Power supply switch health diagnosis method and system, medium and product

Abstract

A power supply switch health diagnosis method, system, medium and product relate to the field of data processing. The method comprises the following steps: determining operation parameters of a power supply switch, including cumulative opening and closing times, opening and closing current and effective arcing time in each opening and closing process, and opening and closing action time; calculating the mechanical life state of the power supply switch based on the accumulated opening and closing times and the preset rated opening and closing times; based on the breaking current and the effective arcing time, adopting a breaking current weighted accumulation method to calculate and obtain an accumulated electrical wear value, and according to the accumulated electrical wear value and a preset theoretical total wear amount, evaluating and obtaining an electrical life state of the power supply switch; obtaining an action performance state of the power supply switch based on the opening and closing action time and a preset action time normal range; and synthesizing the mechanical life state, the electrical life state and the action performance state to generate a health diagnosis result of the power supply switch. By implementing the technical scheme provided by the invention, the accuracy of health diagnosis of the power supply switch is improved.

Description

Technical Field

[0001] This application relates to the field of data processing, specifically to a method, system, medium, and product for diagnosing the health of a power supply switch. Background Technology

[0002] As a core control and protection device in a power system, the power supply switch undertakes the critical tasks of connecting, carrying, and interrupting normal or fault currents. The operational reliability of the power supply switch directly affects the safety and stability of the entire power grid. Traditional equipment maintenance strategies typically rely on periodic preventative maintenance and simple statistics of the cumulative number of operations to assess the health of the power supply switch. The drawback of this approach is that it cannot accurately reflect the actual differences in losses experienced by the power supply switch under different loads and operating conditions.

[0003] To address the inaccuracy of lifespan assessment based solely on the number of operations, an improved diagnostic technique has emerged in this field. This technique assesses electrical lifespan loss by monitoring key electrical parameters of the power supply switch during the switching process, particularly the magnitude of the switching current. For example, by setting one or more current thresholds, the number of times the switching current exceeds these thresholds is counted, and different weights are assigned to different thresholds for accumulation. This yields an electrical wear assessment result that more closely reflects actual operating conditions than simple counting. This method improves the accuracy of lifespan assessment to some extent, allowing maintenance decisions to be more based on the actual electrical stress history of the equipment.

[0004] However, while the aforementioned improved technologies address the differences in electrical losses, their assessment dimensions remain relatively singular. A power switch is a complex electromechanical device, and its health status is the result of multiple factors. This technology primarily focuses on electrical wear, neglecting real-time assessment of the mechanical performance of the operating mechanism and a comprehensive consideration of overall mechanical fatigue life. This increases the risk of misjudgment, leading to lower diagnostic accuracy. Summary of the Invention

[0005] This application provides a method, system, medium, and product for diagnosing the health of power supply switches, which improves the accuracy of power supply switch health diagnosis.

[0006] A first aspect of this application provides a method for health diagnosis of a power supply switch. The method includes: determining the operating parameters of the power supply switch, the operating parameters including the cumulative number of opening and closing cycles, the interrupting current and effective arcing time during each interruption process, and the opening and closing action time; calculating the mechanical life state of the power supply switch based on the cumulative number of opening and closing cycles and a preset rated number of opening and closing cycles; calculating the cumulative electrical wear value using the interrupting current weighted cumulative method based on the interrupting current and the effective arcing time, and evaluating the electrical life state of the power supply switch based on the cumulative electrical wear value and a preset theoretical total wear amount; obtaining the operating performance state of the power supply switch based on the opening and closing action time and a preset normal range of operating time; and generating a health diagnosis result for the power supply switch by comprehensively considering the mechanical life state, the electrical life state, and the operating performance state.

[0007] By adopting the above technical solutions, the operating parameters of the power supply switch are determined, including the cumulative number of opening and closing cycles, breaking current, effective arcing time, and opening and closing action time. This allows for comprehensive collection of key performance indicators of the power supply switch during operation. Using the cumulative number of opening and closing cycles and the rated number of opening and closing cycles, the mechanical life status of the power supply switch can be accurately assessed, and the wear degree of its mechanical components can be determined. Combining breaking current and effective arcing time, the weighted cumulative method of breaking current can quantitatively calculate the cumulative electrical wear value of the power supply switch. By comparing this with the theoretical total wear, the electrical life status of the power supply switch can be scientifically assessed, and its remaining service life under electrical stress can be predicted. Simultaneously, by comparing the opening and closing action time with the normal range, abnormalities in the operating mechanism of the power supply switch can be detected in a timely manner, and it can be determined whether its operating performance deviates from the normal operating range. Finally, by comprehensively considering the mechanical life status, electrical life status, and operating performance status, the health level of the power supply switch can be objectively evaluated from multiple dimensions, generating comprehensive health diagnostic results. This provides data support for condition-based maintenance, life management, and operation and maintenance decisions of the power supply switch, thereby improving the reliability and accuracy of the power supply switch and reducing the risk of power grid accidents.

[0008] Optionally, the mechanical life status includes mechanical life alarm status, mechanical life warning status, and mechanical life normal status. The step of calculating the mechanical life status of the power supply switch based on the cumulative number of opening and closing operations and the preset rated number of opening and closing operations specifically includes: receiving opening and closing operation commands from the control system of the power supply switch; comparing the linkage between the opening and closing operation commands and the cumulative number of opening and closing operations, filtering out invalid and duplicate count values ​​without corresponding operation commands to obtain valid count values; accumulating the valid count values ​​to obtain the target cumulative number of opening and closing operations; and retrieving the rated number of opening and closing operations matching the equipment model from a preset equipment parameter library according to the equipment model information of the power supply switch. The number is used as the preset rated number of opening and closing cycles; the remaining percentage of mechanical life is calculated using the target cumulative number of opening and closing cycles and the preset rated number of opening and closing cycles; the remaining percentage of mechanical life is compared with a first alarm threshold and a second alarm threshold, wherein the first alarm threshold is greater than the second alarm threshold; if the remaining percentage of mechanical life is less than the second alarm threshold, the mechanical life status is determined to be a mechanical life alarm status; if the remaining percentage of mechanical life is greater than or equal to the second alarm threshold and less than the first alarm threshold, it is determined to be a mechanical life warning status; if the remaining percentage of mechanical life is greater than or equal to the first alarm threshold, it is determined to be a normal mechanical life status.

