Power supply equipment monitoring system and monitoring method based on embedded computer

Abstract

The application relates to the fields of big data and intelligent monitoring, in particular to a power supply equipment monitoring system and method based on an embedded computer. The application comprises an abnormal power supply condition analysis module, a weight planning module and an abnormal condition prediction module. The application plans point difference threshold values through the abnormal power supply condition analysis module, calculates the weights corresponding to each abnormal reason according to the difference data through the weight planning module, generates an abnormal reason weight database, the difference value is proportional to the corresponding weight, and finally the abnormal condition prediction module combines the abnormal reason weight database, analyzes the point instantaneous current difference between the current fluctuation image information monitored currently and the current fluctuation image under the normal state, calculates and predicts the abnormal reason according to the weight, reduces the system operation steps, improves the abnormal reason analysis efficiency, plans the abnormal reason direction in advance for the maintenance personnel, and avoids invalid process inspection.

Description

Technical Field

[0001] This invention relates to the fields of big data and intelligent monitoring technology, and more specifically, to a power supply equipment monitoring system and method based on embedded computers. Background Technology

[0002] In layman's terms, an embedded computer is a dedicated computer designed for a specific application, such as networking, communication, audio, video, or industrial control. From an academic perspective, an embedded system is an application-centric, computer technology-based, and customizable hardware and software system. It is suitable for application systems with strict requirements on functionality, reliability, cost, size, and power consumption. It generally consists of four parts: an embedded microprocessor, peripheral hardware devices, an embedded operating system, and user applications.

[0003] From a hardware perspective, peripheral devices based on the CPU are integrated into the CPU chip. The CPU only has the functions of an arithmetic unit and an accumulator, and all other chip functions need to be expanded and implemented through external bridges.

[0004] From a software perspective, this involves selecting the application components and compiling them into a customized operating system kernel before downloading the kernel to the ROM. The application components selected during the customization of the operating system kernel constitute the "embedding" of the software.

[0005] During operation, embedded computers need to connect to multiple hardware devices and run multiple software programs simultaneously, which increases the requirements for their power supply equipment. In order to ensure their normal operation, it is necessary to monitor the transmission current in real time.

[0006] Most existing monitoring methods use current sensors to detect the current in the power supply circuits of embedded computers. However, since embedded computers experience current fluctuations during normal operation, it is impossible to effectively avoid analyzing the abnormal causes of normal differences, resulting in a large amount of redundant monitoring data.

[0007] To address the aforementioned issues, there is an urgent need for a power supply equipment monitoring system and method based on embedded computers. Summary of the Invention

[0008] The purpose of this invention is to provide a power supply equipment monitoring system and method based on an embedded computer to solve the problems mentioned in the background art.

[0009] To achieve the above objectives, one of the objectives of this invention is to provide a power supply equipment monitoring system based on an embedded computer, including a power supply data acquisition module, a database storage module, a data comparison module, an abnormal power supply situation analysis module, a weight planning module, and an abnormal situation prediction module.

[0010] The power supply data acquisition module is used to record the instantaneous current magnitude at each point of the power supply equipment of the embedded computer, and to simulate current fluctuation image information in conjunction with the microcontroller.

[0011] The output end of the power supply data acquisition module is connected to the input end of the database storage module. The database storage module is used to store current fluctuation images under normal conditions as statistically observed in practice and to acquire industry standard data.

[0012] The output of the database storage module is connected to the input of the data comparison module. The input of the data comparison module is also connected to the output of the power supply data acquisition module. The data comparison module combines the currently monitored current fluctuation image information with the current fluctuation image under normal conditions, compares the instantaneous current difference at each point, and summarizes the difference data information.

[0013] The output of the data comparison module is connected to the input of the abnormal power supply analysis module. The abnormal power supply analysis module plans the difference threshold for each point, marks the difference points that are higher than the difference threshold, generates abnormal difference points, and determines the various abnormal causes that form the abnormal difference points.

