Method and device for determining fault between equipment, equipment and storage medium
By using data acquisition equipment, target detection models and trend prediction models in bank outlets, we automatically detect abnormal events and predict failures, and solve the problem that inter-device failure determination depends on manual inspection, improving the degree of automation and fault determination efficiency.
Patent Information
- Application Number
- CN202411464336.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-18
- Publication Date
- 2025-02-11
AI Technical Summary
Determination of faults between bank outlets and equipment depends on manual inspection, which is inefficient and difficult to detect faults and safety hazards in a timely manner.
By obtaining the data acquisition equipment data between devices, inputting the target detection model for abnormal event detection, and inputting the trend prediction model to determine the standard interval of the data, comparing, and automatically determining the fault information.
It improves the degree of automation between equipment, realizes automatic determination of faults, reduces the need for manual inspection, improves the efficiency of fault determination, and ensures the safety of equipment.
Smart Images
Figure CN119417450A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data processing technology, and in particular to a method, apparatus, device and storage medium for determining faults between devices. Background Art
[0002] The equipment room of a bank branch is a physical space used to place uninterruptible power supplies (UPS), switches, servers and other electronic equipment. The equipment in the equipment room is crucial to ensure the normal operation of banking business.
[0003] At present, when there is an abnormality between devices in a bank branch, a full-time staff is usually required to go to the site to troubleshoot and report the fault. This highly manual fault determination method has the problem of low fault determination efficiency. Summary of the invention
[0004] Based on the above problems, the present application provides a method, apparatus, device and storage medium for determining faults between devices.
[0005] The embodiments of the present application disclose the following technical solutions:
[0006] In the first aspect, the present application provides a method for determining a fault between devices, including:
[0007] Acquire data collected by data collection devices between devices;
[0008] Input the data into a target detection model to detect whether an abnormal event occurs between devices and obtain an abnormal event detection result; input the data into a trend prediction model to determine a standard range of the data;
[0009] Comparing the value of the data with the standard interval of the data to obtain a comparison result;
[0010] Based on the abnormal event detection result and the comparison result, fault information between devices is determined.
[0011] In a possible implementation, inputting the data into a trend prediction model to determine a standard range of the data includes:
[0012] Inputting the data into a trend prediction model to generate a dynamic baseline of the data;
[0013] Based on the dynamic baseline of the data, a standard interval of the data is determined.
[0014] In a possible implementation, inputting the data into a trend prediction model to determine a standard range of the data includes:
[0015] The external environment information of the region where the equipment room is located and the data are input into a trend prediction model to determine a standard range of the data.
[0016] In a possible implementation, the determining the fault information between devices based on the abnormal event detection result and the comparison result includes:
[0017] When the comparison result is that the value of the data is outside the standard range of the data, an alarm event is generated;
[0018] Based on the abnormal event detection result and the alarm event, fault information between devices is determined.
[0019] In a possible implementation manner, after determining the fault information between devices based on the abnormal event detection result and the alarm event, the method further includes:
[0020] Based on the type of the alarm event, the frequency of occurrence of the alarm event, the fault response time, and the abnormal event detection result, the equipment room is evaluated to obtain the evaluation result of the equipment room.
[0021] In a possible implementation manner, after determining the fault information between devices based on the abnormal event detection result and the comparison result, the method further includes:
[0022] Performing visualization processing on the fault information to obtain the visualized fault information;
[0023] The visualized fault information is displayed on a display device.
[0024] In a possible implementation manner, after determining the fault information between devices based on the abnormal event detection result and the comparison result, the method further includes:
[0025] Determine, according to the fault information, a processing strategy corresponding to the fault information;
[0026] Based on the processing strategy, corresponding devices among the devices are controlled to perform fault processing.