[0009] By adopting the above technical solution, the system receives opening and closing operation commands from the power supply switch control system, enabling the acquisition of objective records of each operation and avoiding omissions or errors caused by manual transcription. By comparing the linkage between the opening and closing operation commands and the cumulative number of opening and closing operations, invalid and duplicate counts without corresponding commands can be automatically identified, thus filtering out dirty data caused by sensor malfunctions or signal anomalies and improving the data quality of the cumulative number of opening and closing operations. Accumulating the valid counts after filtering out anomalies yields a reliable target cumulative number of opening and closing operations. Based on the power supply switch's equipment model information, the rated number of opening and closing operations for the corresponding model can be quickly matched from a standardized equipment parameter library, ensuring a scientifically sound reference benchmark for mechanical life calculation. Using the target cumulative number of opening and closing operations and the rated number of opening and closing operations, the remaining mechanical life of the power supply switch can be intuitively quantified through percentage calculations. Comparing the remaining percentage of mechanical life with two-level alarm thresholds allows for accurate classification of the power supply switch's mechanical life status, enabling graded early warning of mechanical life and providing a quantitative basis for the formulation of maintenance strategies.

[0010] Optionally, the step of calculating the cumulative electrical wear value using the weighted cumulative method of the breaking current based on the breaking current and the effective arcing time specifically includes: acquiring the current signal during each breaking operation; performing wavelet threshold denoising processing on the current signal to obtain denoised current waveform data, and calculating the effective current value of the current breaking operation based on the denoised current waveform data; obtaining the arcing start time and arcing end time of the current breaking operation, and determining the arcing time based on the arcing start time and arcing end time; performing outlier verification on the arcing time, and if the arcing time does not exceed a preset range, determining the arcing time as the effective arcing time; if the arcing time exceeds the preset range, using the average of multiple target effective arcing times adjacent to the arcing time as the effective arcing time; and calculating the cumulative electrical wear value based on the effective current value, the denoised current waveform data, and the effective arcing time using a preset formula, wherein the preset formula is: ; Among them, W acc I is the cumulative electrical wear value. i Let i(t) be the effective value of the current during the i-th interruption operation, and i(t) be the instantaneous value of the arc current during the i-th interruption operation. ai The arc start time is the effective arc time. ei The arc end time is the effective arc time, and β is an adjustment factor.

[0011] By employing the above technical solutions, for each interruption operation, the complete current signal of the interruption process can be acquired, providing dynamic current change information and a data foundation for subsequent electromagnetic loss analysis. Wavelet threshold denoising of the acquired current signal effectively eliminates high-frequency noise and interference components, improving the signal-to-noise ratio and smoothness, and facilitating the extraction of current waveform features. Using the denoised current waveform data, the effective current value for each interruption can be accurately calculated, reflecting the circuit breaker's ability to interrupt fault current. Obtaining the arc start and end times for each interruption allows for precise determination of the duration of the arc burning on the contacts, revealing the arc energy release process. Outlier verification of the arc time, eliminating abnormal data exceeding the normal range, improves the reliability of the effective arc time. When individual arc times deviate abnormally, the average of several recent effective arc times is used for correction, reducing the impact of outliers on cumulative electrical wear calculations and improving the robustness of diagnostic results. Finally, by using a preset formula, a calculation model for weighted cumulative breaking current is formed by comprehensively considering the effective value of current, the instantaneous value of arc current, and the effective arcing time. This model can scientifically quantify the electromagnetic loss of the power supply switch contacts during each breaking operation, obtain the dynamically accumulated cumulative electrical wear value, and realize the quantitative assessment of the internal electrical health status of the power supply switch.

[0012] Optionally, obtaining the operating performance status of the power supply switch based on the opening and closing action time and a preset normal range of action time specifically includes: acquiring the historical opening and closing action times of the power supply switch to form a historical action time series; performing statistical analysis on the historical action time series to establish a dynamic baseline model, the dynamic baseline model including the mean and standard deviation of the historical action time series; setting a preset action time range based on the mean and the standard deviation; comparing the opening and closing action times with the preset action time range; if it is determined that the opening and closing action times exceed the preset action time range, then the operating performance status is determined to be in a deviation state; performing trend analysis on the historical action time series to obtain the rate of change of the opening and closing action times; if the rate of change exceeds a preset trend threshold, then the operating performance status is determined to be in a deviation state.

[0013] By employing the above technical solutions, historical opening and closing action time data of power supply switches over a period of time can be obtained, enabling the construction of a time series reflecting changes in operational performance. This facilitates trend analysis and anomaly diagnosis. Statistical analysis of the historical action time series extracts its inherent fluctuation patterns, allowing the establishment of a dynamic baseline model for the power supply switch's operational performance and quantifying the normal range of action time variation. The dynamic baseline model includes statistical characteristics such as the mean and standard deviation of historical action times, objectively characterizing the operational performance of a power supply switch under typical operating conditions. Based on the dynamic baseline model, the normal range of opening and closing action times for power supply switches can be scientifically set, avoiding both overly lenient settings that lead to missed abnormal actions and overly strict settings that lead to misjudgments of normal fluctuations. Comparing the online-collected opening and closing action times with the preset normal range automatically identifies abnormal actions exceeding the normal range, enabling the monitoring of deviations in operational performance. Trend analysis of the historical action time series can sensitively capture signs of slow degradation or abrupt changes in action time, providing early warnings of performance degradation risks through indicators such as the rate of change. This provides a reference for optimizing condition-based maintenance strategies and maximizes the reliability of power supply switch operations.

[0014] Optionally, after generating the health diagnosis result of the power supply switch, the method further includes: determining the mechanical life status value and electrical life status value of the power supply switch, wherein the mechanical life status value is the remaining percentage of the mechanical life, the electrical life status value is a preset value minus the percentage of electrical life consumed, and the percentage of electrical life consumed is the cumulative electrical wear value divided by the preset theoretical total wear amount; calculating an imbalance value based on the mechanical life status value and the electrical life status value, wherein the imbalance value is the absolute value of the difference between the mechanical life status value and the electrical life status value; comparing the imbalance value with a preset imbalance threshold; and when the imbalance value is greater than the preset imbalance threshold, generating a working condition diagnosis label based on the relative magnitude relationship between the mechanical life status value and the electrical life status value, and attaching the working condition diagnosis label to the health diagnosis result.

