CN115802199B - Alarm threshold determining method and device, electronic equipment and readable storage medium - Google Patents
Alarm threshold determining method and device, electronic equipment and readable storage medium Download PDFInfo
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- CN115802199B CN115802199B CN202211319355.8A CN202211319355A CN115802199B CN 115802199 B CN115802199 B CN 115802199B CN 202211319355 A CN202211319355 A CN 202211319355A CN 115802199 B CN115802199 B CN 115802199B
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Abstract
The application relates to the technical field of data analysis and discloses a method and a device for determining an alarm threshold, electronic equipment and a readable storage medium. Wherein the method comprises the following steps: acquiring historical operation data generated by monitoring points at each historical moment; analyzing the historical operation data, and determining the distribution parameters, the highest alarm limit value and the lowest alarm limit value of the historical operation data; and dividing the alarm limit range corresponding to the highest alarm limit value and the lowest alarm limit value according to the distribution parameters to obtain the target alarm threshold value corresponding to the monitoring point. By implementing the application, the automatic generation and the automatic configuration of the alarm threshold value are realized, thereby realizing the intelligent configuration of the alarm threshold value, greatly reducing the time and the workload of manually configuring the alarm threshold value, avoiding the phenomena of mismatching, missed configuration and mismatching existing in the manual configuration to the greatest extent, and further improving the configuration accuracy, rationality and effectiveness of the alarm threshold value.
Description
Technical Field
The present application relates to the field of data analysis technologies, and in particular, to a method and apparatus for determining an alarm threshold, an electronic device, and a readable storage medium.
Background
With the rapid progress of the large environment of the China industry, how to ensure the safe operation of various operation processes of the industry is a concern of industrial technicians. At present, industrial alarm is basically adopted so that corresponding measures can be taken in time when the operation is abnormal. However, the configuration of the alarm limit value is manually configured by people, the workload of configuring the alarm limit value depends on the number of monitoring points, and if the number of the monitoring points is huge, the configuration workload of the alarm limit value is complex and complex, and inaccurate phenomena such as mismatch, missed configuration, incorrect configuration and the like are unavoidable. Therefore, how to realize accurate configuration of alarm limit values is needed to be solved.
Disclosure of Invention
In view of the above, the embodiments of the present application provide a method, an apparatus, an electronic device, and a readable storage medium for determining an alarm threshold, so as to solve the problem that the alarm threshold is not accurately configured manually.
According to a first aspect, an embodiment of the present application provides a method for determining an alarm threshold, including: acquiring historical operation data generated by monitoring points at each historical moment; analyzing the historical operation data, and determining distribution parameters, the highest alarm limit value and the lowest alarm limit value of the historical operation data; and dividing the alarm limit value range corresponding to the highest alarm limit value and the lowest alarm limit value according to the distribution parameters to obtain a target alarm threshold value corresponding to the monitoring point.
According to the method for determining the alarm threshold, the historical operation data of the monitoring points are obtained to analyze the operation state of the monitoring points, the distribution parameters of the historical operation data of the monitoring points are determined, and then the alarm threshold value aiming at the monitoring points is generated according to the distribution parameters so as to configure the alarm threshold value to the relevant monitoring points. The alarm threshold value corresponding to the monitoring point is reasonably generated by combining the historical operation data, so that the automatic generation and the automatic configuration of the alarm threshold value are realized, the intelligent configuration of the alarm threshold value is realized, the time and the workload for manually configuring the alarm threshold value are greatly reduced, the phenomena of mismatching, missed configuration and mismatching existing in the manual configuration are avoided to the greatest extent, and the configuration accuracy, the rationality and the effectiveness of the alarm threshold value are further improved.
With reference to the first aspect, in a first implementation manner of the first aspect, the analyzing the historical operation data and determining a distribution parameter, a highest alarm limit value and a lowest alarm limit value of the historical operation data include: analyzing the fluctuation state of the historical operation data and determining the distribution parameters of the historical operation data; determining a maximum value and a minimum value of the operation parameters according to the distribution parameters; and determining the maximum value of the operation parameter as the highest alarm limit value, and determining the minimum value of the operation parameter as the lowest alarm limit value.
According to the method for determining the alarm threshold, provided by the embodiment of the application, the reasonable highest alarm limit value and the reasonable lowest alarm limit value are conveniently determined according to the historical operation data by analyzing the fluctuation state of the historical operation data, so that the automatically generated alarm threshold value is more in accordance with the actual operation state of the monitoring point.
With reference to the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the analyzing a fluctuation state of the historical operation data, and determining a distribution parameter of the historical operation data includes: determining an operation data distribution curve of the monitoring point based on the fluctuation state of the historical operation data; and determining distribution parameters corresponding to the monitoring points based on the characteristics of the operation data distribution curve.
