CN117765702A - Mobile equipment monitoring alarm method, device, equipment and medium - Google Patents
Mobile equipment monitoring alarm method, device, equipment and medium Download PDFInfo
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Abstract
The application provides a method, a device, equipment and a medium for monitoring and alarming mobile equipment, which comprise the following steps: the method comprises the steps that a main service module obtains dynamic equipment data, wherein the dynamic equipment data comprises equipment model parameters, equipment operation data and working condition environment data; the algorithm module synchronously acquires the data of the mobile equipment in real time; the algorithm module inputs the data of the mobile equipment into a preset physical system simulation model and outputs a self-adaptive threshold value and a trend prediction result; the main service module receives the self-adaptive threshold and the trend prediction result sent by the algorithm module, and outputs alarm information according to the self-adaptive threshold and the trend prediction result. Therefore, the whole dynamic equipment monitoring system has a self-adaptive threshold adjusting function, can intelligently adjust the threshold according to equipment characteristics and environmental changes, is beneficial to reducing manual intervention, improves the efficiency and accuracy of data monitoring and alarming, and reduces false alarm conditions of vibration monitoring of dynamic equipment.
Description
Technical Field
The application relates to the technical field of the internet of things, in particular to a method, a device, equipment and a medium for monitoring and alarming of mobile equipment.
Background
Petrochemical industry, electric power industry are important pillar in the industry, and they are especially prominent to the demand of dynamic equipment vibration alarm monitoring. Once an abnormality or a false stop occurs in key equipment in the industries, huge negative effects and economic losses are caused to the production management of enterprises. Thus, the need for state monitoring and predictive maintenance of mobile devices by businesses is becoming increasingly stringent.
Traditional vibration monitoring of dynamic equipment mainly depends on a unified static alarm threshold method, and is applied by combining a specific algorithm in a few cases. However, this method relies mainly on setting alarm rules manually, lacking sufficient flexibility and scalability. Once the alarm rules need to be adjusted or changed, the settings generally need to be reset, and the operation process is relatively cumbersome and not intuitive. Therefore, in actual situations, false alarm situations occur due to improper or too conservative alarm rule settings.
Therefore, how to reduce false alarm conditions of vibration monitoring of a mobile device is a technical problem that needs to be solved by those skilled in the art.
Disclosure of Invention
In view of this, the embodiment of the application provides a method and a device for monitoring and alarming a mobile device, which aim to reduce false alarm conditions of vibration monitoring of the mobile device.
In a first aspect, an embodiment of the present application provides a method for monitoring and alarming a mobile device, including:
the method comprises the steps that a main service module obtains dynamic equipment data, wherein the dynamic equipment data comprises equipment model parameters, equipment operation data and working condition environment data;
the algorithm module synchronously acquires the data of the mobile equipment in real time;
the algorithm module inputs the data of the mobile equipment into a preset physical system simulation model and outputs a self-adaptive threshold value and a trend prediction result;
the main service module receives the self-adaptive threshold and the trend prediction result sent by the algorithm module, and outputs alarm information according to the self-adaptive threshold and the trend prediction result.
Optionally, the main service module acquires mobile device data, including:
the main service module acquires equipment operation data and working condition environment data sent by the collector module;
the main service module determines equipment model parameters, wherein the equipment model parameters comprise an overall equipment model and a branch equipment model;
optionally, after the main service module determines the device model parameters, the method further comprises:
and the main service module establishes an equipment information model according to the whole equipment model and the branch equipment model.
Optionally, the device operational data comprises vibration data; the main service module receives the self-adaptive threshold and the trend prediction result sent by the algorithm module, and outputs alarm information according to the self-adaptive threshold and the trend prediction result, and the method comprises the following steps:
the main service module receives the self-adaptive threshold value and the trend prediction result sent by the algorithm module;
the main service module sets a corresponding threshold value according to the self-adaptive threshold value and the trend prediction result respectively;
and the main service module responds to the vibration data or the historical trend result to be larger than the corresponding threshold value, and outputs alarm information.