[0027] A second aspect: The embodiment of the present application provides a device for determining a fault between devices, including:
[0028] an acquisition unit, an input unit, a comparison unit, and a determination unit;
[0029] The acquisition unit is used to acquire data collected by the data acquisition device between devices;
[0030] The input unit is used to input the data into a target detection model to detect whether an abnormal event occurs between devices and obtain an abnormal event detection result; input the data into a trend prediction model to determine a standard interval of the data;
[0031] The comparison unit is used to compare the value of the data with the standard interval of the data to obtain a comparison result;
[0032] The determining unit is used to determine the fault information between devices based on the abnormal event detection result and the comparison result.
[0033] In a possible implementation, the input unit is specifically used to:
[0034] Inputting the data into a trend prediction model to generate a dynamic baseline of the data;
[0035] Based on the dynamic baseline of the data, a standard interval of the data is determined.
[0036] In a possible implementation, the input unit is specifically used to:
[0037] The external environment information of the region where the equipment room is located and the data are input into a trend prediction model to determine a standard range of the data.
[0038] In a possible implementation manner, the determining unit is specifically configured to:
[0039] When the comparison result is that the value of the data is outside the standard range of the data, an alarm event is generated;
[0040] Based on the abnormal event detection result and the alarm event, fault information between devices is determined.
[0041] In a possible implementation, the device further includes: an evaluation unit;
[0042] The evaluation unit is used to evaluate the equipment room based on the type of the alarm event, the frequency of occurrence of the alarm event, the fault response time, and the abnormal event detection result to obtain the evaluation result of the equipment room.
[0043] In a possible implementation, the device further includes: a visualization unit;
[0044] The visualization unit is used to perform visualization processing on the fault information to obtain the visualized fault information; and display the visualized fault information on a display device.
[0045] In a possible implementation, the device further includes: a control unit;
[0046] The control unit is used to determine a processing strategy corresponding to the fault information according to the fault information; and based on the processing strategy, control corresponding devices between the devices to perform fault processing.
[0047] A third aspect: An embodiment of the present application provides an electronic device, the electronic device comprising: a processor and a memory;
[0048] The memory is used to store program code and transmit the program code to the processor;
[0049] The processor is used to execute the steps of the above-mentioned method for determining a fault between devices according to the instructions in the program code.
[0050] Aspect 4: An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of a method for determining a fault between devices as described above are implemented.
[0051] Compared with the prior art, this application has the following beneficial effects:
[0052] The embodiments of the present application provide a method, device, equipment and storage medium for determining faults between devices. By acquiring data collected by data acquisition equipment between devices; inputting the data into a target detection model, it is possible to detect in real time whether an abnormal event occurs between devices to obtain abnormal event detection results; inputting the data into a trend prediction model, it is possible to predict possible faults between devices and determine the standard range of the data. On this basis, the value of the data is compared with the standard range of the data to obtain a comparison result. Based on the abnormal event detection result and the comparison result, the fault information between devices is determined. The method provided by the embodiments of the present application improves the degree of automation between devices, and can rely on electronic equipment to realize automatic determination of faults between devices, without the need for manual inspections to ensure the safety of the devices, and effectively improves the efficiency of fault determination. BRIEF DESCRIPTION OF THE DRAWINGS
[0053] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.
[0054] Figure 1 A flowchart of a method for determining a fault between devices provided in an embodiment of the present application;
[0055] Figure 2 A visual process diagram provided for an embodiment of the present application;
[0056] Figure 3 A schematic diagram of the structure of a device for determining a fault between devices is provided for an embodiment of the present application;
[0057] Figure 4 An example diagram of a software structure provided for an embodiment of the present application. DETAILED DESCRIPTION
[0058] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0059] As mentioned above, currently when there are abnormalities between devices at bank branches, dedicated personnel are usually required to go to the site to troubleshoot and report the problem.