According to the method for determining the alarm threshold, provided by the embodiment of the application, the fluctuation state of the historical operation data is analyzed to determine the data distribution curve aiming at the monitoring points, and then the corresponding distribution parameters are determined, so that the distribution parameters are more reasonably determined, and the alarm threshold value generated later is more accurate.
With reference to the first aspect, in a third implementation manner of the first aspect, the acquiring historical operating data of the monitoring point includes: acquiring a preset sampling range and a preset sampling period; and collecting the historical operation data generated by the monitoring points based on the preset sampling period in the preset sampling range.
The method for determining the alarm threshold provided by the embodiment of the application supports setting the sampling range and the sampling period, so that the collection of the historical operation data is more flexible.
With reference to the first aspect, in a fourth implementation manner of the first aspect, the distribution parameter includes a variance, a control line coefficient, and a standard deviation estimation coefficient, and dividing, according to the distribution parameter, an alarm limit range corresponding to the highest alarm limit and the lowest alarm limit to obtain a target alarm threshold corresponding to the monitoring point, where the method includes: dividing the alarm limit value range into a plurality of parts based on the variance to obtain a plurality of alarm threshold values; determining an upper control threshold value and a lower control threshold value based on the control line coefficient and the standard deviation estimation coefficient; and determining the alarm threshold values, the upper control threshold values and the lower control threshold values as the target alarm threshold values.
According to the method for determining the alarm threshold, provided by the embodiment of the application, the alarm threshold ranges are divided to obtain the alarm threshold values, and the upper control threshold value and the lower control threshold value are determined based on the control line coefficient and the standard deviation estimation coefficient, so that the alarm threshold values are generated, and the target alarm threshold value is more in line with the actual industrial alarm service.
With reference to the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the distribution parameter further includes an alarm threshold value average difference, and the method further includes: and carrying out grading treatment on the target alarm threshold value according to the preset percentage of the average difference of the alarm threshold values to obtain a target gear corresponding to the target alarm threshold value.
According to the method for determining the alarm threshold, disclosed by the embodiment of the application, the gear of the target alarm threshold is configured according to the average difference of the alarm thresholds, so that the alarm limits of different gears are automatically configured, and the workload of manually configuring a plurality of alarm thresholds is reduced to the greatest extent.
With reference to the first aspect or any implementation manner of the first to fifth implementation manners of the first aspect, in a sixth implementation manner of the first aspect, the method further includes: detecting whether the real-time operation data of the monitoring point exceeds the target alarm threshold value; and generating alarm information when the real-time operation data exceeds the target alarm threshold value.
According to the method for determining the alarm threshold, when the real-time operation data is detected to exceed the target alarm threshold, alarm information is generated to remind a technician to take relevant measures in time, and the operation stability of an industrial process is guaranteed to the greatest extent.
According to a second aspect, an embodiment of the present application provides a device for determining an alarm threshold, including: the acquisition module is used for acquiring historical operation data generated by the monitoring points at each historical moment; the analysis module is used for analyzing the historical operation data and determining distribution parameters, the highest alarm limit value and the lowest alarm limit value of the historical operation data; and the dividing module is used for dividing the alarm limit value range corresponding to the highest alarm limit value and the lowest alarm limit value according to the distribution parameters to obtain a target alarm threshold value corresponding to the monitoring point.
According to a third aspect, an embodiment of the present application provides an electronic device, including: the alarm threshold determining device comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions so as to execute the alarm threshold determining method according to the first aspect or any implementation mode of the first aspect.
According to a fourth aspect, an embodiment of the present application provides a computer readable storage medium, where computer instructions are stored, where the computer instructions are configured to cause a computer to perform the method for determining an alarm threshold according to the first aspect or any implementation manner of the first aspect.
It should be noted that, the description of the corresponding content in the method for determining the alarm threshold is omitted herein for brevity.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method of determining an alarm threshold according to an embodiment of the present application;
FIG. 2 is another flow chart of a method of determining an alarm threshold according to an embodiment of the application;
FIG. 3 is yet another flow chart of a method of determining an alarm threshold according to an embodiment of the present application;
FIG. 4 is a schematic diagram of the results of the collection of historical operating data according to an embodiment of the application;
FIG. 5 is a schematic diagram of the distribution of historical operating data according to an embodiment of the application;
FIG. 6 is a block diagram of the structure of the alarm threshold determining apparatus according to the embodiment of the present application;
fig. 7 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
At present, industrial alarm is basically adopted so that corresponding measures can be taken in time when the operation is abnormal. However, the configuration of the alarm limit value is manually configured by people, the workload of configuring the alarm limit value depends on the number of monitoring points, and if the number of the monitoring points is huge, the configuration workload of the alarm limit value is complex and complex, and inaccurate phenomena such as mismatch, missed configuration, incorrect configuration and the like are unavoidable. Therefore, how to realize accurate configuration of alarm limit values is needed to be solved.