[0014] The output of the abnormal power supply analysis module is connected to the input of the weight planning module. The weight planning module calculates the weights corresponding to each abnormal cause according to the difference data and generates an abnormal cause weight database.

[0015] The output of the weighted planning module is connected to the input of the anomaly prediction module. The anomaly prediction module combines the anomaly cause weight database to analyze the instantaneous current difference between the currently monitored current fluctuation image information and the current fluctuation image under normal conditions, and calculates and predicts the anomaly cause according to the weight.

[0016] As a further improvement to this technical solution, the power supply data acquisition module includes a check data recording unit and a plotting data conversion unit. The check data recording unit is equipped with a current sensor to detect the current in the power supply circuit of the embedded computer and generate current detection data. The output end of the check data recording unit is connected to the input end of the plotting data conversion unit. The plotting data conversion unit receives the current detection data and converts the current detection data into plotting data to draw a current change waveform.

[0017] As a further improvement to this technical solution, the input end of the inspection data recording unit is connected to a unit for planning the unit time. The unit for planning the unit time is used to plan the unit detection time, and the current sensor performs unit detection according to the unit detection time.

[0018] As a further improvement to this technical solution, the data comparison module includes a comparison time point determination unit, a fluctuation difference calculation unit, and a difference data aggregation unit;

[0019] The comparison time point determination unit is used to determine the peak instantaneous point of the currently monitored current fluctuation image information and the current fluctuation image under normal conditions.

[0020] The output of the comparison time point determination unit is connected to the input of the fluctuation difference calculation unit, and the fluctuation difference calculation unit is used to calculate the instantaneous current difference at each point;

[0021] The output of the fluctuation difference calculation unit is connected to the input of the difference data aggregation unit. The difference data aggregation unit combines the instantaneous current difference at each point to aggregate various difference data information.

[0022] As a further improvement to this technical solution, the output end of the difference data aggregation unit is connected to a difference threshold planning unit. The difference threshold planning unit is used to plan the difference threshold and classify and process the difference data information according to the difference threshold.

[0023] As a further improvement to this technical solution, the abnormal power supply analysis module includes the collection of software operation abnormality information, hardware status information, and the impact of external hardware devices.

[0024] As a further improvement to this technical solution, the output terminal of the abnormal power supply analysis module is connected to a data update module, and the data update module is connected to the input terminal of the database storage module.

[0025] As a further improvement to this technical solution, the weight planning module includes a difference rate conversion unit and a weight score planning unit. The difference rate conversion unit is used to determine the abnormal difference conversion standard. The output of the difference rate conversion unit is connected to the input of the weight score planning unit. The weight score planning unit calculates the weight corresponding to each abnormal cause according to the abnormal difference conversion standard.

[0026] As a further improvement to this technical solution, the weight planning module adopts a weight planning algorithm, the formula of which is as follows:

[0027] ;

[0028] ;

[0029] in This is the weighted difference. This is the current peak value being detected. This represents the peak current under normal conditions. For the weight assignment function, , , as well as For each weight difference interval, to These represent the weights corresponding to each interval.

[0030] The second objective of this invention is to provide a monitoring method for a power supply equipment monitoring system based on an embedded computer, comprising the following steps:

[0031] S1. The power supply data acquisition module records the instantaneous current at each point of the embedded computer's power supply equipment and combines it with the microcontroller to simulate current fluctuation image information.

[0032] S2, the database storage module stores the current fluctuation images under normal conditions obtained from practical statistics and acquires industry standard data to determine the current fluctuation diagram displayed by the power supply equipment of the embedded computer under normal operating conditions of each software or hardware.

[0033] S3. The data comparison module combines the currently monitored current fluctuation image information with the current fluctuation image under normal conditions, compares the instantaneous current difference at each point, and summarizes the difference data information.