[0015] By adopting the above technical solution, after generating the health diagnosis results of the power supply switch, the status values ​​of the mechanical life and electrical life of the power supply switch are further determined, which can quantitatively characterize the health level of both. Using the remaining percentage of mechanical life as the mechanical life status value directly can intuitively represent the wear degree of mechanical components. The electrical life status value is obtained by subtracting the percentage of electrical life consumption from a preset value, where the percentage of electrical life consumption is obtained by dividing the cumulative electrical wear value by the theoretical total wear amount, which can objectively quantify the level of electrical life degradation of the power supply switch under electrical stress. Based on the mechanical life status value and the electrical life status value, by calculating the absolute value of the difference between the two, an imbalance value that comprehensively reflects the degree of imbalance between mechanical wear and electrical aging can be obtained. Comparing the imbalance value with a preset threshold, when it exceeds the threshold, it proves that there is a significant difference in the aging rate between the mechanical system and the electrical system of the power supply switch, and the overall system is in an unbalanced state. Further comparing the relative magnitudes of the mechanical life status value and the electrical life status value can determine whether mechanical wear or electrical aging is dominant, thereby generating corresponding operating condition diagnostic labels. Attaching the diagnosed operating condition tags to the health diagnosis results can intuitively reveal the potential risks of the power supply switch's operating conditions, prompting maintenance personnel to carry out targeted equipment maintenance, system optimization, and fault prevention, thereby effectively improving the accuracy and effectiveness of power supply switch maintenance.

[0016] Optionally, generating a working condition diagnostic label based on the relative magnitude of the mechanical life state value and the electrical life state value specifically includes: generating an excessive electrical stress label when the mechanical life state value is higher than the electrical life state value; and generating a frequent mechanical operation label when the mechanical life state value is lower than the electrical life state value.

[0017] By adopting the above technical solution, after determining that the mechanical life status value and electrical life status value of the power supply switch are severely unbalanced, the high-risk operating condition type of the power supply switch can be identified further based on their relative magnitudes. When the mechanical life status value is significantly higher than the electrical life status value, a "high electrical stress" label is generated, indicating that the power supply switch has been frequently switching under high current and high energy density conditions for a long time. The electrical circuit and contact system have been subjected to electrical stress exceeding the design value. Arc erosion has caused extensive wear of the contact material, accelerated aging of the insulating medium, and a significant risk of electrical faults. The reliability of the current transformer and operating mechanism needs to be closely monitored. When the mechanical life status value is significantly lower than the electrical life status value, a "frequent mechanical operation" label is generated, indicating that the power supply switch may be frequently operated under no-load or light-load conditions, leading to accelerated wear of mechanical components while the electrical circuit is subjected to relatively little short-circuit current impact. The mechanical life is much faster than the electrical life, requiring optimization of the circuit breaker's operating strategy to reduce unnecessary opening and closing actions. By identifying the diagnostic labels for two operating conditions, "excessive electrical stress" and "frequent mechanical operation," we can uncover deep-seated defects in the operating conditions of power supply switches, providing decision support for equipment management departments to develop targeted operation and maintenance plans and improve equipment status.

[0018] Optionally, generating a health diagnosis result for the power supply switch by comprehensively considering the mechanical lifespan status, the electrical lifespan status, and the operational performance status specifically includes: constructing a health index model for the power supply switch; inputting the mechanical lifespan status, the electrical lifespan status, and the operational performance status into the health index model to calculate the health index of the power supply switch; classifying the health index into levels based on preset health level criteria to obtain the health level of the power supply switch; and generating a health diagnosis result for the power supply switch, wherein the health diagnosis result includes the health index, the health level, the mechanical lifespan status, the electrical lifespan status, and the operational performance status.

[0019] By adopting the above technical solution, in order to quantitatively evaluate the overall health level of the power supply switch, a scientific and reasonable health index model needs to be constructed based on the three dimensions of state variables: mechanical life, electrical life, and operational performance. By inputting the quantitative indicators representing the mechanical, electrical, and operational states into the health index model, and through weighted calculations and data fusion, a dimensionless health index value between 0 and 100 can be obtained. The health index intuitively reflects the comprehensive health level of the power supply switch; a higher value indicates a healthier equipment condition, while a lower value indicates a certain degree of performance degradation or failure risk. Classifying the health index into levels corresponds to the health level of the power supply switch, intuitively revealing the current state of the equipment and providing maintenance personnel with graded evaluation results for quickly assessing equipment capabilities. By generating health diagnostic reports that include health index, health level, mechanical life status, electrical life status, and operational performance status, a comprehensive health profile of the power supply switch can be displayed, quantifying the performance of the equipment in different key performance aspects. This not only helps managers grasp the overall status of the equipment but also provides key references for front-line maintenance personnel to carry out targeted testing and maintenance. Ultimately, it enables condition-based maintenance and risk management driven by objective data, ensuring the long-term safe and stable operation of the power supply switch.

[0020] In a second aspect, embodiments of this application provide a power switch health diagnosis system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, which includes computer instructions, and the one or more processors call the computer instructions to cause the power switch health diagnosis system to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a power supply switch health diagnosis system, cause the power supply switch health diagnosis system to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a power supply switch health diagnosis system, cause the power supply switch health diagnosis system to perform the method described in the first aspect and any possible implementation thereof.

[0023] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: The power supply switch health diagnosis method provided in this application overcomes the limitations of traditional technologies that rely solely on cumulative operation counts or a single electrical life assessment dimension by comprehensively evaluating mechanical life status, electrical life status, and operational performance status. This method collects the operating parameters of the power supply switch, accurately calculates electrical wear values ​​using a weighted cumulative method of breaking current, and combines this with real-time monitoring of mechanical fatigue and operational performance to comprehensively reflect the overall health status of the power supply switch. Compared to existing technologies, this solution can more accurately identify the actual losses of equipment under different operating conditions, effectively reduce the risk of misjudgment, improve the comprehensiveness and accuracy of diagnosis, and provide a reliable basis for formulating scientific maintenance strategies, thereby significantly improving the safety and stability of power grid operation. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating a power supply switch health diagnosis method disclosed in an embodiment of this application; Figure 2 This is another schematic flowchart of a power supply switch health diagnosis method disclosed in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a power supply switch health diagnosis system provided in an embodiment of this application.