Based on the method, the technical scheme of the application reasonably generates the alarm threshold value corresponding to the monitoring point by combining the historical operation data, and realizes the automatic generation and the automatic configuration of the alarm threshold value, thereby avoiding the phenomena of mismatching, missed configuration and mismatching existing in the manual configuration, and further improving the configuration accuracy, rationality and effectiveness of the alarm threshold value.
In accordance with an embodiment of the present application, there is provided an embodiment of a method of determining an alarm threshold, it being noted that the steps shown in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than what is shown or described herein.
In this embodiment, a method for determining an alarm threshold is provided, which may be used in an electronic device, such as a mobile phone, a computer, a server, etc., fig. 1 is a flowchart of a method for determining an alarm threshold according to an embodiment of the present application, and as shown in fig. 1, the flowchart includes the following steps:
s11, acquiring historical operation data generated by the monitoring points at each historical moment.
The historical time is the collection time aiming at the monitoring point, the historical operation data is the data which is generated by the monitoring point and used for representing the operation state, and the data can be a current value, a voltage value, electric quantity, water quantity, flow and the like. Corresponding acquisition devices, such as meters, sensors and the like, are pre-deployed at each monitoring point, and are in communication connection with the electronic devices. The acquisition device can upload the data acquired by the acquisition device at each acquisition time to the electronic device, and accordingly, the electronic device can receive the historical operation data generated by each monitoring point at each historical time, wherein the historical operation data carries a time stamp, so that the electronic device can sort the received historical operation data according to the time stamp.
S12, analyzing the historical operation data, and determining the distribution parameters, the highest alarm limit value and the lowest alarm limit value of the historical operation data.
The electronic equipment analyzes the plurality of historical operation data received by the electronic equipment to determine the change state of the historical operation data generated at the monitoring point, and determines the data distribution state of the monitoring point according to the change state of the historical operation data, so as to determine the distribution parameters of the monitoring point based on the current distribution state. And meanwhile, comparing the historical operation data to determine the highest operation parameter value and the lowest operation parameter value, determining the highest alarm limit value of the abnormal alarm according to the highest operation parameter, and determining the lowest alarm limit value of the abnormal alarm according to the lowest operation parameter value.
And S13, dividing the alarm limit value range corresponding to the highest alarm limit value and the lowest alarm limit value according to the distribution parameters to obtain a target alarm threshold value corresponding to the monitoring point.
The target alarm threshold value is an abnormal operation alarm threshold value corresponding to the monitoring point, and the electronic equipment can send an alarm prompt after the real-time operation data exceeds the target alarm threshold value. An alarm limit range exists between the highest alarm limit and the lowest alarm limit, and the electronic equipment can divide the alarm limit range based on the distribution parameters to obtain a plurality of alarm threshold values, wherein the plurality of alarm threshold values are target alarm threshold values generated by the electronic equipment. The alarm limit value range is reasonably divided through the alarm threshold values, accurate alarm is convenient to carry out, and after the target alarm threshold value is determined, the target alarm threshold value can be configured to a corresponding monitoring point by the electronic equipment so as to accurately monitor the operation of the monitoring point.
According to the method for determining the alarm threshold, the historical operation data of the monitoring points are obtained to analyze the operation state of the monitoring points, the distribution parameters of the historical operation data of the monitoring points are determined, and then the alarm threshold value aiming at the monitoring points is generated according to the distribution parameters so as to configure the alarm threshold value to the relevant monitoring points. The alarm threshold value corresponding to the monitoring point is reasonably generated by combining the historical operation data, so that the automatic generation and the automatic configuration of the alarm threshold value are realized, the intelligent configuration of the alarm threshold value is realized, the time and the workload for manually configuring the alarm threshold value are greatly reduced, the phenomena of mismatching, missed configuration and mismatching existing in the manual configuration are avoided to the greatest extent, and the configuration accuracy, the rationality and the effectiveness of the alarm threshold value are further improved.
In this embodiment, a method for determining an alarm threshold is provided, which may be used in an electronic device, such as a mobile phone, a computer, a server, etc., fig. 2 is a flowchart of the method for determining an alarm threshold according to an embodiment of the present application, and as shown in fig. 2, the flowchart includes the following steps:
s21, acquiring historical operation data generated by the monitoring points at each historical moment.