[0034] S4. The abnormal power supply analysis module plans the difference threshold for each point and marks the difference points that are higher than the difference threshold, generating abnormal difference points.

[0035] S5. The weight planning module calculates the weights corresponding to each abnormal cause based on the difference data and generates an abnormal cause weight database.

[0036] S6. The abnormal situation prediction module combines the abnormal cause weight database to analyze the instantaneous current difference at each point of the currently monitored current fluctuation image information and the current fluctuation image under normal conditions.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0038] 1. In this power supply equipment monitoring system and method based on embedded computers, the abnormal power supply situation analysis module plans the difference threshold for each point, and the weight planning module calculates the weight corresponding to each abnormal cause according to the difference data, generating an abnormal cause weight database. The difference size is proportional to the corresponding weight. Finally, the abnormal situation prediction module combines the abnormal cause weight database to analyze the instantaneous current difference between the currently monitored current fluctuation image information and the current fluctuation image under normal conditions, and calculates and predicts the abnormal cause according to the weight. This reduces the system operation steps, improves the efficiency of abnormal cause analysis, and allows maintenance personnel to plan the direction of abnormal causes in advance, avoiding them from performing ineffective process checks.

[0039] 2. In this power supply equipment monitoring system and method based on embedded computer, the unit detection time is planned by the unit time planning unit, the current sensor performs unit detection according to the unit detection time, and data is collected according to the unit time so as to locate the data collection time later.

[0040] 3. In the power supply equipment monitoring system and method based on embedded computer, the difference data aggregation unit combines the instantaneous current difference at each point to aggregate various difference data information for subsequent current anomaly judgment and to locate the cause of various anomalies.

[0041] 4. In this power supply equipment monitoring system and method based on embedded computer, data is updated through a data update module and the updated data is transmitted to a database storage module to expand the stored data in a timely manner for later elimination of the influence of external hardware devices. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the overall structure of Embodiment 1 of the present invention;

[0043] Figure 2 This is a schematic diagram of the power supply data acquisition module structure according to Embodiment 1 of the present invention;

[0044] Figure 3 This is a schematic diagram of the data comparison module structure in Embodiment 1 of the present invention;

[0045] Figure 4 This is a schematic diagram of the weight planning module structure in Embodiment 1 of the present invention.

[0046] The meanings of the labels in the diagram are as follows:

[0047] 10. Power supply data acquisition module; 110. Inspection data recording unit; 120. Drawing data conversion unit; 130. Data acquisition unit time planning unit;

[0048] 20. Database storage module;

[0049] 30. Data comparison module; 310. Comparison time point determination unit; 320. Fluctuation difference calculation unit; 330. Difference data summary unit; 340. Difference threshold planning unit;

[0050] 40. Abnormal power supply analysis module;

[0051] 50. Weighted planning module; 510. Difference rate conversion unit; 520. Weighted score planning unit;

[0052] 60. Abnormal Situation Prediction Module;

[0053] 70. Data update module. Detailed Implementation

[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0056] Example 1

[0057] Please see Figures 1-4 As shown, one of the objectives of this embodiment is to provide a power supply equipment monitoring system based on an embedded computer, including a power supply data acquisition module 10, a database storage module 20, a data comparison module 30, an abnormal power supply situation analysis module 40, a weight planning module 50, and an abnormal situation prediction module 60.

[0058] The power supply data acquisition module 10 is used to record the instantaneous current magnitude at each point of the power supply equipment of the embedded computer, and to simulate current fluctuation image information in conjunction with the microcontroller.

[0059] The output terminal of the power supply data acquisition module 10 is connected to the input terminal of the database storage module 20. The database storage module 20 is used to store current fluctuation images under normal conditions obtained through practical statistics and to acquire industry standard data.

[0060] The output of the database storage module 20 is connected to the input of the data comparison module 30. The input of the data comparison module 30 is also connected to the output of the power supply data acquisition module 10. The data comparison module 30 combines the currently monitored current fluctuation image information with the current fluctuation image under normal conditions, compares the instantaneous current difference at each point, and summarizes the difference data information.