[0060] With the rapid development of banking business, the management of bank branch equipment rooms is also facing greater challenges. First, although there are many bank branches, there are few full-time staff in the equipment rooms; second, bank branches are widely distributed. For bank branches in remote areas, it takes a lot of human resources and time costs for full-time staff to conduct on-site inspections and troubleshooting; third, affected by external factors such as climate and geographical location, as well as objective factors such as improper maintenance, equipment rooms may experience high temperature, high humidity, water leakage, etc., which may easily lead to equipment failures in the equipment rooms; fourth, if the compliance awareness of bank branch staff is weak, non-compliant behaviors may be caused by human factors, which will in turn bury hidden dangers to the safety of the equipment rooms.
[0061] The current method of having full-time personnel go on-site to troubleshoot and report faults is highly dependent on manual labor. Given the large number and wide distribution of bank outlets and the small number of full-time personnel, it is difficult to promptly discover equipment failures in the equipment room and potential safety hazards in the equipment room, resulting in low efficiency in fault determination.
[0062] Based on this, an embodiment of the present application provides a method for determining faults between devices, by acquiring data collected by a data acquisition device between devices; inputting the data into a target detection model, it is possible to detect in real time whether an abnormal event occurs between devices to obtain abnormal event detection results; inputting the data into a trend prediction model, it is possible to predict possible faults between devices and determine the standard range of the data. On this basis, the value of the data is compared with the standard range of the data to obtain a comparison result. Based on the abnormal event detection result and the comparison result, the fault information between devices is determined. The method provided by the embodiment of the present application improves the degree of automation between devices, and can rely on electronic equipment to realize automatic determination of faults between devices, without the need for full-time personnel to go to the site to troubleshoot and report faults, effectively improving the efficiency of fault determination and ensuring the safety of the equipment.
[0063] Combine the following Figure 1 The method for determining a fault between devices provided in an embodiment of the present application is introduced. The figure is a flow chart of a method for determining a fault between devices provided in an embodiment of the present application, including S101-S104.
[0064] S101. Acquire data collected by a data collection device between devices.
[0065] In the embodiment of the present application, the data collection equipment between devices may include but is not limited to cameras, temperature sensors, humidity sensors, and device performance collectors between devices.
[0066] Based on the Internet of Things, we can obtain in real time the scene images between devices collected by the cameras between devices, the temperature between devices collected in real time by the temperature sensor, the humidity between devices collected in real time by the humidity sensor, and the operating status of the corresponding devices collected in real time by the device performance collector.
[0067] S102, input the data into a target detection model to detect whether an abnormal event occurs between devices and obtain an abnormal event detection result; input the data into a trend prediction model to determine a standard range of the data.
[0068] In an embodiment of the present application, the target detection model can be used to detect whether abnormal events occur between devices, such as whether there is accumulation of debris, water leakage, illegal entry and exit, etc.
[0069] The target detection model can be obtained by training a large amount of detection videos between devices as a data set. The large amount of detection videos can be obtained by collecting scene images between devices by cameras between devices.
[0070] In one example, after obtaining a large amount of detection videos, the scene images in the large amount of detection videos can be annotated to obtain an annotated data set. For example, a scene image with debris accumulation is annotated as debris accumulation; a scene image with water leakage is annotated as water leakage; and a scene image with only one person entering the equipment room is annotated as illegal entry and exit when a single person is not allowed to enter the equipment room.
[0071] The target detection model can be obtained by training the model based on the labeled data set. The data collected by the data acquisition device is input into the target detection model. When there is accumulation of debris in the equipment room, the abnormal event detection result can be output as the existence of debris accumulation; when there is a water leakage in the equipment room, the abnormal event detection result can be output as water leakage; when only one person is detected in the equipment room, the abnormal event detection result can be output as illegal entry and exit; when no functional abnormality occurs in the detection equipment room, the abnormal event detection result can be output as normal.
[0072] It is understandable that the types of abnormal events in the embodiments of the present application are not specifically limited, and the above are only examples.
[0073] The trend prediction model can be trained based on data collected by data collection devices between devices, and is used to predict possible future failures between devices based on the collected data.
[0074] In a possible implementation, a dynamic baseline of the data may be generated by inputting the data into a trend prediction model; and a standard interval of the data may be determined based on the dynamic baseline of the data.