[0025] Explanation of reference numerals in the attached drawings: 301, Central Processing Unit; 302, Read-Only Memory; 303, Random Access Memory; 304, Bus; 305, Input / Output Interface; 306, Input Section; 307, Output Section; 308, Storage Section; 309, Communication Section; 310, Driver; 311, Removable Media. Detailed Implementation

[0026] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0027] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0028] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0029] This application provides a method for health diagnosis of power supply switches, referring to... Figure 1 , Figure 1 This is a flowchart illustrating a power supply switch health diagnosis method provided in an embodiment of this application. The method is applied to a system, which can execute a power supply switch health diagnosis program. The method includes steps S101 to S105, as follows: Step S101: Determine the operating parameters of the power supply switch. The operating parameters include the cumulative number of opening and closing operations, the breaking current and effective arcing time during each opening and closing process, and the opening and closing action time.

[0030] In step S101, operating parameters refer to a set of physical quantities characterizing the performance of the power supply switch during operation. These operating parameters are the foundational data source for subsequent health diagnostics. The cumulative number of opening and closing operations represents the total number of complete opening and closing operations performed by the power supply switch since its commissioning. This parameter is directly related to the degree of mechanical wear of the power supply switch. The breaking current during each interruption process represents the magnitude of the current flowing through the arc at the moment the contacts separate when the power supply switch performs an opening operation and cuts off the circuit. This parameter is a key factor affecting arc energy and contact electrical wear. The effective arcing time refers to the effective duration from the generation of the arc through contact separation to the reliable extinguishing of the arc during the interruption process. The arc during this period will cause contact erosion. The opening and closing action time represents the time consumed from the moment the power supply switch receives the opening or closing operation command until the main contacts of the power supply switch reach a completely open or completely closed state. This parameter reflects the performance status of the operating mechanism.

[0031] Specifically, the system connects to the monitoring unit or data acquisition device of the power supply switch to acquire operating parameters in real time or periodically. For the cumulative number of opening and closing cycles, the system monitors the opening and closing command signals and auxiliary contact feedback signals in the power supply switch control circuit. Each time a valid and complete operation cycle is detected, the internally stored counter is incremented. For the breaking current and effective arcing time during each breaking process, upon receiving the opening command, the system triggers a high-speed data acquisition function to record the current waveform during the breaking period at a high sampling rate. By analyzing the current waveform, the system identifies the starting point of arc generation (the moment when the current begins to decay unexpectedly) and the ending point of arc extinction (the moment when the current stabilizes at zero). The time difference between these two points is the effective arcing time. Simultaneously, the effective value or peak value of the current within this time period is calculated as the breaking current. For the opening and closing action time, the system records the precise timestamp of the operation command issuance and the precise timestamp of the corresponding change in the auxiliary contact position state. The difference between the two timestamps is the opening and closing action time. The system stores all acquired operating parameters to provide data input for subsequent steps.

[0032] Step S102: Calculate the mechanical life state of the power supply switch based on the cumulative number of opening and closing cycles and the preset rated number of opening and closing cycles.

[0033] In step S102, the preset rated number of opening and closing cycles refers to the maximum number of times the power supply switch manufacturer can reliably perform operations within its expected service life, as specified by the equipment design standards and type test results. This value serves as a benchmark for evaluating mechanical life. The mechanical life status is used to indicate the assessment conclusion regarding the current wear and aging degree of mechanical components of the power supply switch, such as operating mechanisms, linkages, and springs.

[0034] Specifically, the system first obtains the latest cumulative number of opening and closing cycles from step S101. Then, based on the equipment model identifier of the power supply switch, the system queries and retrieves the preset rated number of opening and closing cycles matching that model from the preset equipment parameter database. Next, the system calculates the percentage of mechanical life consumed using the formula: the cumulative number of opening and closing cycles divided by the preset rated number of opening and closing cycles, multiplied by 100%. The system internally sets warning thresholds and alarm thresholds for mechanical life, for example, a warning threshold of 80% and an alarm threshold of 95%. The system compares the calculated percentage of mechanical life consumed with the set thresholds. If the consumed percentage is greater than or equal to the alarm threshold, the system determines the mechanical life status of the power supply switch to be in an alarm state; if the consumed percentage is less than the alarm threshold but greater than or equal to the warning threshold, the system determines the mechanical life status to be in a warning state; if the consumed percentage is less than the warning threshold, the system determines the mechanical life status to be in a normal state. Finally, the system outputs the evaluated mechanical life status.

[0035] Please refer to Figure 2 In one possible implementation, the mechanical life state of the power supply switch is calculated based on the cumulative number of opening and closing cycles and the preset rated number of opening and closing cycles, specifically including steps S201-S209, as follows: Step S201: Receive the opening and closing operation command issued by the control system of the power supply switch.

[0036] In step S201, the opening and closing operation command refers to the electrical signal or data command issued by the control system of the power supply switch to drive the power supply switch to perform opening or closing actions. This command is the starting signal that triggers a valid operation.

[0037] Specifically, the system establishes a communication connection with the control system of the power supply switch and continuously listens for operation commands issued by the control system. This command can be a high or low level change at the hardware level or a specific message frame in the communication network. When the system detects such a command, it immediately records the type of command, i.e., opening or closing, as well as the precise timestamp of the command being issued, and uses this information as the basis for subsequent processing.

[0038] Step S202: Compare the linkage between the opening and closing operation commands and the cumulative number of opening and closing operations, filter out invalid count values ​​and duplicate count values ​​that do not correspond to the operation commands, and obtain the valid count values.

[0039] In step S202, the linkage relationship refers to the one-to-one correspondence between the opening / closing operation command and the actual mechanical action count of the power supply switch. An invalid count value refers to an unexpected count value generated by the counting device when no corresponding operation command is received, such as a miscount caused by electromagnetic interference or mechanical vibration. A duplicate count value refers to multiple counts generated by the counting device for a single operation command due to contact jitter or other reasons. A valid count value refers to a count value that has been verified and confirmed to uniquely correspond to a single valid opening / closing operation command.