[0061] The output of the data comparison module 30 is connected to the input of the abnormal power supply analysis module 40. The abnormal power supply analysis module 40 plans the difference threshold for each point, marks the difference points that are higher than the difference threshold, generates abnormal difference points, and determines the various abnormal causes that form the abnormal difference points.

[0062] The output of the abnormal power supply analysis module 40 is connected to the input of the weight planning module 50. The weight planning module 50 calculates the weights corresponding to each abnormal cause according to the difference data and generates an abnormal cause weight database.

[0063] The output of the weighted planning module 50 is connected to the input of the abnormal situation prediction module 60. The abnormal situation prediction module 60 combines the abnormal cause weight database to analyze the instantaneous current difference between the currently monitored current fluctuation image information and the current fluctuation image under normal conditions, and calculates and predicts the abnormal cause according to the weight.

[0064] In practical use, during the monitoring of the power supply equipment of an embedded computer, the power supply data acquisition module 10 first records the instantaneous current magnitude at each point of the embedded computer's power supply equipment. Combined with the current fluctuation image information simulated by the microcontroller, this forms the current fluctuation diagram of the embedded computer's power supply equipment. The database storage module 20 stores the current fluctuation images under normal conditions obtained through practical statistics and acquires industry standard data to determine the current fluctuation diagram displayed by the embedded computer's power supply equipment under normal operating conditions for each software or hardware. Subsequently, the data comparison module 30 compares the instantaneous current difference at each point with the currently monitored current fluctuation image information and the current fluctuation image under normal conditions, summarizing the various difference data. This data is then transmitted to the abnormal power supply situation analysis module 40. The power supply analysis module 40 plans the difference threshold for each point and marks the difference points that exceed the threshold, generating abnormal difference points. It then identifies the various abnormal causes that lead to these abnormal difference points, such as abnormal software operation causing abnormal fluctuations in the current fluctuation graph displayed by the power supply equipment. Subsequently, the weight planning module 50 calculates the weights corresponding to each abnormal cause based on the difference data, generating an abnormal cause weight database. The difference size is proportional to the corresponding weight. Finally, the abnormal situation prediction module 60 combines the abnormal cause weight database to analyze the instantaneous current difference between the currently monitored current fluctuation image information and the current fluctuation image under normal conditions, and calculates and predicts the abnormal causes according to the weights. This reduces system operation steps, improves the efficiency of abnormal cause analysis, and allows maintenance personnel to plan the direction of abnormal causes in advance, avoiding unnecessary process checks.

[0065] Furthermore, the power supply data acquisition module 10 includes a data recording unit 110 and a plotting data conversion unit 120. The data recording unit 110 is equipped with a current sensor to detect the current in the power supply circuit of the embedded computer and generate current detection data. The output of the data recording unit 110 is connected to the input of the plotting data conversion unit 120. The plotting data conversion unit 120 receives the current detection data and converts it into plotting data to draw a current change waveform. In the process of power supply data acquisition, the data recording unit 110 first uses a current sensor to detect the current in the power supply circuit of the embedded computer and generates current detection data. The current sensor senses the information of the measured current and can transform the sensed information into an electrical signal or other required form of information output that meets certain standards, so as to meet the requirements of information transmission, processing, storage, display, recording and control. Then, the plotting data conversion unit 120 receives the current detection data and converts it into plotting data to draw a current change waveform, which can intuitively show the current change amplitude of the power supply circuit of the embedded computer.

[0066] Furthermore, the input terminal of the inspection data recording unit 110 is connected to a unit time planning unit 130. The unit time planning unit 130 is used to plan the unit detection time. The current sensor performs unit detection according to the unit detection time. In order to form an orderly detection process, the unit detection time is first planned by the unit time planning unit 130, and the current sensor performs unit detection according to the unit detection time. Data is collected according to the unit time so that the data collection time can be located later.