[0075] A dynamic baseline is a baseline whose value is dynamically adjusted as time or other variables change. A baseline is usually a reference standard or expected value that is used to compare actual data between devices to evaluate data between devices, device performance, or status.
[0076] In the embodiment of the present application, a dynamically adjusted baseline can be generated through real-time collected data, and the standard interval of the data can be dynamically adjusted based on the dynamically adjusted baseline, so as to facilitate timely alarms in the event of a failure or a potential safety hazard. In one example, the threshold of the data can be dynamically adjusted based on the dynamically adjusted baseline, and the threshold of the data determines the standard interval of the data, and the standard interval of the data is the normal value range of the data.
[0077] Since the device status between devices is affected by the external environmental conditions of the region where they are located, in one possible implementation, in order to improve the accuracy of the determined standard range of data, the external environmental information of the region where the devices are located and the data can be input into a trend prediction model to determine the standard range of the data.
[0078] The external environment information of the region may include but is not limited to the local climate, air pressure, etc. For example, for equipment rooms in areas with high humidity, the equipment may be susceptible to failure due to the influence of humidity. Compared with equipment rooms in areas with low humidity, the humidity threshold of some data related to humidity in equipment rooms in areas with high humidity may be lower.
[0079] S103: Compare the data value with the standard range of the data to obtain a comparison result.
[0080] Exemplarily, by comparing the temperature of the equipment room with the temperature standard range, it can be determined whether the current temperature of the equipment room exceeds the temperature standard range; by comparing the humidity of the equipment room with the humidity standard range, it can be determined whether the current humidity of the equipment room exceeds the humidity standard range.
[0081] S104: Determine fault information between devices based on the abnormal event detection result and the comparison result.
[0082] In a possible implementation, when the comparison result is that the value of the data is outside the standard range of the data, an alarm event may be generated. On this basis, based on the abnormal event detection result and the alarm event, the fault information between the devices is determined.
[0083] In the embodiment of the present application, based on the abnormal event detection result and the comparison result, the correlation relationship between all events in the same time period can be determined, the influence of multiple interference factors can be filtered out, and the fault information between devices can be determined.
[0084] For example, in the event of a sudden power outage between devices, the UPS will begin to discharge, and the devices powered by the UPS can operate normally, while the devices not powered by the UPS will stop operating, such as the air conditioner, and the IoT connection will be interrupted.
[0085] When UPS starts to discharge, the UPS power supply data may be outside the standard range, triggering a UPS power supply alarm; and the UPS power may be outside the standard range of the UPS power, that is, the UPS power is lower than the UPS power threshold, triggering a UPS power alarm. Since the air conditioner stops running, the temperature may be outside the standard range, that is, the temperature exceeds the temperature threshold, triggering a temperature alarm; due to the interruption of the IoT connection, the air conditioner offline alarm will be triggered.
[0086] Based on a comprehensive analysis of these alarm events caused by a series of chain reactions and the abnormal event detection results, it can be determined that the fault information between the devices is a sudden city power interruption between the devices.
[0087] In one possible implementation, after determining the fault information between devices based on the abnormal event detection result and the alarm event, the devices can also be evaluated based on the type of the alarm event, the frequency of occurrence of the alarm event, the fault response time, and the abnormal event detection result to obtain the evaluation result of the devices.
[0088] The evaluation result may be a score or an evaluation grade.
[0089] In one example, based on the evaluation results between the various devices, the evaluation results between the devices at various bank branches may be determined.
[0090] Taking the evaluation results as an example, each bank branch includes multiple equipment rooms, and each equipment room can be evaluated to obtain a score for each equipment room, and the average of the scores for each equipment room is used as the score for the equipment room of the bank branch.
[0091] In another example, based on the evaluation results between the devices of each bank outlet, the evaluation results between the devices of the corresponding branch can be determined.