The detailed description refers to the corresponding related descriptions of the above embodiments, and will not be repeated here.
S22, analyzing the historical operation data, and determining the distribution parameters, the highest alarm limit value and the lowest alarm limit value of the historical operation data.
Specifically, the step S22 may include:
s221, analyzing the fluctuation state of the historical operation data and determining the distribution parameters of the historical operation data.
The historical operation data generated by the monitoring points at each historical moment is not constant, and the fluctuation state is the change generated by the historical operation data at each historical moment. According to the fluctuation state, a distribution function of the historical operation data can be fitted, and then, according to the distribution function obtained by fitting, the distribution parameter corresponding to the historical operation data is calculated.
Alternatively, the step S221 may include:
(1) And determining an operation data distribution curve of the monitoring point based on the fluctuation state of the historical operation data.
The operation data distribution curve is a data curve between the historical operation data generated by the monitoring points and the historical moment. The electronic equipment cleans, organizes and counts the historical operation data, and the operation parameter values generated by the monitoring points at each historical moment are sequentially connected according to the time sequence to generate an operation data distribution curve of the monitoring points.
(2) And determining distribution parameters corresponding to the monitoring points based on the characteristics of the operational data distribution curve.
The operation data distribution curve characterizes operation parameter values generated by the monitoring points at all moments, and the characteristics of the operation data distribution curve can be determined through the operation data distribution curve. The electronic equipment can fit a corresponding distribution function based on the characteristic of the distribution curve of the operation data, and then can calculate corresponding distribution parameters according to the distribution function. Specifically, the distribution parameters may include a variation trend, an average value, a mean value, a standard deviation, a control line coefficient, a standard deviation estimation coefficient, and the like. The content of the distribution parameters is not limited herein, and any parameters can be used to characterize the distribution state of the operation data, and those skilled in the art can determine the parameters according to actual requirements.
S222, determining the maximum value and the minimum value of the operation parameters according to the distribution parameters.
The maximum value of the operation parameter is the maximum value of the operation data generated by the monitoring point, and the minimum value of the operation parameter is the minimum value of the operation data generated by the monitoring point. Because the historical operation data is collected at fixed time based on the collection period, the maximum value and the minimum value of the operation parameters may not appear at the collection time, and at this time, the electronic device can determine the maximum value and the minimum value of the operation parameters generated by the monitoring points by combining the distribution function and the distribution parameters.
S223, determining the maximum value of the operation parameter as the highest alarm limit value, and determining the minimum value of the operation parameter as the lowest alarm limit value.
An operation abnormality may occur beyond or below the maximum or minimum operating parameter, and the electronic device may determine the maximum operating parameter as a highest alarm limit and the minimum operating parameter as a lowest alarm limit, thereby facilitating monitoring of abnormal operating conditions that may occur at the monitoring point.
S23, dividing the alarm limit value range corresponding to the highest alarm limit value and the lowest alarm limit value according to the distribution parameters to obtain a target alarm threshold value corresponding to the monitoring point.
The detailed description refers to the corresponding related descriptions of the above embodiments, and will not be repeated here.
According to the method for determining the alarm threshold, provided by the embodiment, the reasonable highest alarm limit value and the reasonable lowest alarm limit value are conveniently determined according to the historical operation data by analyzing the fluctuation state of the historical operation data, so that the automatically generated alarm threshold value is more in accordance with the actual operation state of the monitoring point. The fluctuation state of the historical operation data is analyzed to determine the data distribution curve aiming at the monitoring points, and then the corresponding distribution parameters are determined, so that the distribution parameters are more reasonably determined, and the subsequently generated alarm threshold value is more accurate.
In this embodiment, a method for determining an alarm threshold is provided, which may be used in an electronic device, such as a mobile phone, a computer, a server, etc., fig. 3 is a flowchart of the method for determining an alarm threshold according to an embodiment of the present application, and as shown in fig. 3, the flowchart includes the following steps:
s31, acquiring historical operation data generated by the monitoring points at each historical moment.
Specifically, the step S31 may include:
s311, acquiring a preset sampling range and a preset sampling period.
The preset sampling range is a sampling time range, such as one day, one week (7 days), one month, one year, and the like. The preset sampling period is the duration of each sampling interval, e.g., 10 seconds, 1 minute, 1 hour, etc. The preset sampling range and the preset sampling period are not limited herein, and may be determined by those skilled in the art according to actual requirements.
Specifically, an industrial technician can input a sampling range and a sampling period to the electronic device through an input interface (a keyboard, a mouse, etc.) according to actual needs, and accordingly, the electronic device can respond to input operation of the industrial technician to obtain a preset sampling range and a preset sampling period.
