection judgment process, or the collected log is set to be an asynchronous process to continuously collect data, and after the judgment is finished, a timer is started to start the timing of the alarm period, and step S509 is performed after the timing is finished.
Step S511: and generating alarm information and outputting.
And when the abnormality is judged, acquiring the currently detected equipment ID, the abnormal key parameter and the abnormal information thereof, and generating alarm information for outputting, wherein the alarm information comprises the equipment ID, the key parameter, the abnormal time and the abnormal data content. In the continuous deterioration alarm strategy and the period limit alarm strategy, the abnormal time is the time corresponding to each acquired data, and the abnormal data content is the acquired data value corresponding to each key parameter; in the fluctuation range limited alarm strategy, the abnormal time is the time when the current period ends, and the abnormal data content comprises the fluctuation value of the key parameter in the alarm period, the fluctuation range threshold value and the corresponding alarm period duration.
Therefore, an alarm strategy can be set according to the requirement, and alarm is carried out based on the alarm strategy, so that noise pollution is reduced, and really important abnormal information is highlighted. Moreover, through the continuous deterioration alarm strategy, the alarm is given again only when the deterioration is continued, and really useful abnormal information can be highlighted on the basis of not compromising the real-time performance, so that a user can pay attention to deteriorated equipment in time, and the reference value of alarm information is improved. In the embodiment of the invention, the continuous deterioration alarm strategy is a preferable scheme compared with the period limiting alarm strategy, because the period limiting alarm strategy ignores data exceeding a threshold value and cannot highlight an alarm limit value, and the fluctuation range limiting alarm strategy is another preferable scheme and reflects the fluctuation speed of key parameter data. The three alarm strategies are combined, a reasonable and effective alarm mechanism is provided, the characteristics of key parameters can be adapted, and the requirement for reducing noise can be met. In a specific implementation, according to requirements, one of the alarm strategies may be set for each key parameter of the device, or a combined alarm strategy (for example, any combination of the three alarm strategies mentioned in the embodiments of the present invention) may be set for the same key parameter of the device, when a certain alarm strategy is set, an alarm is performed only if the condition of the corresponding alarm strategy is satisfied, and when a combined alarm strategy is set, an alarm is performed if the condition of any one of the combined alarm strategies is satisfied, for example, a persistent worsening alarm strategy and a fluctuation range limiting alarm strategy are simultaneously set for a certain key parameter, so that the fluctuation range alarm strategy is used as a supplement to the persistent worsening alarm strategy, the change trend of the parameter is reflected by the persistent worsening alarm strategy, and the change range of the parameter is reflected by the fluctuation range alarm strategy, when the change trend or the change amplitude meets a certain condition (the condition of continuously deteriorating the alarm strategy or the condition of limiting the alarm strategy by the fluctuation range) alarming is carried out. Thus, the alarm strategy corresponding to the key parameter of one device may be a combination of one or more alarm strategies, and fig. 5 shows that each key parameter of the nuclear magnetic resonance device corresponds to one alarm strategy, so that the nuclear magnetic resonance device corresponds to the situations of three alarm strategies at the same time.
In various embodiments of the present invention, generating the alarm information output refers to generating an information output including the device identification key parameter, the abnormal information, and the time when the abnormality occurs, where the output may be output to a user page, or sent to a user by a mobile phone short message or an email, or output to a user terminal, and the user terminal may be, for example, a WeChat or a client APP corresponding to the system of the embodiments of the present invention. Fig. 6 shows a specific implementation manner of outputting alarm information to a user terminal schematically, taking a user terminal as an example of WeChat, as shown in fig. 6, the method includes:
step S601: account information is assigned to the user and the device is associated with the account information.
The account information is distributed for each user, the equipment responsible for the user is appointed for the user distributed with the account, the account information comprising a user name and a password can be added through a user page, the equipment ID related to each account is distributed through the page, and then the user information database comprising the user name, the password and the equipment ID is generated according to the input of the page. In other embodiments, a mobile phone number or a mail of the user can be input when the account information is allocated, so that the alarm information can be conveniently sent to the user in a mobile phone short message or mail mode. A user page may also be provided, so that a user who has allocated an account can modify or add information thereof, such as a mobile phone number, a mail, and the like, through the user page.
Step S602: the account information of the user is associated with the WeChat of the user.