Optionally, the alarm information includes an alarm level;
the main service module outputs alarm information in response to the vibration data or the historical trend result being greater than the corresponding threshold value, and the alarm information comprises:
the main service module responds to the vibration data or the historical trend result being larger than the corresponding threshold value, and determines an alarm level according to a preset corresponding relation;
and outputting alarm information.
Optionally, the outputting the alarm information includes:
sending alarm information to a first user terminal;
and responding to the first user side not responding in a preset time period, and sending alarm information to a second user side.
Optionally, the method further comprises:
the main service module outputs a diagnosis map by using a preset analysis map tool and a manual diagnosis case library;
and the main service module responds to the confirmed diagnostic map and sends the confirmed diagnostic map result to an algorithm module so that the algorithm module trains the preset physical system simulation model by utilizing the confirmed diagnostic map result.
In a second aspect, an embodiment of the present application provides a mobile device monitoring alarm apparatus, including:
the system comprises an acquisition module, a main service module and a control module, wherein the acquisition module is used for acquiring dynamic equipment data, and the dynamic equipment data comprises equipment model parameters, equipment operation data and working condition environment data;
the synchronization module is used for synchronously acquiring the data of the mobile equipment in real time by the algorithm module;
the algorithm module is used for inputting the data of the mobile equipment into a preset physical system simulation model and outputting a self-adaptive threshold value and a trend prediction result;
and the alarm module is used for receiving the self-adaptive threshold and the trend prediction result sent by the algorithm module by the main service module and outputting alarm information according to the self-adaptive threshold and the trend prediction result.
In a third aspect, embodiments of the present application provide an apparatus, the apparatus including a memory for storing instructions or code, and a processor for executing the instructions or code to cause the apparatus to perform the dynamic apparatus monitoring alarm method of any one of the preceding first aspects.
In a fourth aspect, embodiments of the present application provide a computer storage medium having code stored therein, where when the code is executed, a device executing the code implements the dynamic device monitoring alarm method of any one of the first aspects.
The embodiment of the application provides a method and a device for monitoring and alarming mobile equipment, wherein when the method is executed, a main service module firstly acquires mobile equipment data, and the mobile equipment data comprises equipment model parameters, equipment operation data and working condition environment data; then, an algorithm module synchronously acquires the data of the mobile equipment in real time;
furthermore, the algorithm module inputs the data of the mobile equipment into a preset physical system simulation model and outputs a self-adaptive threshold value and a trend prediction result; and finally, the main service module receives the self-adaptive threshold and the trend prediction result sent by the algorithm module, and outputs alarm information according to the self-adaptive threshold and the trend prediction result. Therefore, the whole dynamic equipment monitoring system has a self-adaptive threshold adjusting function, can intelligently adjust the threshold according to equipment characteristics and environmental changes, is beneficial to reducing manual intervention, improves the efficiency and accuracy of data monitoring and alarming, and reduces false alarm conditions of vibration monitoring of dynamic equipment.
Drawings
In order to more clearly illustrate the present embodiments or the technical solutions in the prior art, the drawings that are required for the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a monitoring and alarm system for a mobile device according to an embodiment of the present application;
FIG. 2 is a flowchart of a method for monitoring and alarming a mobile device according to an embodiment of the present application;
FIG. 3 is a diagram illustrating an algorithm module of a method for monitoring and alarming a mobile device according to an embodiment of the present application;
fig. 4 is a use case diagram of a main service module alarming step of the mobile device monitoring alarming method according to the embodiment of the present application;
fig. 5 is a multi-level alarm information issuing diagram of a mobile device monitoring alarm method according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a monitoring and alarming device for a mobile device according to an embodiment of the present application.
Detailed Description
In various equipment fields, the vibration alarm technology of the movable equipment has the possibility of wide application, and covers industrial machinery, power equipment, industrial production line equipment, transportation equipment and the like. Among them, petrochemical industry and electric power industry are dominant in the application of dynamic equipment vibration alarm monitoring, market share exceeds 75%. For a manufacturing enterprise, normal operation of key equipment is critical to production management and economic benefits. Therefore, enterprises are urgent to need a system capable of realizing state monitoring and predictive maintenance of equipment, so as to ensure safe production. In addition, the need for predictive diagnostics and abnormal state analysis of devices by businesses is also continually increasing.