S312, acquiring historical operation data generated by the monitoring points based on a preset sampling period in a preset sampling range.
The electronic equipment generates a sampling instruction according to the received preset sampling range and the preset sampling period, and issues the sampling instruction to the acquisition equipment arranged at the monitoring point, and controls the acquisition equipment to acquire historical operation data generated by the monitoring point in the preset sampling range according to the preset sampling period.
As shown in fig. 4, the electronic device may sample data according to a preset sampling range and a preset sampling period setting. Wherein the subgroup capacity and the subgroup number are input in advance; d2 and D3 represent an upper limit value and a lower limit value of the control line coefficient corresponding to the subgroup capacity and the subgroup number, respectively; d4 represents the standard deviation estimation coefficient corresponding to the subgroup capacity and the subgroup number, and A2 represents the exponent corresponding to the subgroup capacity and the subgroup number.
It should be noted that, D2, D3, D4 and A2 are all determined according to the international specification ISA-18.2, and those skilled in the art can know that the determination process is not specifically described herein.
S32, analyzing the historical operation data, and determining the distribution parameters, the highest alarm limit value and the lowest alarm limit value of the historical operation data.
The detailed description refers to the corresponding related descriptions of the above embodiments, and will not be repeated here.
And S33, dividing the alarm limit value range corresponding to the highest alarm limit value and the lowest alarm limit value according to the distribution parameters to obtain a target alarm threshold value corresponding to the monitoring point.
Specifically, the distribution parameters include variance, control line coefficient, and standard deviation estimation coefficient, and accordingly, the above step S33 may include:
s331, dividing the alarm limit range into a plurality of parts based on the variance, and obtaining a plurality of alarm threshold values.
The electronic device analyzes all the historical operation data in the preset sampling range, and can determine that the fluctuation state of the historical operation data can be presented in a normal distribution rule, as shown in fig. 5. According to the rule of normal distribution, the alarm limit value range can be divided into equal parts according to the variance to cover all data to the greatest extent, and the alarm threshold value corresponding to each equal part is obtained. Specifically, the alarm threshold values can be obtained by dividing the alarm threshold values into 6 equal parts according to-3 sigma, -2 sigma, -1 sigma, 2 sigma and 3 sigma.
S332, determining an upper control threshold value and a lower control threshold value based on the control line coefficient and the standard deviation estimation coefficient.
The upper control threshold value and the lower control threshold value both comprise two control lines, and specifically, the upper control threshold value comprises an upper control threshold maximum value and an upper control threshold minimum value; the lower control threshold value includes a lower control threshold highest value and a lower control threshold lowest value. Representing the average difference by rbar and the variance by xbrbar, the upper control threshold maximum value UCLr and the upper control threshold minimum value UCLx may be expressed as:
UCLr＝D4*rbar；UCLx＝xbarbar+a2*rbar
the lower control threshold highest value LCLr and the lower control threshold lowest value LCLx can be expressed as:
LCLr＝d3*rbar；LCLx＝xbarbar-a2*rbar
s333, determining a plurality of alarm threshold values, an upper control threshold value and a lower control threshold value as target alarm threshold values.
The electronic equipment determines a plurality of calculated alarm threshold values, an upper control threshold value and a lower control threshold value as target alarm threshold values of the monitoring points and deploys the target alarm threshold values to the monitoring points, so that automatic deployment of the alarm threshold values can be realized.
As an optional implementation manner, the distribution parameter may further include an alarm threshold value average difference, and correspondingly, the steps may further include:
s334, performing gear-shifting processing on the target alarm threshold according to the preset percentage of the average difference of the alarm threshold to obtain a target gear corresponding to the target alarm threshold.
The target gear corresponds to different alarm threshold values, i.e. different alarm gear can be set corresponding to different alarm threshold values. Based on the above embodiment, 10 numerical gear positions can be determined, and in order to fit the actual situation of the industrial alarm limit value, the numerical gear positions can be divided into 5 high limit values and 5 low limit values. Specifically, the electronic device may calculate the average difference of the alarm threshold values, and perform a step treatment according to 10%, 20%, 30%, 40%, 50% of the average difference of the alarm threshold values, so as to obtain 10 alarm gears corresponding to ±10%, ±20%, ±30%, ±40%, ±50%.
It should be noted that, considering different practical situations, the method can select to generate high-low report, high-low 2 report, high-low 3 report, high-low 4 report and high-low 5 report, namely 10 limit value alarm modes: high 5, high 4, high 3, high, low 3, low 4, low 5; alternatively, a high newspaper or a low newspaper may be generated. Wherein, the high report represents the alarm gear generated by exceeding the alarm threshold value, and the low report represents the alarm gear generated by being lower than the alarm threshold value.