[0040] Specifically, upon receiving a circuit breaker opening / closing command, the system opens a preset time window. Within this window, the system monitors changes in count values ​​from the auxiliary contacts of the power supply switch or a mechanical counter. The system correlates the count values ​​generated within this time window with the received operation command. If a count value is generated without a command being received, the system determines this count value as invalid and filters it out. If multiple count values ​​are detected within the time window after a command, the system retains only the first one, and subsequent count values ​​are determined as duplicate count values ​​and filtered out. Only when a unique count value matching the command type is detected within the time window is the system recognized as a valid count value.

[0041] Step S203: Accumulate the valid count values ​​to obtain the target cumulative number of opening and closing operations.

[0042] In step S203, the target cumulative number of opening and closing operations represents the sum of all valid operations performed by the power supply switch since its commissioning, after filtering out invalid and duplicate counts. This value is the precise input for mechanical life assessment.

[0043] Specifically, the system internally maintains a memory for storing the target cumulative number of circuit breaker openings and closings. The value in this memory is set to zero or restored from the last record during system initialization. Whenever a valid count value is generated in step S202 (typically one), the system performs an accumulation operation. The system reads the current target cumulative number of circuit breaker openings and closings from the memory, adds the new valid count value to that value, and then writes the calculated new sum back to the memory, thus completing the update of the target cumulative number of circuit breaker openings and closings.

[0044] Step S204: Based on the equipment model information of the power supply switch, retrieve the rated number of opening and closing cycles that matches the equipment model from the preset equipment parameter library as the preset rated number of opening and closing cycles.

[0045] In step S204, the equipment model information refers to a string or code used to uniquely identify the manufacturer, specifications, and performance level of the power supply switch. The preset equipment parameter library refers to a data set storing the technical parameters of different power supply switch models, such as a database table or configuration file. The rated number of opening and closing cycles represents the maximum number of operations guaranteed to ensure normal operation during the equipment's lifespan, as promised by the equipment manufacturer and verified through testing.

[0046] Specifically, the system first obtains the device model information of the object being diagnosed. This information may be manually entered during system configuration or automatically read from the power supply switch intelligent terminal via a communication protocol. Then, the system uses this device model information as a query keyword to search a local or remote preset device parameter database. This database stores key-value pairs, where the key is the device model information and the value is structured data containing multiple parameters. After finding a matching entry, the system extracts the rated number of opening and closing cycles and uses this value as the preset rated number of opening and closing cycles required for subsequent calculations.

[0047] Step S205: Calculate the remaining percentage of mechanical life using the target cumulative number of opening and closing cycles and the preset rated number of opening and closing cycles.

[0048] In step S205, the remaining mechanical life percentage is used to represent the proportion of the mechanical parts of the power supply switch that have not yet been consumed and can continue to be used to the total rated life.

[0049] Specifically, the system calls the target cumulative number of opening and closing operations obtained in step S203 and the preset rated number of opening and closing operations obtained in step S204. The system calculates this using a mathematical formula: the remaining percentage of mechanical life equals the sum of the number in parentheses minus the target cumulative number of opening and closing operations divided by the preset rated number of opening and closing operations, multiplied by 100%. The result is a percentage that accurately reflects the current remaining mechanical life.

[0050] Step S206: Compare the remaining percentage of mechanical life with the first alarm threshold and the second alarm threshold, wherein the first alarm threshold is greater than the second alarm threshold.

[0051] In step S206, the first alarm threshold and the second alarm threshold are two pre-set numerical standards used to divide the mechanical life state range. The first alarm threshold is the boundary between the normal state and the warning state, and the second alarm threshold is the boundary between the warning state and the alarm state, and the value of the first alarm threshold is greater than the value of the second alarm threshold.

[0052] Specifically, the system reads the set first alarm threshold and second alarm threshold from the configuration parameters. For example, the first alarm threshold can be set to 20% and the second alarm threshold to 5%. The system compares the remaining mechanical life percentage calculated in step S205 with these two thresholds to provide a basis for subsequent logical judgments.

[0053] Step S207: If the remaining percentage of mechanical life is less than the second alarm threshold, the mechanical life status is determined to be a mechanical life alarm status.

[0054] In step S207, the mechanical life alarm status indicates that the mechanical life of the power supply switch has been severely consumed, is close to or has reached the end of its life, and has an extremely high risk of failure, requiring immediate handling.

[0055] Specifically, the system performs a logical judgment based on the comparison result of step S206. If the system finds that the remaining percentage of mechanical life is less than the second alarm threshold, the judgment condition is met. The system then sets the mechanical life status attribute of the power supply switch to the mechanical life alarm status and may trigger a higher-level alarm event.

[0056] Step S208: If the remaining percentage of mechanical life is greater than or equal to the second alarm threshold and less than the first alarm threshold, then the mechanical life warning state is determined.

[0057] In step S208, the mechanical life warning status indicates that the mechanical life of the power supply switch has been largely consumed. Although it has not yet reached the scrapping standard, it has entered a stage that requires attention, and maintenance or replacement should be planned in advance.

[0058] Specifically, if the condition in the previous step S207 is not met, the system continues to perform logical judgment. If the system finds that the remaining percentage of mechanical life is greater than or equal to the second alarm threshold and simultaneously less than the first alarm threshold, then the judgment condition is met. The system then sets the mechanical life status attribute of the power supply switch to mechanical life warning status.

[0059] Step S209: If the remaining percentage of mechanical life is greater than or equal to the first alarm threshold, the mechanical life is determined to be in a normal state.

[0060] In step S209, the normal mechanical life state indicates that the mechanical life consumption of the power supply switch is still within a reasonable range, the equipment is operating stably, and no special maintenance intervention is required.

[0061] Specifically, if the conditions in steps S207 and S208 are not met, the system executes the final logical branch. At this point, the remaining percentage of mechanical life must be greater than or equal to the first alarm threshold. Based on this, the system sets the mechanical life status attribute of the power supply switch to the normal mechanical life state.