The user notes the public number through the WeChat, enters the page of the system through the public number to execute the binding operation, for example, correct account information, namely a user name and a password, allocated by the system is input in a binding page, then the binding request is sent to the system through a corresponding page option of a public number, the system receives the binding request of a user, the user name and the password input by the user are obtained from the binding request, validity verification is carried out, namely matching authentication is carried out on the user name and the password stored in a user information database so as to verify the identity of the user, if the authentication is successful, namely, the user name and the password which are matched with the user name and the password exist, the WeChat account number (namely, the WeChat OpenID) automatically carried in the request is associated with the user information and stored, so that the account information for sending the request is associated and bound with the WeChat account number of the user, namely, a user information database comprising user name-password-device ID-WeChat OpenID is generated. And if the system fails to verify the account information, feedback information of wrong user name or password is returned to the WeChat end of the user.
Step S603: and outputting the generated alarm information to a WeChat terminal of a corresponding user.
And then, after the alarm information is generated, the system acquires the micro signal bound by the user from the user information database according to the equipment ID needing alarming, and sends the generated alarm information to a micro message terminal corresponding to the micro message OpenID.
Through the steps, the user can bind the WeChat with the method and the system, so that the alarm prompt is sent to a communication tool commonly used by the user according to the habit of the user, the user is prompted in time, the user experience is improved, the method is efficient and rapid, and the traditional monitoring mode of watching is thoroughly liberated.
Those skilled in the art can understand that the output terminal in the embodiment of the present invention may be only one of WeChat, SMS, email, or client APP, or may be any combination of two or more.
It should be noted that, in other embodiments, the device log collection module may also be connected in an intranet of a hospital, the device log is uploaded to a database or a server of an appointment information system of the hospital through the intranet for storage, the analysis module acquires the device log from the database or the server of the appointment information system of the hospital, and the device information database generated after analysis is established on the server of the appointment information system of the hospital, so that the hospital can store information of the nmr device based on its own server or database, thereby preventing information leakage and ensuring information security of the hospital. In this case, the system of the embodiment of the present invention may be deployed on the hospital's own server. That is, by the method and the system of the embodiment of the present invention, each hospital can monitor and pre-warn all medical devices in its own hospital, and also can monitor and pre-warn all medical devices in all hospitals by using a cloud system, only the device log of each device needs to be obtained for analysis, a threshold and an alarm policy are set for each device, the obtained real-time maximum value and the obtained real-time minimum value of each device key parameter are compared with the threshold, and whether the condition of the alarm policy is met is determined when the device is abnormal, so that alarm information is generated according to the determination result to alarm and remind each device to the designated personnel.
In other embodiments, the manner of obtaining the real-time data values of the key parameters of the device may also be implemented by setting a sensor at a corresponding position of the device and connecting the sensor with a data acquisition box, in this manner, all the obtained real-time data values and the obtained time need to be stored to form a key parameter information data record of the device, and after obtaining the real-time values, the database operation is performed on the key parameter information data record, and the maximum value and the minimum value of the current time in the current day are extracted to determine whether an abnormality occurs and perform an early warning. The processing manner of the abnormality judgment and the early warning is the same as that of the foregoing embodiments.
In addition, the method and system of the embodiment of the present invention can also be implemented by an electronic device, which only needs to include a storage medium and a control unit, and stores the application program that implements the method or system of the embodiment of the present invention in the storage medium, and the control unit executes the application program to achieve the purpose of the present invention. Such an electronic device may be, for example, an intelligent terminal device (e.g., a smart phone or a smart watch) capable of carrying and executing an application program, or a tablet computer.
What has been described above are merely some embodiments of the present invention. It will be apparent to those skilled in the art that various changes and modifications can be made without departing from the inventive concept thereof, and these changes and modifications can be made without departing from the spirit and scope of the invention.

Claims (15)

1. The equipment key parameter early warning system comprises a data acquisition module and a system platform for carrying out abnormity analysis and early warning on equipment key parameters, wherein the system platform comprises a data acquisition module and a data acquisition module
The data acquisition module is connected with corresponding equipment and used for acquiring equipment logs of the equipment in real time and sending the equipment logs to the system platform, the equipment is medical equipment, and the system platform is deployed on a cloud server or a server special for the inside of a hospital;
the system platform comprises a key parameter information record generation module, an abnormality detection module, an alarm module and a storage unit,
the key parameter information record generating module is used for generating a data record of an equipment key parameter information database according to key parameter data obtained by analyzing the equipment log, wherein the data record in the key parameter information database comprises an equipment ID, a key parameter and time;
the abnormal detection module is used for carrying out abnormal judgment on the key parameter of the current equipment according to the key parameter information historical record of the current updated corresponding equipment in the key parameter information database and the stored abnormal configuration information when the key parameter information record generation module sends an update notification, and outputting a judgment result to the alarm module when the judgment result is abnormal, wherein the abnormal configuration information comprises an equipment ID, a threshold type corresponding to the key parameter type, an upper limit threshold value and a lower limit threshold value for judging whether the key parameter is abnormal, and the current updated corresponding equipment is identified by the equipment ID;
the alarm module is set to generate alarm information according to the judgment result output by the abnormity detection module and output the alarm information to a user page or a user terminal, the user terminal is one or the combination of more than two of WeChat, mail or client APP, and the alarm information comprises equipment ID or equipment name, key parameters, abnormal values and time.