Different alarm modes can be selected for the alarms of different gears, for example, different color light alarms, different voice alarms and the like, and the different alarm modes are not limited, so long as the alarms of different gears can be distinguished.
By configuring the gears of the target alarm threshold values according to the preset percentages, the automatic configuration of the alarm limit values of different gears is realized, and the workload of manually configuring a plurality of alarm threshold values is reduced to the greatest extent.
As an optional implementation manner, after determining the target alarm threshold value, the method may further include:
s34, detecting whether the real-time operation data of the monitoring point exceeds a target alarm threshold value.
After the target alarm threshold value is deployed to the monitoring point, the electronic equipment receives the real-time operation data detected at the sub-current sampling moment and compares the real-time operation data with the target alarm threshold value to determine whether the real-time operation data of the monitoring point exceeds the target alarm threshold value. When the real-time operation data of the monitoring point does not exceed the target alarm threshold value, the normal operation state of the current monitoring point is indicated, and the real-time operation data of the monitoring point is continuously detected; when the real-time operation data exceeds the target alarm threshold value, step S35 is performed.
And S35, when the real-time operation data exceeds the target alarm threshold value, generating alarm information.
When the real-time operation data exceeds the target alarm threshold value, the monitoring point is indicated to have the possibility of abnormal operation at present, and the electronic equipment can send corresponding alarm information according to the target alarm threshold value where the current real-time operation data is located. The alarm information can be an audible and visual alarm, can be a voice alarm, can be pushed to a mobile terminal of a technician, and can also take other alarm modes as long as the technician can be reminded of timely taking processing measures, and the mode of the alarm information is not limited.
The method for determining the alarm threshold supports setting of the sampling range and the sampling period, so that the collection of historical operation data is more flexible. The alarm limit value ranges are divided to obtain a plurality of alarm threshold values, and meanwhile, the upper control threshold value and the lower control threshold value are determined based on the control line coefficient and the standard deviation estimation coefficient, so that the generation of the plurality of alarm threshold values is realized, and the target alarm threshold value is more in line with the actual industrial alarm service. When the real-time operation data is detected to exceed the target alarm threshold value, alarm information is generated to remind technicians of timely taking relevant measures, and the operation stability of the industrial process is guaranteed to the greatest extent.
The embodiment also provides a device for determining an alarm threshold, which is used for implementing the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The embodiment provides a determining device for an alarm threshold, as shown in fig. 6, including:
and the acquisition module 41 is used for acquiring historical operation data generated by the monitoring points at each historical moment.
The analysis module 42 is configured to analyze the historical operating data and determine a distribution parameter, a highest alarm limit, and a lowest alarm limit of the historical operating data.
The dividing module 43 is configured to divide the alarm limit range corresponding to the highest alarm limit and the lowest alarm limit according to the distribution parameter, so as to obtain a target alarm threshold corresponding to the monitoring point.
Alternatively, the analysis module 42 may include:
the first analysis sub-module is used for analyzing the fluctuation state of the historical operation data and determining the distribution parameters of the historical operation data.
And the first determining submodule is used for determining the maximum value and the minimum value of the operation parameters according to the distribution parameters.
And the second determining sub-module is used for determining the maximum value of the operation parameter as the highest alarm limit value and determining the minimum value of the operation parameter as the lowest alarm limit value.
Optionally, the first analysis submodule is specifically configured to: determining an operation data distribution curve of the monitoring point based on the fluctuation state of the historical operation data; and determining distribution parameters corresponding to the monitoring points based on the characteristics of the operational data distribution curve.
Alternatively, the acquiring module 41 may include:
the first acquisition submodule is used for acquiring a preset sampling range and a preset sampling period.
And the generation sub-module is used for acquiring historical operation data generated by the monitoring points based on a preset sampling period in a preset sampling range.
Optionally, the distribution parameters include variance, control line coefficient, standard deviation estimation coefficient and alarm threshold value average difference, and the dividing module 43 may include:
and the dividing sub-module is used for dividing the alarm limit value range into a plurality of parts based on the variance to obtain a plurality of alarm threshold values.
And the third determining submodule is used for determining an upper control threshold value and a lower control threshold value based on the control line coefficient and the standard deviation estimation coefficient.
And the fourth determining submodule is used for determining a plurality of alarm threshold values, an upper control threshold value and a lower control threshold value as target alarm threshold values.
And the grading sub-module is used for grading the target alarm threshold value according to the preset percentage of the average difference of the alarm threshold value to obtain a target gear corresponding to the target alarm threshold value.