[0067] Specifically, the data comparison module 30 includes a comparison time point determination unit 310, a fluctuation difference calculation unit 320, and a difference data aggregation unit 330;

[0068] The comparison time point determination unit 310 is used to determine the instantaneous peak point of the currently monitored current fluctuation image information and the current fluctuation image under normal conditions.

[0069] The output of the comparison time point determination unit 310 is connected to the input of the fluctuation difference calculation unit 320, and the fluctuation difference calculation unit 320 is used to calculate the instantaneous current difference at each point.

[0070] The output of the fluctuation difference calculation unit 320 is connected to the input of the difference data summarization unit 330. The difference data summarization unit 330 combines the instantaneous current difference at each point to summarize various difference data information.

[0071] In the process of comparing the current fluctuation image information detected at the moment with the current fluctuation image under normal conditions, the peak instantaneous point of the current fluctuation image information detected at the moment with the current fluctuation image under normal conditions is first determined by the comparison time point determination unit 310. Since the current fluctuation image is a sinusoidal image, each image has a minimum peak point and a maximum peak point. Each peak point is selected for comparison processing. Then, the instantaneous current difference at each point is calculated by the fluctuation difference calculation unit 320. The difference data summarization unit 330 combines the instantaneous current difference at each point to summarize the difference data information for subsequent current anomaly judgment and to locate the cause of each anomaly.

[0072] In practical use, during the process of summarizing the difference data, there are various reasons for current fluctuations, and current fluctuations will also occur during normal operation, which will also generate difference data. In addition, the output terminal of the difference data summarization unit 330 is connected to the difference threshold planning unit 340. The difference threshold planning unit 340 is used to plan the difference threshold and classify the difference data information according to the difference threshold. By planning the difference threshold through the difference threshold planning unit 340, the difference data information is classified according to the difference threshold. The difference data below the difference threshold is classified as normal difference, and the difference data not below the difference threshold is classified as abnormal difference. At this time, it is necessary to analyze the abnormal cause through the abnormal power supply situation analysis module 40. The difference threshold planning unit 340 can effectively avoid the abnormal cause analysis of normal difference.

[0073] In addition, the abnormal power supply analysis module 40 includes software operation anomaly information collection, hardware status information collection, and external hardware device impact assessment. Specifically, the software operation anomaly information collection involves analyzing the embedded computer exhibiting abnormal values, determining the background information of each running software program, analyzing the differences between its running data and the normal state, and locating the abnormal software. Hardware status information collection involves analyzing the embedded computer hardware exhibiting abnormal values, determining the hardware connection status and data read content, comparing it with the normal state, and locating the abnormal hardware. External hardware device impact assessment involves recording the connection status and data read content of newly connected hardware devices, based on the embedded computer's operating status.

[0074] Furthermore, the output of the abnormal power supply analysis module 40 is connected to a data update module 70, which is connected to the input of the database storage module 20. When the abnormal power supply analysis module 40 collects data on newly connected hardware devices, it records the connection status and data read content of the newly connected hardware, and transmits the data read content to the data update module 70. The data update module 70 updates the data and transmits the updated data to the database storage module 20 to expand the stored data in a timely manner for later elimination of the impact of external hardware devices.

[0075] Furthermore, the weight planning module 50 includes a difference rate conversion unit 510 and a weight score planning unit 520. The difference rate conversion unit 510 is used to determine the abnormal difference conversion standard. The output of the difference rate conversion unit 510 is connected to the input of the weight score planning unit 520. The weight score planning unit 520 calculates the weight corresponding to each abnormal cause according to the abnormal difference conversion standard. The difference rate conversion unit 510 determines the abnormal difference conversion standard, and the weight score planning unit 520 calculates the weight corresponding to each abnormal cause according to the abnormal difference conversion standard, and binds the abnormal cause to its corresponding weight to generate an abnormal cause weight database for later abnormal cause prediction.