[0092] Exemplarily, each branch includes multiple bank outlets, and each bank outlet includes multiple equipment rooms. Based on the scores of each equipment room under each bank outlet, the scores of the equipment rooms of each bank outlet can be determined. On this basis, the average of the scores of the equipment rooms of each bank outlet can be used as the score of the equipment rooms of the branch.
[0093] In the embodiments of the present application, a multi-level evaluation system can be established starting from the levels of a single equipment room, a bank outlet, a branch, etc., to evaluate the management level of the equipment room and the compliance awareness of personnel at each level to ensure the normal operation of the equipment room.
[0094] In a possible implementation, after determining the fault information between devices based on the abnormal event detection result and the comparison result, the fault information can also be visualized to obtain visualized fault information; and the visualized fault information is displayed on a display device.
[0095] Exemplarily, the visualized fault information may include, but is not limited to, the device where the fault occurs, the location of the device, the fault type, a handling strategy, etc.
[0096] In addition, to facilitate the maintenance of equipment rooms by staff, the display device can display the data collected by the collection device in real time, the evaluation results of the equipment room, etc. Among them, the evaluation results of the equipment room can be displayed in units of equipment rooms, bank outlets, branches, or multiple levels at the same time.
[0097] like Figure 2 As shown, this figure is a visual process diagram provided by an embodiment of the present application. In the embodiment of the present application, a scientific evaluation model can be established. The scientific evaluation model can evaluate the equipment room according to the data collected by the equipment in the equipment room, the frequency of occurrence of alarm events, the fault response time, and the intelligent analysis results, and establish a multi-level evaluation system. Among them, the intelligent analysis results may include but are not limited to abnormal event detection results, determined fault information, etc.
[0098] A visualization model is established to display the real-time scene images, various indicators, and related information of alarm events between devices based on a multi-level evaluation system and data collected by acquisition equipment, so as to assist staff in analyzing faults and improving decision-making efficiency.
[0099] In a possible implementation, after determining the fault information between the devices based on the abnormal event detection result and the comparison result, a processing strategy corresponding to the fault information can also be determined based on the fault information; based on the processing strategy, the corresponding devices between the devices are controlled to perform fault processing.
[0100] For example, based on the abnormal event detection result and the comparison result, after determining that the fault information of the equipment room is that the temperature of the equipment room is too high, the refrigeration equipment in the equipment room can be controlled, such as adjusting the air conditioning temperature, to reduce the temperature of the equipment room.
[0101] In summary, the method provided in the embodiment of the present application improves the degree of automation between devices, and can rely on electronic equipment to automatically determine faults between devices, without the need for dedicated personnel to go to the site to troubleshoot and report faults, effectively improving the efficiency of fault determination and ensuring the safety of the equipment.
[0102] At the same time, through intelligent control, countermeasures can be automatically taken, which greatly reduces the troubleshooting time and effectively reduces the operational risk. By evaluating the equipment room, a quantitative assessment of the management level of the equipment room can be achieved, providing a strong basis for the assessment of the superior unit, giving full play to the baton role of the assessment, and promoting the improvement of management level and compliance awareness. The method provided in the embodiment of the present application can reuse the existing Internet of Things and collection equipment in the equipment room of the bank branch, which can reduce the carbon emissions caused by the inspection and the power consumption of the equipment room while reducing the investment cost.
[0103] The present application provides a device for determining a fault between devices, such as Figure 3 As shown, the figure is a structural diagram of an inter-device fault determination device provided in an embodiment of the present application, and its specific implementation method is consistent with the implementation method and the technical effect achieved in the embodiment of the above method, and some contents will not be repeated here.
[0104] An inter-device fault determination apparatus 1100 provided in an embodiment of the present application includes:
[0105] An acquisition unit 1101, an input unit 1102, a comparison unit 1103 and a determination unit 1104;
[0106] The acquisition unit 1101 is used to acquire data collected by a data collection device between devices;
[0107] The input unit 1102 is used to input the data into a target detection model to detect whether an abnormal event occurs between devices and obtain an abnormal event detection result; input the data into a trend prediction model to determine a standard interval of the data;
[0108] The comparison unit 1103 is used to compare the value of the data with the standard interval of the data to obtain a comparison result;
[0109] The determining unit 1104 is used to determine fault information between devices based on the abnormal event detection result and the comparison result.