Most of the traditional vibration monitoring methods of the dynamic equipment depend on a static alarm threshold method, and a few of the traditional vibration monitoring methods can be applied in combination with a specific algorithm. However, this method mainly relies on setting alarm rules manually, which is not only inflexible but also has limited expandability. Once the alarm rules need to be adjusted, the alarm rules must be reset, and the operation is relatively cumbersome. Therefore, in practical application, false alarm situations frequently occur. In addition, the traditional method lacks real-time analysis on trend and fluctuation change rule of the vibration signal, and is difficult to accurately identify instantaneous vibration fluctuation or potential displacement change trend, so that alarming is not timely.
In addition, other problems exist with existing vibration monitoring systems. For example, effective alarms cannot be accurately identified, and a large number of repeated alarms cannot be effectively filtered. Meanwhile, the alarm notification mode is single, and is mainly realized through short message notification or software internal alarm notification. This may result in a user not being able to pay attention to the critical alarm information in time, and thus not being able to take corresponding processing measures in time. Therefore, in terms of development and application of the vibration alarm technology of the dynamic equipment, further improvement and perfection are still needed.
The method provided by the embodiment of the application is executed by the computer equipment and is used for reducing false alarm conditions of vibration monitoring of the mobile equipment.
The computer device may include a plurality of modules, such as a main service module (main module), an algorithm module (algoritm module), and a Collector module (Collector module). For example, referring to fig. 1, a main service module provides a service main service, provides service aggregation and processing capabilities, provides an equipment model, processes and displays information, and the like. The algorithm module provides an algorithm base, realizes the training capability of the information model, and provides an adaptive and trend prediction algorithm model. The collector module is used for realizing data access of various sensor devices and providing data storage and data analysis computing capacity. The sensor device may be referred to generally as a measurement device for collecting and monitoring the status of a mobile device in an industrial setting.
It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Referring to fig. 2, fig. 2 is a flowchart of a method for monitoring and alarming a mobile device according to an embodiment of the present application, including:
step S201: and the main service module acquires the data of the mobile equipment.
The dynamic equipment data comprises equipment model parameters, equipment operation data, working condition environment data and the like.
The equipment model parameters comprise model parameters of the dynamic equipment and subsection equipment models, and specifically comprise parameter information such as driving equipment, load equipment, transmission equipment, bearing equipment and the like, for example: the model number, the rotating speed, the rotor entry number, the manufacturer and other information of the driving load bearing and the like ensure that the model parameter value is real and effective. The equipment operation data comprises static data, dynamic data, configuration issuing, library and table dividing, vibration data and the like. The operating condition environment data include process operating conditions and the like.
As a possible implementation, the device operation data includes vibration data, and the step S201 includes the following steps S2011 to S2012:
step S2011: the main service module acquires equipment operation data and working condition environment data sent by the collector module.
The collector module acquires dynamic working condition and environment data in real time through application interaction with a distributed control system DCS (Distributed Control System), a ground control system GCS (Ground Control System), a safety instrument system SIS (Safety Instrumented System), a programmable logic controller system PLC (Programmable Logic Controller), an intelligent instrument and other control systems, and cooperates with a vibration sensor to normally collect vibration data, store in a time sequence and display business in the main business module.
Step S2012: the main business module determines device model parameters.
As a possible implementation manner, after step S2011, the main service module builds a device information model according to the whole device model and the branch device model. This process may be accomplished using configuration functions provided in the host service module. The equipment information model is a unit model and is configured by driving, loading, transmission, bearing and other branch equipment models, wherein one equipment model is formed by combining a plurality of branch equipment and is a father-son relationship of a tree structure, and the branch equipment is a brother relationship.
Step S202: the algorithm module synchronously acquires the data of the mobile equipment in real time.