2. The system of claim 1, wherein the system platform further comprises a threshold setting module configured to generate exception configuration information from the received threshold information, the threshold information including a device ID, a threshold type, an upper threshold, and a lower threshold, for storage in the storage unit.
3. The system of claim 1, wherein the system further comprises a user terminal, the system platform further comprises a user management module and a terminal binding module,
the user management module is used for distributing account information for the user and associating corresponding equipment information for the distributed account information;
the terminal binding module is used for associating the user terminal with the matched account information according to a binding request of the user terminal and the account information distributed by the user management module;
the alarm module is further configured to output the generated alarm information to the associated user terminal.
4. The system according to any one of claims 1 to 3, wherein the system platform further comprises an alarm policy setting module, configured to receive input alarm policy information, generate abnormal configuration information containing the alarm policy information, and store the abnormal configuration information in the storage unit;
and the abnormality detection module is also used for carrying out corresponding abnormality detection processing on each key parameter of the equipment according to the set alarm strategy.
5. The implementation method of the equipment key parameter early warning system according to claim 1, comprising:
configuring threshold information for key parameters of each device, and generating and storing abnormal configuration information, wherein the abnormal configuration information comprises a device ID, a threshold type corresponding to the key parameter type, an upper threshold and a lower threshold for judging whether the key parameters are abnormal;
acquiring an equipment log of equipment, analyzing, generating and storing equipment key parameter information, wherein the generated equipment key parameter information comprises an equipment ID and key parameters;
and carrying out abnormity judgment on the key parameters of the current equipment according to the stored key parameter information history record of the current equipment and the stored abnormal configuration information, and generating alarm information to output when the judgment result is abnormal, wherein the current equipment is equipment which acquires an equipment log at present and completes analysis and is identified by an equipment ID.
6. The method of claim 5, wherein the abnormal judgment of the key parameters of the current device is performed according to the stored history of the key parameter information of the current device and the stored abnormal configuration information, and when the judgment result is that the abnormality occurs, the alarm information output is generated by the following method:
acquiring the current maximum value and the current minimum value of each key parameter of the current equipment according to the stored key parameter information historical record, and acquiring the upper limit threshold value and the lower limit threshold value of the threshold type corresponding to each key parameter of the current equipment according to the abnormal configuration information;
and judging whether the abnormality occurs according to the acquired current maximum value and minimum value of each key parameter of the current equipment and the upper limit threshold value and the lower limit threshold value of the corresponding threshold value type, and generating alarm information to output when the judgment result is that the abnormality occurs and the current abnormality is not early-warning abnormality.
7. The method of claim 5 or 6, further comprising:
allocating user account information, configuring associated equipment for the allocated account information, and generating user information for storage;
receiving a binding request, configuring a related user terminal for the allocated account information according to the binding request and the stored user information, and generating user information storage simultaneously containing related equipment and the related user terminal;
and when the alarm information is output, acquiring a user terminal associated with the abnormal equipment according to the user information, and outputting the generated alarm information to the user terminal associated with the equipment.
8. The implementation method of the equipment key parameter early warning system according to claim 1, comprising:
configuring threshold information and an alarm strategy for key parameters of each device, and generating and storing abnormal configuration information, wherein the abnormal configuration information comprises a device ID, a threshold type corresponding to the key parameter type, an upper threshold and a lower threshold for judging whether the key parameters are abnormal, the alarm strategy and key parameter information corresponding to the alarm strategy;
acquiring an equipment log of equipment, analyzing, generating and storing equipment key parameter information, wherein the generated equipment key parameter information comprises an equipment ID and key parameters;
the method comprises the steps of obtaining an alarm strategy corresponding to each key parameter of current equipment, carrying out abnormity detection on each key parameter of the current equipment according to the alarm strategy of the corresponding key parameter of the current equipment, the key parameter information history record of the current equipment and stored abnormity configuration information, and generating alarm information output according to a detection result, wherein the current equipment is equipment which obtains an equipment log at present and completes analysis, and is identified through an equipment ID.