[0110] In a possible implementation, the input unit is specifically used to:
[0111] Inputting the data into a trend prediction model to generate a dynamic baseline of the data;
[0112] Based on the dynamic baseline of the data, a standard interval of the data is determined.
[0113] In a possible implementation, the input unit is specifically used to:
[0114] The external environment information of the region where the equipment room is located and the data are input into a trend prediction model to determine a standard range of the data.
[0115] In a possible implementation manner, the determining unit is specifically configured to:
[0116] When the comparison result is that the value of the data is outside the standard range of the data, an alarm event is generated;
[0117] Based on the abnormal event detection result and the alarm event, fault information between devices is determined.
[0118] In a possible implementation, the device further includes: an evaluation unit;
[0119] The evaluation unit is used to evaluate the equipment room based on the type of the alarm event, the frequency of occurrence of the alarm event, the fault response time, and the abnormal event detection result to obtain the evaluation result of the equipment room.
[0120] In a possible implementation, the device further includes: a visualization unit;
[0121] The visualization unit is used to perform visualization processing on the fault information to obtain the visualized fault information; and display the visualized fault information on a display device.
[0122] In a possible implementation, the device further includes: a control unit;
[0123] The control unit is used to determine a processing strategy corresponding to the fault information according to the fault information; and based on the processing strategy, control corresponding devices between the devices to perform fault processing.
[0124] To sum up, the device provided in the embodiment of the present application improves the degree of automation between devices, and can rely on electronic equipment to automatically determine faults between devices, without the need for dedicated personnel to go to the site to troubleshoot and report faults, effectively improving the efficiency of fault determination and ensuring the safety of the equipment.
[0125] At the same time, through intelligent control, countermeasures can be automatically taken, which greatly reduces the troubleshooting time and effectively reduces the operational risk. By evaluating the equipment room, a quantitative assessment of the management level of the equipment room can be achieved, providing a strong basis for the assessment of the superior unit, giving full play to the baton role of the assessment, and promoting the improvement of management level and compliance awareness. The method provided in the embodiment of the present application can reuse the existing Internet of Things and collection equipment in the equipment room of the bank branch, which can reduce the carbon emissions caused by the inspection and the power consumption of the equipment room while reducing the investment cost.
[0126] Figure 4 This is an example diagram of a software structure provided in an embodiment of the present application.
[0127] The layered architecture divides the software into several layers, each with clear roles and division of labor. The layers communicate with each other through software interfaces. In some embodiments, the system is divided into five layers, from top to bottom: application display layer, function layer, service layer, data layer, and resource layer.
[0128] The resource layer includes cameras, temperature sensors, humidity sensors, device performance collectors, and the Internet of Things, etc. Among them, the Internet of Things can be used for network connection; the camera can be used to collect scene images between devices in real time; the temperature sensor can be used to collect the temperature between devices in real time; the humidity sensor can be used to collect the humidity between devices in real time; the device performance collector can be used to collect the operating status of the corresponding device in real time.
[0129] The data layer includes a relational database management system (MYSQL) and an open source, highly scalable distributed full-text search engine (ElasticSearch).
[0130] The service layer includes a target detection model, a trend prediction model and a fault tracing model. The target detection model and the trend prediction model can be used to execute the above S102; the fault tracing model can be used to execute the above S103-S104.
[0131] The functional layer includes alarm module, intelligent control module and intelligent evaluation module.
[0132] Among them, the alarm module can be used to issue alarms based on alarm events. In one example, the corresponding alarm thresholds can be customized according to different situations in different regions and different needs of different users. The alarm module can issue alarms according to corresponding rules to achieve real-time alarms and customized alarms.