And model parameter synchronization is performed between the main service module and the algorithm module through a preset instant protocol. When the models of the two are changed, the two models are dynamically synchronous with each other, such as: equipment model information parameters, sensor real-time dynamic data, alarm dynamic threshold value data change and the like. The preset instant protocol may be MQTT (Message Queuing Telemetry Transport) protocol, or may be replaced by another transmission protocol, for example: the rabitimq protocol.
Step S203: the algorithm module inputs the data of the mobile equipment into a preset physical system simulation model and outputs a self-adaptive threshold value and a trend prediction result.
Referring to fig. 3, fig. 3 is a diagram of an algorithm module. The algorithm module inputs the dynamic equipment data into a preset physical system simulation model, and the intelligent algorithm autonomously optimizes and adjusts the model through equipment running state and working condition environment data input by the main service module. The predetermined physical system simulation model may be a physical system simulation model based on a digital technique. After the algorithm module finishes evaluation and prediction, a suggested self-adaptive threshold and a trend prediction result are output to the main service module, and the configuration of the alarm threshold is automatically finished.
The algorithm module can adjust the threshold value of the vibration acquisition item according to the equipment characteristics and environmental changes, so that the threshold value self-adaption is realized, and the manual intervention is reduced; and calculating trend through historical data, results and trend analysis algorithm of visual data of the numerical range of the vibration signal, so as to realize the capability of predicting fault alarm.
Step S204: the main business module receives the self-adaptive threshold and the trend prediction result sent by the algorithm module, and outputs alarm information according to the self-adaptive threshold and the trend prediction result.
Referring to fig. 4, fig. 4 is a diagram illustrating an alarm step of a main service module. When the threshold is completed with the self-adaptive threshold configuration, the main service module generates an automatic alarm message after the real-time vibration data and the historical trend result of the sensor exceed the threshold. And accurately judging whether the equipment exceeds a normal threshold value according to the numerical range of the vibration signal and the change rule of the vibration signal under the current running state of the equipment, judging the alarm level and realizing the accurate alarm capability.
The main service module can provide various alarm information output modes, such as mobile phone short message reminding, app internal reminding, audible alarm, alarm lamplight flashing, notification bar notification reminding and the like.
As a possible implementation manner, the step S204 may include the following steps S2041 to S2043:
s2041: the main business module receives the self-adaptive threshold value and the trend prediction result sent by the algorithm module.
S2042: the main business module sets corresponding threshold values according to the self-adaptive threshold values and the trend prediction results respectively.
S2043: and the main service module outputs alarm information in response to the vibration data or the historical trend result being greater than the corresponding threshold value.
As a possible implementation, the alarm information may include an alarm level. Step S204 may include the main service module determining an alarm level according to a preset corresponding relationship in response to the vibration data or the historical trend result being greater than a corresponding threshold value; and then outputting alarm information. Specifically, the preset correspondence may be set according to a threshold level, and the alarm class is classified into: early warning, mid warning and late warning.
As a possible implementation manner, outputting the alarm information may include: firstly, sending alarm information to a first user side; and responding to the fact that the first user side does not respond within a preset time period, and sending alarm information to the second user side. In this way, the reminding can be carried out layer by layer according to the post level. For example, referring to fig. 5, the alert information may be issued step by step as shown in fig. 5.
In addition, the main service module also provides a plurality of analysis map tools of static and dynamic data including vibration acquisition values and a manual diagnosis case library, and is used for assisting in identifying the fault condition of the mobile equipment and the correctness of alarming. And after the alarm is confirmed, closing the alarm flow, and synchronously feeding back an algorithm module, wherein the algorithm module performs input training. Specifically, the main service module firstly utilizes a preset analysis map tool and a manual diagnosis case library to output a diagnosis map; and then, the main service module responds to the confirmed diagnosis map and sends the confirmed result of the diagnosis map to the algorithm module so that the algorithm module trains the preset physical system simulation model by utilizing the confirmed result of the diagnosis map.
In summary, the following technical effects may be achieved in this embodiment:
(1) The alarm rule is not set manually, flexibility and expandability are achieved, resetting is not needed when changing is needed, and false alarm conditions can be reduced.