[0062] Step S103: Based on the breaking current and effective arcing time, the cumulative electrical wear value is calculated using the breaking current weighted cumulative method, and the electrical life status of the power supply switch is evaluated based on the cumulative electrical wear value and the preset theoretical total wear amount.

[0063] In step S103, the weighted cumulative method of breaking current refers to an engineering method for calculating the electrical wear of contacts. This method assumes that the amount of electrical wear generated by each breaking operation is proportional to a certain power of the breaking current and the effective arcing time, and accumulates the wear amounts of each operation. The cumulative electrical wear value represents a quantitative assessment of the total material loss caused by arc erosion of the power supply switch contacts since commissioning. The preset theoretical total wear amount refers to the maximum allowable wear limit of the contacts, determined based on the contact design and material characteristics. Exceeding this limit is considered the end of the electrical life of the contacts. The electrical life status is used to represent the assessment conclusion of the current wear degree of the arc-extinguishing chamber contacts of the power supply switch.

[0064] Specifically, the system first obtains the breaking current and effective arcing time of the current switching operation from step S101. The system uses a preset electrical wear calculation model; for example, the single wear amount is approximately equal to the nth power of the breaking current multiplied by the effective arcing time, where the exponent n is an empirical constant related to the contact material and arc-extinguishing medium, typically between 1.5 and 2.0. The system uses this model to calculate the single electrical wear amount caused by the current switching operation. Then, the system reads the historical cumulative electrical wear value obtained from the previous calculation from internal storage and adds the currently calculated single electrical wear amount to the historical cumulative electrical wear value to obtain the updated current cumulative electrical wear value. Simultaneously, the system retrieves the corresponding preset theoretical total wear amount from the equipment parameter library based on the power supply switch model. The system calculates the percentage of electrical life consumed using the formula: the current cumulative electrical wear value divided by the preset theoretical total wear amount, then multiplied by 100%. Similar to mechanical life assessment, the system compares this consumption percentage with preset electrical life warning and alarm thresholds to determine whether the current electrical life status of the power supply switch is normal, warning, or alarm.

[0065] In one possible implementation, the cumulative electrical wear value is calculated using the weighted cumulative method of breaking current and effective arcing time, specifically including steps S1031-S1036, as follows: Step S1031: For each switching operation, acquire the current signal during the switching process.

[0066] In step S1031, the interruption operation refers to the action of switching the power supply switch from a closed state to an open state, and interrupting the fault current or load current during this process. The current signal refers to an analog or digital quantity that can reflect the change of current over time during the interruption process, collected by sensors such as current transformers.

[0067] Specifically, the system monitors the line current connected in series with the power supply switch in real time using a high-frequency sampling device. When the system detects a trigger signal for an interruption operation, such as a trip command issued by a protection device, the system immediately begins acquiring the instantaneous value of the current signal at a sampling rate much higher than the power frequency, such as tens of thousands of times per second. The acquisition process continuously covers the entire time period from before the contacts separate to after the arc is completely extinguished, forming a high-resolution current time series data, which is then stored for subsequent analysis.

[0068] Step S1032: Perform wavelet threshold denoising on the current signal to obtain denoised current waveform data, and calculate the effective value of the current for the current interruption operation based on the denoised current waveform data.

[0069] In step S1032, wavelet threshold denoising is a signal processing technique used to separate and remove high-frequency noise from the original signal. The denoised current waveform data refers to a data sequence that, after wavelet threshold denoising, retains the main characteristics of the current and has a smoother waveform. The effective current value refers to the root mean square value characterizing the thermal effect of the current within a complete cycle before interruption.

[0070] Specifically, the system takes the current time series data acquired in step S1031 as input, applies a preset wavelet basis function, such as the db4 wavelet, to perform multi-level wavelet decomposition on the data, and obtains wavelet coefficients at different scales. The system sets a threshold based on noise characteristics, sets wavelet coefficients with absolute values ​​less than the threshold to zero or reduces them, and then uses the processed wavelet coefficients to perform inverse wavelet transform to reconstruct denoised current waveform data with little or no noise. Subsequently, based on this denoised current waveform data, the system extracts data from the stable cycle preceding the arcing event, and obtains the effective current value for the current interruption operation by calculating the square root of the average of the sum of squares of the instantaneous current values ​​within that cycle.

[0071] Step S1033: Obtain the arc start time and arc end time of the current interruption operation, and determine the arc time based on the arc start time and arc end time.

[0072] In step S1033, the arc start time refers to the precise moment when the moving and stationary contacts of the power supply switch separate, and the current breaks down the dielectric to form an arc. The arc end time refers to the moment when the arc is effectively stretched and cooled, eventually extinguished, and the current in the circuit is permanently zero. The arc duration refers to the length of time from the start to the end of the arc.

[0073] Specifically, the system analyzes the denoised current waveform data. The system accurately calibrates the arcing start time by detecting the inflection point where the current waveform distortion occurs, or by combining this with the change in the position signal of the switch auxiliary contacts. The system continues to monitor the current waveform, determining the moment when the instantaneous current value first crosses zero and then does not recover as the arcing end time. Finally, the system subtracts the arcing start time from the arcing end time to calculate the arcing time in milliseconds or microseconds.

[0074] Step S1034: Perform outlier verification on the arcing time. If the arcing time does not exceed the preset range, then determine the arcing time as a valid arcing time.

[0075] In step S1034, outlier verification is a data verification process used to determine whether the calculated arcing time is within a reasonable physical range. The preset range refers to the minimum and maximum range of normal arcing time fluctuations, derived from the design characteristics of the switchgear and historical operating data. The effective arcing time refers to the arcing time that has passed outlier verification and is confirmed to truly reflect the physical characteristics of the current switching process.

[0076] Specifically, the system reads the preset arcing time range for this type of switch from the configuration library, for example, 15 milliseconds to 50 milliseconds. The system compares the arcing time calculated in step S1033 with the upper and lower limits of the preset range. If the calculated arcing time value is greater than or equal to the minimum value of the range and less than or equal to the maximum value of the range, the system determines that the arcing time is a normal value and directly determines it as the valid arcing time for this switching operation for subsequent calculations.

[0077] Step S1035: If the arcing time exceeds the preset range, the average value of multiple target effective arcing times adjacent to the arcing time is used as the effective arcing time.