Optionally, the determining device of the alarm threshold may further include:
and the detection module is used for detecting whether the real-time operation data of the monitoring point exceeds a target alarm threshold value.
And the alarm generation module is used for generating alarm information when the real-time operation data exceeds a target alarm threshold value.
The alarm threshold determining means in this embodiment are in the form of functional units, here referred to as ASIC circuits, processors and memories executing one or more software or firmware programs, and/or other devices that can provide the above described functions.
Further functional descriptions of the above modules are the same as those of the above corresponding embodiments, and are not repeated here.
According to the determining device of the alarm threshold, the historical operation data of the monitoring points are obtained to analyze the operation state of the monitoring points, the distribution parameters of the historical operation data of the monitoring points are determined, and then the alarm threshold value aiming at the monitoring points is generated according to the distribution parameters so as to configure the alarm threshold value to the relevant monitoring points. The alarm threshold value corresponding to the monitoring point is reasonably generated by combining the historical operation data, so that the automatic generation and the automatic configuration of the alarm threshold value are realized, the intelligent configuration of the alarm threshold value is realized, the time and the workload for manually configuring the alarm threshold value are greatly reduced, the phenomena of mismatching, missed configuration and mismatching existing in the manual configuration are avoided to the greatest extent, and the configuration accuracy, the rationality and the effectiveness of the alarm threshold value are further improved.
The embodiment of the application also provides electronic equipment, which is provided with the alarm threshold determining device shown in the figure 6.
Referring to fig. 7, fig. 7 is a schematic structural diagram of an electronic device according to an alternative embodiment of the present application, and as shown in fig. 7, the electronic device may include: at least one processor 501, such as a central processing unit (Central Processing Unit, CPU), at least one communication interface 503, a memory 504, at least one communication bus 502. Wherein a communication bus 502 is used to enable connected communications between these components. The communication interface 503 may include a Display screen (Display), a Keyboard (Keyboard), and the optional communication interface 503 may further include a standard wired interface, and a wireless interface. The memory 504 may be a high-speed volatile random access memory (Random Access Memory, RAM) or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 504 may also optionally be at least one storage device located remotely from the aforementioned processor 501. Wherein the processor 501 may have stored in the memory 504 an application program in the apparatus described in connection with fig. 6 and the processor 501 invokes the program code stored in the memory 504 for performing any of the above-mentioned method steps.
The communication bus 502 may be, among other things, a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, etc. The communication bus 502 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 7, but not only one bus or one type of bus.
Wherein the memory 504 may include volatile memory (RAM), such as random-access memory (RAM); the memory may also include a nonvolatile memory (non-volatile memory), such as a flash memory (flash memory), a hard disk (HDD) or a Solid State Drive (SSD); memory 504 may also include a combination of the types of memory described above.
The processor 501 may be a central processing unit (central processing unit, CPU), a network processor (network processor, NP) or a combination of CPU and NP, among others.
The processor 501 may further include a hardware chip, among others. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (programmable logic device, PLD), or a combination thereof. The PLD may be a complex programmable logic device (complex programmable logic device, CPLD), a field-programmable gate array (field-programmable gate array, FPGA), general-purpose array logic (generic array logic, GAL), or any combination thereof.
Optionally, the memory 504 is also used for storing program instructions. The processor 501 may invoke program instructions to implement the method of determining the alarm threshold as shown in the above-described embodiments of the application.
The embodiment of the application also provides a non-transitory computer storage medium, which stores computer executable instructions, and the computer executable instructions can execute the method for determining the alarm threshold in any of the method embodiments. The storage medium may be a magnetic Disk, an optical disc, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present application have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the application, and such modifications and variations fall within the scope of the application as defined by the appended claims.