(2) Real-time analysis of trend and fluctuation change rule of vibration signals can be realized, instantaneous vibration fluctuation or potential displacement change trend can be accurately identified, and timely alarm can be realized.
(3) The method has the advantages that effective alarms are accurately identified, a large number of repeated alarms are accurately filtered, the alarms are accurately identified, and alarm information is prevented from being ignored or cannot be responded and processed in time.
Referring to the schematic structural diagram of the monitoring and alarming device for mobile equipment shown in fig. 6, the device 600 includes an acquisition module 601, a synchronization module 602, an algorithm module 603, and an alarming module 604.
The acquiring module 601 is configured to acquire mobile device data by using a main service module, where the mobile device data includes device model parameters, device operation data, and operating condition environment data;
the synchronization module 602 is configured to synchronize the acquisition of the mobile device data in real time by using an algorithm module;
the algorithm module 603 is configured to input the mobile device data into a preset physical system simulation model, and output an adaptive threshold and a trend prediction result;
and the alarm module 604 is configured to receive the adaptive threshold and the trend prediction result sent by the algorithm module by using the main service module, and output alarm information according to the adaptive threshold and the trend prediction result.
As a possible implementation manner, the obtaining module 601 includes:
the first acquisition unit is used for acquiring equipment operation data and working condition environment data sent by the collector module by the main service module;
the second acquisition unit is used for determining equipment model parameters by the main service module, wherein the equipment model parameters comprise an overall equipment model and a branch equipment model;
as a possible implementation manner, the apparatus 600 further includes:
the modeling module 605 is configured to build an equipment information model according to the overall equipment model and the branch equipment model by using the main service module.
As one possible implementation, the device operational data includes vibration data; the alarm module 604 includes:
the threshold sending unit is used for receiving the self-adaptive threshold and the trend prediction result sent by the algorithm module by the main service module;
the threshold setting unit is used for setting a corresponding threshold value by the main service module according to the self-adaptive threshold value and the trend prediction result respectively;
the first alarm unit is used for responding to the vibration data or the historical trend result by the main service module and outputting alarm information.
As a possible implementation manner, the alarm information includes an alarm level;
the alarm module 604 includes:
the grade confirmation unit is used for determining an alarm grade according to a preset corresponding relation by the main service module in response to the vibration data or the historical trend result being larger than the corresponding threshold value;
and the second alarm unit is used for outputting alarm information.
As one possible implementation, the alarm module 604 includes:
the first-level alarm unit is used for sending alarm information to the first user terminal;
and the secondary alarm unit is used for responding to the fact that the first user side does not respond within a preset time period and sending alarm information to the second user side.
As a possible implementation manner, the apparatus 600 further includes:
the diagnosis unit is used for outputting a diagnosis map by the main service module through a preset analysis map tool and a manual diagnosis case library;
and the feedback unit is used for responding to the confirmation of the diagnostic map by the main service module and sending the confirmation result of the diagnostic map to the algorithm module so that the algorithm module trains the simulation model of the preset physical system by utilizing the confirmation result of the diagnostic map.
The embodiment of the application also provides corresponding equipment and a computer storage medium, which are used for realizing the scheme provided by the embodiment of the application.
The device comprises a memory and a processor, wherein the memory is used for storing instructions or codes, and the processor is used for executing the instructions or codes so that the device can execute the dynamic device monitoring alarm method according to any embodiment of the application.
The computer storage medium stores codes, and when the codes are executed, equipment for executing the codes realizes the monitoring and alarming method of the mobile equipment according to any embodiment of the application.
The "first" and "second" in the names of "first", "second" (where present) and the like in the embodiments of the present application are used for name identification only, and do not represent the first and second in sequence.
From the above description of embodiments, it will be apparent to those skilled in the art that all or part of the steps of the above described example methods may be implemented in software plus general hardware platforms. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a storage medium, such as a read-only memory (ROM)/RAM, a magnetic disk, an optical disk, or the like, including several instructions for causing a computer device (which may be a personal computer, a server, or a network communication device such as a router) to perform the methods described in the embodiments or some parts of the embodiments of the present application.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The foregoing is merely exemplary embodiments of the present application and is not intended to limit the scope of the present application.