[0133] The intelligent control module can be used to control the automatic shutdown of equipment, automatic turning on and off of air conditioners, automatic control of the wind direction of air conditioners, and accelerate cooling in high-temperature areas. By installing access control devices, the intelligent control module can also be used to prohibit unauthorized items and personnel from entering the equipment room, thereby effectively reducing the illegal accumulation of debris and illegal entry and exit in the equipment room.
[0134] The intelligent evaluation module can be used to evaluate the equipment and obtain evaluation results.
[0135] The display layer includes a visualization model. In an embodiment of the present application, the visualization model can be established based on at least one of digital twin technology, hypertext markup language (HTML), and Javascript. The visualization model is used to visualize the fault information to obtain the visualized fault information; and display the visualized fault information on a display device.
[0136] An embodiment of the present application provides an electronic device, comprising: a processor and a memory; the memory is used to store program code and transmit the program code to the processor; the processor is used to execute the steps of a method for determining a fault between devices as described above according to instructions in the program code.
[0137] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for determining a fault between devices as described above are implemented.
[0138] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
Claims
1. A method for determining a fault between devices, characterized in that: include: Acquire data collected by data collection devices between devices; Input the data into a target detection model to detect whether an abnormal event occurs between devices and obtain an abnormal event detection result; input the data into a trend prediction model to determine a standard range of the data; Comparing the value of the data with the standard interval of the data to obtain a comparison result; Based on the abnormal event detection result and the comparison result, fault information between devices is determined.
2. The method according to claim 1, characterized in that The step of inputting the data into a trend prediction model and determining a standard range of the data includes: Inputting the data into a trend prediction model to generate a dynamic baseline of the data; Based on the dynamic baseline of the data, a standard interval of the data is determined.
3. The method according to claim 1, characterized in that The step of inputting the data into a trend prediction model and determining a standard range of the data includes: The external environment information of the region where the equipment room is located and the data are input into a trend prediction model to determine a standard range of the data.
4. The method according to claim 1, characterized in that: The determining the fault information between devices based on the abnormal event detection result and the comparison result includes: When the comparison result is that the value of the data is outside the standard range of the data, an alarm event is generated; Based on the abnormal event detection result and the alarm event, fault information between devices is determined.
5. The method according to claim 4, characterized in that After determining the fault information between devices based on the abnormal event detection result and the alarm event, the method further includes: Based on the type of the alarm event, the frequency of occurrence of the alarm event, the fault response time, and the abnormal event detection result, the equipment room is evaluated to obtain the evaluation result of the equipment room.
6. The method according to any one of claims 1 to 5, characterized in that: After determining the fault information between devices based on the abnormal event detection result and the comparison result, the method further includes: Performing visualization processing on the fault information to obtain the visualized fault information; The visualized fault information is displayed on a display device.
7. The method according to any one of claims 1 to 5, characterized in that: After determining the fault information between devices based on the abnormal event detection result and the comparison result, the method further includes: Determine, according to the fault information, a processing strategy corresponding to the fault information; Based on the processing strategy, corresponding devices among the devices are controlled to perform fault processing.
8. A device for determining a fault between devices, characterized in that: include: an acquisition unit, an input unit, a comparison unit, and a determination unit; The acquisition unit is used to acquire data collected by the data acquisition device between devices; The input unit is used to input the data into a target detection model to detect whether an abnormal event occurs between devices and obtain an abnormal event detection result; input the data into a trend prediction model to determine a standard interval of the data; The comparison unit is used to compare the value of the data with the standard interval of the data to obtain a comparison result; The determining unit is used to determine the fault information between devices based on the abnormal event detection result and the comparison result.
9. An electronic device, characterized in that: The electronic device comprises: a processor and a memory; The memory is used to store program codes and transmit the program codes to the processor; The processor is used to execute the steps of a method for determining a fault between devices as described in any one of claims 1 to 7 according to the instructions in the program code.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for determining a fault between devices according to any one of claims 1 to 7 are implemented.