[0078] In step S1035, the multiple adjacent target effective arc times refer to the several arc time data that are closest to the current interruption operation time point in the historical record and have been confirmed as effective.

[0079] Specifically, when the verification result of step S1034 shows that the arcing time exceeds the preset range, the system determines that the calculation result is an abnormal value, possibly caused by a data acquisition error or special operating conditions. At this time, the system accesses the database storing historical operation data and retrieves the effective arcing time records of the five or ten most recent interruption operations that occurred before the current operation, according to the chronological order of the operations. The system adds these multiple historical effective arcing time values ​​together, calculates the arithmetic mean, and uses the calculated average as the corrected effective arcing time for the current interruption operation.

[0080] Step S1036: Based on the RMS current value, denoised current waveform data, and effective arcing time, calculate the cumulative electrical wear value using a preset formula. The preset formula is as follows: ; Among them, W acc I represents the cumulative electrical wear value. i Let i(t) be the effective value of the current during the i-th interruption operation, and i(t) be the instantaneous value of the arc current during the i-th interruption operation. ai The arc start time is the effective arc time, t. ei The arc end time is the effective arc burning time, and β is an adjustment factor.

[0081] In step S1036, the preset formula is a mathematical model used to quantify the degree of erosion of the contact material by the arc energy. The cumulative electrical wear value is the sum of the electrical wear generated by each opening and closing operation since the power supply switch was put into operation. The instantaneous value of the arc current refers to the specific value of the current changing with time during the arcing period, provided by the denoised current waveform data. The adjustment factor β is a dimensionless empirical constant used to correct for the difference in the erosion efficiency of the contact by the arc energy under different current magnitudes.

[0082] Specifically, the system first acquires the effective current value Iᵢ for this interruption operation, as well as the denoised current waveform data within the effective arcing time interval. This data provides the data from the arcing start time t. a ᵢ to the end of the arc burning time t e The system reads the preset adjustment factor β from the configuration, for example, 1.5. The system calculates the sum of the β-th power of the instantaneous arc current value i(t) at each sampling point within the effective arcing time period using a numerical integration method, i.e., calculating the integral term ∫i(t)ᵝdt. Subsequently, the system multiplies this integral result by the square of the effective current value Iᵢ to obtain the electrical wear amount generated by this interruption operation. Finally, the system reads the existing cumulative electrical wear value Wacc from memory and adds the calculated electrical wear amount to Wacc; the updated sum is the new cumulative electrical wear value.

[0083] For example, suppose a power switch performs an opening and closing operation. After the system acquires the current signal during the opening and closing process, it obtains smoothed and denoised current waveform data through wavelet threshold denoising processing, and calculates the effective value of the current during this opening operation as 2000 amperes. By analyzing the waveform, the system determines that the arcing start time is 10.5 milliseconds and the arcing end time is 35.5 milliseconds, thus calculating the arcing time to be 25 milliseconds. This value falls within the preset range of 15 to 50 milliseconds, and is therefore determined as the effective arcing time. Next, the system calculates electrical wear according to a preset formula, with the adjustment factor β set to 1.6. The system performs a numerical integration of the instantaneous value of the arc current i(t) within the 25 milliseconds of the arcing period to the power of 1.6, and multiplies the integration result by the square of the effective current value of 2000. Assume that the calculated electrical wear amount for this operation is 5 units. If the switch has previously recorded a cumulative electrical wear value of 120 units, the system will add the current 5 units to it, and finally obtain and store a new cumulative electrical wear value of 125 units.

[0084] Step S104: Based on the opening and closing action time and the preset normal range of action time, obtain the action performance status of the power supply switch.

[0085] In step S104, the preset normal operating time range refers to an acceptable fluctuation range set for the opening and closing operating time of the power supply switch. Operating times exceeding this range may indicate an abnormality in the operating mechanism. The operating performance status is used to represent the evaluation conclusions on the response speed, smoothness of operation, and reliability of the power supply switch operating mechanism.

[0086] Specifically, the system obtains the opening and closing action time of this operation from step S101. Instead of using a fixed value, the system establishes a dynamic baseline to determine the preset normal range for the action time. The system stores multiple opening and closing action times from the power supply switch's history, forming a time series. By statistically analyzing the most recent historical action time series, such as calculating the average and standard deviation of the series, the system sets the normal range to an interval equal to or less than the average plus or minus a certain number of standard deviations, for example, three times the standard deviation. This dynamic baseline can adapt to normal fluctuations caused by factors such as changes in ambient temperature. The system compares the currently obtained opening and closing action time with the calculated dynamic normal range. If the current action time falls within this range, the system determines the action performance status as normal. If the current action time exceeds this range, the system determines the action performance status as deviating or abnormal. Furthermore, the system also performs trend analysis on the historical action time series. If a clear trend of continuously lengthening or shortening action time is found, even if the current value is still within the normal range, the system will mark the action performance status as having an abnormal trend as an early warning.

[0087] In one possible implementation, the operating performance status of the power supply switch is obtained based on the normal range of the opening and closing action time and the preset action time, specifically including steps S1041-S1047, as follows: Step S1041: Obtain the historical opening and closing action times of the power supply switch to form a historical action time sequence.

[0088] In step S1041, the historical opening and closing operation time of the power supply switch refers to the time record of each opening or closing operation performed since the switch was put into operation, and the time unit is usually milliseconds. The historical operation time series is a data set composed of these historical operation times arranged in the order in which the operations occurred.

[0089] Specifically, the system accesses a historical database or log file storing operational data from the storage device. The system queries a power switch with a specific identifier and extracts all recorded opening and closing action times. This time data is typically stored along with a unique identifier and timestamp for each operation. The system sorts the retrieved action time data according to the chronological order of the operations, forming one or more ordered lists of values, such as a historical opening action time series and a historical closing action time series, for subsequent statistical analysis.

[0090] Step S1042: Perform statistical analysis on the historical action time series and establish a dynamic baseline model. The dynamic baseline model includes the mean and standard deviation of the historical action time series.

[0091] In step S1042, statistical analysis refers to using mathematical methods to calculate the historical action time series to reveal the central tendency and dispersion of the data. The dynamic baseline model is a mathematical reference model characterizing the distribution of normal action times of the power supply switch under its current health condition. The mean of the historical action time series represents the average level of all action times in the series. The standard deviation of the historical action time series measures the deviation of the action time values ​​from the mean.