[0076] Specifically, the weight planning module 50 employs a weight planning algorithm, the formula of which is as follows:

[0077] ;

[0078] ;

[0079] in This is the weighted difference. This is the current peak value being detected. This represents the peak current under normal conditions. For the weight assignment function, , , as well as For each weight difference interval, to These represent the weights corresponding to each interval.

[0080] The second objective of this embodiment is to provide a monitoring method for a power supply equipment monitoring system based on an embedded computer, comprising the following steps:

[0081] S1. The power supply data acquisition module 10 records the instantaneous current magnitude at each point of the embedded computer's power supply equipment and combines it with the microcontroller to simulate current fluctuation image information.

[0082] S2, Database storage module 20 stores the current fluctuation image under normal conditions statistically analyzed and obtains industry standard data to determine the current fluctuation image displayed by the power supply equipment of the embedded computer under normal operating conditions of each software or hardware.

[0083] S3. The data comparison module 30 combines the currently monitored current fluctuation image information with the current fluctuation image under normal conditions, compares the instantaneous current difference at each point, and summarizes the difference data information.

[0084] S4, Abnormal Power Supply Analysis Module 40 plans the difference threshold for each point, marks the difference points that are higher than the difference threshold, and generates abnormal difference points;

[0085] S5, the weight planning module 50 calculates the weights corresponding to each abnormal cause according to the difference data and generates an abnormal cause weight database;

[0086] S6, Abnormal Situation Prediction Module 60 combines the abnormal cause weight database to analyze the instantaneous current difference between the currently monitored current fluctuation image information and the current fluctuation image under normal conditions at each point.

[0087] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A power supply equipment monitoring system based on an embedded computer, characterized in that: It includes a power supply data acquisition module (10), a database storage module (20), a data comparison module (30), an abnormal power supply situation analysis module (40), a weight planning module (50), and an abnormal situation prediction module (60). The power supply data acquisition module (10) is used to record the instantaneous current magnitude at each point of the power supply equipment of the embedded computer, and to simulate the current fluctuation image information in conjunction with the microcontroller. The output end of the power supply data acquisition module (10) is connected to the input end of the database storage module (20). The database storage module (20) is used to store the current fluctuation image under normal conditions as statistically observed in practice and to acquire industry standard data. The output end of the database storage module (20) is connected to the input end of the data comparison module (30). The input end of the data comparison module (30) is also connected to the output end of the power supply data acquisition module (10). The data comparison module (30) combines the currently monitored current fluctuation image information with the current fluctuation image under normal conditions, compares the instantaneous current difference at each point, and summarizes the difference data information. The output of the data comparison module (30) is connected to the input of the abnormal power supply analysis module (40). The abnormal power supply analysis module (40) plans the difference threshold for each point, marks the difference points that are higher than the difference threshold, generates abnormal difference points, and determines the various abnormal causes that form abnormal difference points. The output of the abnormal power supply analysis module (40) is connected to the input of the weight planning module (50). The weight planning module (50) calculates the weights corresponding to each abnormal cause according to the difference data and generates an abnormal cause weight database. The output of the weight planning module (50) is connected to the input of the abnormal situation prediction module (60). The abnormal situation prediction module (60) combines the abnormal cause weight database to analyze the instantaneous current difference between the current fluctuation image information monitored at the moment and the current fluctuation image under normal conditions, and calculates and predicts the abnormal cause according to the weight.

2. The power supply equipment monitoring system based on an embedded computer according to claim 1, characterized in that: The power supply data acquisition module (10) includes a check data recording unit (110) and a plotting data conversion unit (120). The check data recording unit (110) is equipped with a current sensor to detect the current of the power supply equipment line of the embedded computer and generate current detection data. The output end of the check data recording unit (110) is connected to the input end of the plotting data conversion unit (120). The plotting data conversion unit (120) receives the current detection data and converts the current detection data into plotting data to draw a current change waveform.