Claims (10)
1. A method of monitoring and alerting a mobile device, the method comprising:
the method comprises the steps that a main service module obtains dynamic equipment data, wherein the dynamic equipment data comprises equipment model parameters, equipment operation data and working condition environment data;
the algorithm module synchronously acquires the data of the mobile equipment in real time;
the algorithm module inputs the data of the mobile equipment into a preset physical system simulation model and outputs a self-adaptive threshold value and a trend prediction result;
the main service module receives the self-adaptive threshold and the trend prediction result sent by the algorithm module, and outputs alarm information according to the self-adaptive threshold and the trend prediction result.
2. The method of claim 1, wherein the main service module obtains mobile device data, comprising:
the main service module acquires equipment operation data and working condition environment data sent by the collector module;
the main service module determines equipment model parameters including an overall equipment model and a fractional equipment model.
3. The method of claim 2, wherein after the main business module determines the device model parameters, the method further comprises:
and the main service module establishes an equipment information model according to the whole equipment model and the branch equipment model.
4. The method of claim 1, wherein the equipment operational data comprises vibration data; the main service module receives the self-adaptive threshold and the trend prediction result sent by the algorithm module, and outputs alarm information according to the self-adaptive threshold and the trend prediction result, and the method comprises the following steps:
the main service module receives the self-adaptive threshold value and the trend prediction result sent by the algorithm module;
the main service module sets a corresponding threshold value according to the self-adaptive threshold value and the trend prediction result respectively;
and the main service module responds to the vibration data or the historical trend result to be larger than the corresponding threshold value, and outputs alarm information.
5. The method of claim 4, wherein the alert information comprises an alert level;
the main service module outputs alarm information in response to the vibration data or the historical trend result being greater than the corresponding threshold value, and the alarm information comprises:
the main service module responds to the vibration data or the historical trend result being larger than the corresponding threshold value, and determines an alarm level according to a preset corresponding relation;
and outputting alarm information.
6. The method of claim 1, wherein outputting the alarm information comprises:
sending alarm information to a first user terminal;
and responding to the first user side not responding in a preset time period, and sending alarm information to a second user side.
7. A method according to claim 3, characterized in that the method further comprises:
the main service module outputs a diagnosis map by using a preset analysis map tool and a manual diagnosis case library;
and the main service module responds to the confirmed diagnostic map and sends the confirmed diagnostic map result to an algorithm module so that the algorithm module trains the preset physical system simulation model by utilizing the confirmed diagnostic map result.
8. A mobile device monitoring alarm apparatus, the apparatus comprising:
the system comprises an acquisition module, a main service module and a control module, wherein the acquisition module is used for acquiring dynamic equipment data, and the dynamic equipment data comprises equipment model parameters, equipment operation data and working condition environment data;
the synchronization module is used for synchronously acquiring the data of the mobile equipment in real time by the algorithm module;
the algorithm module is used for inputting the data of the mobile equipment into a preset physical system simulation model and outputting a self-adaptive threshold value and a trend prediction result;
and the alarm module is used for receiving the self-adaptive threshold and the trend prediction result sent by the algorithm module by the main service module and outputting alarm information according to the self-adaptive threshold and the trend prediction result.
9. An apparatus comprising a memory for storing instructions or code and a processor for executing the instructions or code to cause the apparatus to perform the dynamic apparatus monitoring alarm method of any one of claims 1 to 7.
10. A computer storage medium having code stored therein, which when executed, causes a computer storage device executing the code to implement the dynamic device monitoring alarm method of any of claims 1 to 7.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202311854215.5A CN117765702A (en) | 2023-12-28 | 2023-12-28 | Mobile equipment monitoring alarm method, device, equipment and medium |
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| CN202311854215.5A CN117765702A (en) | 2023-12-28 | 2023-12-28 | Mobile equipment monitoring alarm method, device, equipment and medium |
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