Claims (8)
1. A method for determining an alarm threshold, comprising:
acquiring historical operation data generated by monitoring points at each historical moment;
analyzing the historical operation data, and determining distribution parameters, the highest alarm limit value and the lowest alarm limit value of the historical operation data;
dividing the alarm limit value range corresponding to the highest alarm limit value and the lowest alarm limit value according to the distribution parameters to obtain a target alarm threshold value corresponding to the monitoring point;
the distribution parameters comprise variances, control line coefficients and standard deviation estimation coefficients, the alarm limit value ranges corresponding to the highest alarm limit value and the lowest alarm limit value are divided according to the distribution parameters, and a target alarm threshold value corresponding to the monitoring point is obtained, and the method comprises the following steps: dividing the alarm limit value range into a plurality of parts based on the variance to obtain a plurality of alarm threshold values; determining an upper control threshold value and a lower control threshold value based on the control line coefficient and the standard deviation estimation coefficient; determining the alarm threshold values, the upper control threshold values and the lower control threshold values as the target alarm threshold values;
the distribution parameters further comprise an alarm threshold value average difference, and the method further comprises: carrying out grading treatment on the target alarm threshold value according to the preset percentage of the average difference of the alarm threshold values to obtain a target gear corresponding to the target alarm threshold value;
the upper control threshold value comprises an upper control threshold highest value and an upper control threshold lowest value; the lower control threshold value comprises a lower control threshold highest value and a lower control threshold lowest value; representing the average difference by rbar and the variance by xbrbar, the upper control threshold maximum value UCLr and the upper control threshold minimum value UCLx may be expressed as:
UCLr＝D4*rbar；UCLx＝xbarbar+a2*rbar
the lower control threshold highest value LCLr and the lower control threshold lowest value LCLx can be expressed as:
LCLr＝d3*rbar；LCLx＝xbarbar-a2*rbar；
d4 represents a standard deviation estimation coefficient corresponding to the subgroup capacity and the subgroup number; d3 represents a lower limit value of the control line coefficient corresponding to the number of subgroups; a2 represents an index corresponding to the subgroup capacity and the subgroup number.
2. The method of claim 1, wherein the analyzing the historical operating data to determine a distribution parameter, a highest alarm limit, and a lowest alarm limit for the historical operating data comprises:
analyzing the fluctuation state of the historical operation data and determining the distribution parameters of the historical operation data;
determining a maximum value and a minimum value of the operation parameters according to the distribution parameters;
and determining the maximum value of the operation parameter as the highest alarm limit value, and determining the minimum value of the operation parameter as the lowest alarm limit value.
3. The method of claim 2, wherein analyzing the fluctuation status of the historical operating data, determining the distribution parameters of the historical operating data, comprises:
determining an operation data distribution curve of the monitoring point based on the fluctuation state of the historical operation data;
and determining distribution parameters corresponding to the monitoring points based on the characteristics of the operation data distribution curve.
4. The method of claim 1, wherein the obtaining historical operating data for the monitoring point comprises:
acquiring a preset sampling range and a preset sampling period;
and collecting the historical operation data generated by the monitoring points based on the preset sampling period in the preset sampling range.
5. The method of any one of claims 1-4, further comprising:
detecting whether the real-time operation data of the monitoring point exceeds the target alarm threshold value;
and generating alarm information when the real-time operation data exceeds the target alarm threshold value.
6. A device for determining an alarm threshold, comprising:
the acquisition module is used for acquiring historical operation data generated by the monitoring points at each historical moment;
the analysis module is used for analyzing the historical operation data and determining distribution parameters, the highest alarm limit value and the lowest alarm limit value of the historical operation data;
the dividing module is used for dividing the alarm limit value range corresponding to the highest alarm limit value and the lowest alarm limit value according to the distribution parameters to obtain a target alarm threshold value corresponding to the monitoring point;
the distribution parameters comprise variance, control line coefficient, standard deviation estimation coefficient and alarm threshold value average difference, and the dividing module comprises: dividing the alarm limit value range into a plurality of parts based on the variance to obtain a plurality of alarm threshold values; a third determining submodule, configured to determine an upper control threshold value and a lower control threshold value based on the control line coefficient and the standard deviation estimation coefficient; a fourth determining submodule, configured to determine the plurality of alarm threshold values, the upper control threshold value, and the lower control threshold value as the target alarm threshold values; the grading sub-module is used for grading the target alarm threshold value according to the preset percentage of the average difference of the alarm threshold value to obtain a target gear corresponding to the target alarm threshold value; the upper control threshold value comprises an upper control threshold highest value and an upper control threshold lowest value; the lower control threshold value comprises a lower control threshold highest value and a lower control threshold lowest value; representing the average difference by rbar and the variance by xbrbar, the upper control threshold maximum value UCLr and the upper control threshold minimum value UCLx may be expressed as:
UCLr＝D4*rbar；UCLx＝xbarbar+a2*rbar
the lower control threshold highest value LCLr and the lower control threshold lowest value LCLx can be expressed as:
LCLr＝d3*rbar；LCLx＝xbarbar-a2*rbar；
d4 represents a standard deviation estimation coefficient corresponding to the subgroup capacity and the subgroup number; d3 represents a lower limit value of the control line coefficient corresponding to the number of subgroups; a2 represents an index corresponding to the subgroup capacity and the subgroup number.
7. An electronic device, comprising:
a memory and a processor, said memory and said processor being communicatively coupled to each other, said memory having stored therein computer instructions, said processor executing said computer instructions to perform the method of determining an alarm threshold of any of claims 1-5.
8. A computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of determining an alarm threshold according to any one of claims 1-5.
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