9. The method of claim 8, wherein the alarm strategy configured for each critical parameter comprises one of a persistent worsening alarm strategy, a period-limited alarm strategy, and a fluctuation range-limited alarm strategy, or a combination of both.
10. The method according to claim 9, wherein when the alarm policy corresponding to the key parameter is a continuous deterioration alarm policy, performing abnormality detection on each key parameter of the current device according to the alarm policy corresponding to the key parameter of the current device, the history of the key parameter information of the current device, and the stored abnormality configuration information, and generating an alarm information output according to the detection result includes:
acquiring the current maximum value and the current minimum value of the corresponding key parameter of the current equipment according to the stored key parameter information historical record, and acquiring the upper limit threshold value and the lower limit threshold value of the corresponding key parameter of the current equipment according to the stored abnormal configuration information;
and judging whether the abnormality occurs according to the acquired current maximum value and minimum value of the corresponding key parameter of the current equipment and the acquired upper limit threshold value and lower limit threshold value, and generating alarm information to output when the judgment result is that the abnormality occurs and the current abnormality is not early-warning abnormality.
11. The method according to claim 9, wherein when the alarm policy corresponding to the key parameter is a fluctuation range limited alarm policy, performing abnormality detection on each key parameter of the current device according to the alarm policy corresponding to the key parameter of the current device, the history of the key parameter information of the current device, and the stored abnormal configuration information, and generating an alarm information output according to the detection result includes:
acquiring an upper limit threshold, a lower limit threshold, a fluctuation range and an alarm period of corresponding key parameters of current equipment according to the abnormal configuration information;
timing according to the alarm period, and acquiring the maximum value and the minimum value of the corresponding key parameter of the current equipment in the alarm period time interval from the stored key parameter information historical record at intervals of the alarm period;
calculating the fluctuation value of the corresponding key parameter of the current equipment in the corresponding alarm period according to the maximum value and the minimum value in the time interval;
calculating a fluctuation range threshold corresponding to the corresponding key parameter of the current equipment according to the upper limit threshold, the downlink threshold and the fluctuation range;
and carrying out abnormity judgment according to the fluctuation value and the fluctuation range threshold value, and generating alarm information to output when the abnormity is judged to occur.
12. The method according to claim 9, wherein when the alarm policy corresponding to the key parameter is a period-limited alarm policy, performing abnormality detection on each key parameter of the current device according to the alarm policy corresponding to the key parameter of the current device, the history of the key parameter information of the current device, and the stored abnormal configuration information, and generating an alarm information output according to the detection result includes:
acquiring an upper limit threshold, a lower limit threshold and an alarm period of corresponding key parameters of current equipment according to the abnormal configuration information;
timing according to the alarm period, and acquiring the latest data value of the corresponding key parameter of the current equipment when the information is acquired from the stored key parameter information historical record at intervals of the alarm period;
and carrying out abnormity judgment according to the latest data value, the upper limit threshold value and the downlink threshold value, and generating alarm information to output when the abnormity is judged to occur.
13. The method of claim 12, wherein the alarm period corresponding to the period-limited alarm policy includes a first alarm period and a second alarm period, the duration of the first alarm period is longer than the second alarm period, when the alarm policy corresponding to the key parameter is the period-limited alarm policy, performing anomaly detection on each key parameter of the current device according to the alarm policy of the corresponding key parameter of the current device, the key parameter information history of the current device, and the stored anomaly configuration information, and generating the alarm information output according to the detection result further includes generating the alarm information output according to the detection result
When a period limited alarm strategy is adopted for carrying out abnormity detection for the first time, setting the alarm period of corresponding key parameters of current equipment as a first alarm period;
when abnormality occurs, counting the output frequency of the alarm information, and switching the alarm period of the corresponding key parameter of the current equipment between a first alarm period and a second alarm period according to the output frequency of the alarm information when abnormality detection is not performed by adopting a period limited alarm strategy for the first time.
14. The method of any of claims 8 to 13, further comprising:
allocating user account information, configuring associated equipment for the allocated account information, and generating user information for storage;
receiving a binding request, configuring a related user terminal for the allocated account information according to the binding request and the stored user information, and generating user information storage simultaneously containing related equipment and the related user terminal;
and when the alarm information is output, acquiring a user terminal associated with the abnormal equipment according to the user information, and outputting the generated alarm information to the user terminal associated with the equipment.
15. An electronic apparatus characterized by comprising a storage medium storing an application program for implementing the system of any one of claims 1 to 4, and a control unit for executing the application program.
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