3. The power supply equipment monitoring system based on an embedded computer according to claim 2, characterized in that: The input terminal of the inspection data recording unit (110) is connected to the acquisition unit time planning unit (130), which is used to plan the unit detection time. The current sensor performs unit detection according to the unit detection time.

4. The power supply equipment monitoring system based on an embedded computer according to claim 1, characterized in that: The data comparison module (30) includes a comparison time point determination unit (310), a fluctuation difference calculation unit (320), and a difference data aggregation unit (330). The comparison time point determination unit (310) is used to determine the peak instantaneous point of the current fluctuation image information monitored at the moment and the current fluctuation image under normal conditions. The output of the comparison time point determination unit (310) is connected to the input of the fluctuation difference calculation unit (320), and the fluctuation difference calculation unit (320) is used to calculate the instantaneous current difference at each point; The output of the fluctuation difference calculation unit (320) is connected to the input of the difference data summarization unit (330). The difference data summarization unit (330) combines the instantaneous current difference at each point to summarize various difference data information.

5. The power supply equipment monitoring system based on an embedded computer according to claim 4, characterized in that: The output of the difference data aggregation unit (330) is connected to the difference threshold planning unit (340), which is used to plan the difference threshold and classify the difference data information according to the difference threshold.

6. The power supply equipment monitoring system based on an embedded computer according to claim 1, characterized in that: The abnormal power supply analysis module (40) includes software operation abnormality information collection, hardware status information collection, and external hardware device impact.

7. The power supply equipment monitoring system based on an embedded computer according to claim 6, characterized in that: The output of the abnormal power supply analysis module (40) is connected to the data update module (70), and the data update module (70) is connected to the input of the database storage module (20).

8. The power supply equipment monitoring system based on an embedded computer according to claim 1, characterized in that: The weighted planning module (50) includes a difference rate conversion unit (510) and a weighted score planning unit (520). The difference rate conversion unit (510) is used to determine the abnormal difference conversion standard. The output of the difference rate conversion unit (510) is connected to the input of the weighted score planning unit (520). The weighted score planning unit (520) calculates the weight corresponding to each abnormal cause according to the abnormal difference conversion standard.

9. The power supply equipment monitoring system based on an embedded computer according to claim 8, characterized in that: The weight planning module (50) uses a weight planning algorithm, the formula of which is as follows: ； ； in This is the weighted difference. This is the current peak value being detected. This represents the peak current under normal conditions. For the weight assignment function, , , as well as For each weight difference interval, to These represent the weights corresponding to each interval.

10. A monitoring method applied to a power supply equipment monitoring system based on an embedded computer, comprising any one of claims 1-9, characterized in that: The methods and steps include the following: S1, Power supply data acquisition module (10) records the instantaneous current magnitude at each point of the power supply equipment of the embedded computer, and combines the microcontroller to simulate the current fluctuation image information; S2, Database storage module (20) stores the current fluctuation image under normal conditions of practice statistics and obtains industry standard data to determine the current fluctuation image displayed by the power supply equipment of the embedded computer under normal use conditions of each software or hardware. S3. The data comparison module (30) combines the current fluctuation image information monitored at the moment with the current fluctuation image under normal conditions, compares the instantaneous current difference at each point, and summarizes the difference data information. S4, Abnormal power supply analysis module (40) plans the difference threshold for each point, marks the difference points that are higher than the difference threshold, and generates abnormal difference points; S5, Weight planning module (50) calculates the weights corresponding to each abnormal cause according to the difference data and generates an abnormal cause weight database; S6. The abnormal situation prediction module (60) combines the abnormal cause weight database to analyze the instantaneous current difference between the current fluctuation image information monitored at the moment and the current fluctuation image under normal conditions.

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