[0092] Specifically, the system uses the historical action time series obtained in step S1041 as input data. First, the system calculates the arithmetic mean of all time values ​​in the series to obtain the mean. Next, the system calculates the square of the difference between each time value in the series and the mean, then calculates the average of these squared differences, and finally takes the square root of this average to obtain the standard deviation. The calculated mean and standard deviation together constitute the dynamic baseline model. This model is dynamic because whenever new action time data is generated, the system can incorporate it into the historical series and recalculate the mean and standard deviation, thus enabling the baseline model to reflect the gradual changes in switching performance.

[0093] Step S1043: Set a preset action time range based on the mean and standard deviation.

[0094] In step S1043, the preset action time range is a numerical range calculated based on the dynamic baseline model, which is used to define the normal fluctuation limit of the power supply switch action time.

[0095] Specifically, the system sets this range based on the mean and standard deviation in the dynamic baseline model established in step S1042. A commonly used method is to use the "three sigma" criterion in statistics, which is a range centered on the mean, fluctuating above and below the mean by three standard deviations. The system subtracts three standard deviations from the mean as the lower limit of the preset action time range, and adds three standard deviations to the mean as the upper limit of the range. For example, if the mean is 50 milliseconds and the standard deviation is 1 millisecond, the preset action time range is set to 47 milliseconds to 53 milliseconds.

[0096] Step S1044: Compare the opening and closing action time with the preset action time range.

[0097] In step S1044, the opening and closing operation time refers to the time value measured for the most recent single opening or closing operation that is being evaluated.

[0098] Specifically, after the power supply switch completes a new opening or closing operation, the monitoring system immediately measures and records the operation time. The system then compares this newly measured operation time value with the upper and lower limits of the preset operation time range calculated based on historical data in step S1043. The purpose of this comparison is to determine whether the latest operation time falls within the normal range defined by the historical data.

[0099] Step S1045: If it is determined that the opening and closing action time exceeds the preset action time range, then the action performance status is determined to be a deviation state.

[0100] In step S1045, the operational performance status is a qualitative assessment of the current health status of the power supply switch's mechanical operating performance. A deviation status is a specific performance state indicating that the switch's operational characteristics have deviated from the normal, stable baseline level.

[0101] Specifically, the system makes a judgment based on the comparison result of step S1044. If the newly measured opening and closing action time is less than the lower limit of the preset action time range, or greater than the upper limit of the range, the system determines that the action time is abnormal. Once determined to be abnormal, the system determines the action performance status of the power supply switch as a deviation state, and may trigger an alarm or generate a maintenance strategy.

[0102] Step S1046: Perform trend analysis on the historical action time series to obtain the rate of change of the opening and closing action time.

[0103] In step S1046, trend analysis is a method to predict future trends by analyzing the changing patterns of historical data over time. The rate of change of the opening and closing action time is an indicator that quantifies how quickly the action time changes with the increase of the number of operations, and is usually manifested as an overall increasing or decreasing trend in the action time series.

[0104] Specifically, the system performs linear regression analysis on the entire historical action time series, including the time of the most recent action. The system uses the operation sequence number (e.g., first, second, third operation) as the independent variable and the corresponding action time as the dependent variable to fit a straight line that best represents the data trend. The slope of this line represents the rate of change of the opening and closing action time. A positive slope indicates a trend of increasing action time, while a negative slope indicates a trend of decreasing action time.

[0105] Step S1047: If the rate of change exceeds the preset trend threshold, the motion performance state is determined to be in a deviation state.

[0106] In step S1047, the preset trend threshold is a pre-defined maximum absolute value of an acceptable rate of change. This threshold is used to determine whether the long-term trend of the action time exceeds the normal aging or wear rate.

[0107] Specifically, the system compares the absolute value of the rate of change calculated in step S1046 with a preset trend threshold read from the system configuration. For example, the preset trend threshold might be set to allow the action time to change by no more than 0.05 milliseconds per operation. If the absolute value of the calculated rate of change is greater than this threshold, for example, if the calculated action time increases by an average of 0.06 milliseconds per operation, the system considers the switch's performance to be degrading too rapidly. In this case, even if the current action time is still within the preset action time range, the system will determine the operating performance state of the power supply switch as a deviation state.

[0108] For example, suppose the system needs to evaluate the tripping performance of a power supply switch. The system first retrieves the tripping times of the switch's past 100 trips from the database, forming a historical action time series. Through statistical analysis of these 100 data points, the system calculates the mean of the dynamic baseline model to be 48.0 milliseconds, with a standard deviation of 0.5 milliseconds. Based on this, the system sets a preset action time range of 46.5 milliseconds to 49.5 milliseconds, calculated by adding or subtracting three times the standard deviation from the mean. At this point, the switch performs a new tripping operation, with a measured action time of 49.2 milliseconds. Since 49.2 milliseconds falls within the range of 46.5 milliseconds to 49.5 milliseconds, the switch appears normal based solely on this action time. However, the system then performs trend analysis on a total of 101 action time points, including this latest data point, and calculates through linear regression that the rate of change in action time is an average increase of 0.08 milliseconds per operation. The system's preset trend threshold is 0.05 milliseconds. Because the calculated rate of change of 0.08 milliseconds exceeded the preset threshold of 0.05 milliseconds, it indicated that although the switch's operating time was still within the normal range, its slowing trend was too rapid. Therefore, the system ultimately determined that the power switch's operating performance was in a deviated state and issued a warning to the maintenance personnel, suggesting that they should pay attention to the potential degradation of the switch's mechanical structure.

[0109] Step S105: Based on the comprehensive mechanical life status, electrical life status, and operational performance status, generate a health diagnosis result for the power supply switch.

[0110] In step S105, the health diagnosis result refers to the final conclusion and state description of the overall health level of the power supply switch after integrating the evaluation information of the three dimensions of mechanical life, electrical life and operating performance.

[0111] Specifically, the system aggregates the mechanical life status, electrical life status, and operational performance status obtained from the preceding steps. Internally, the system includes a comprehensive diagnostic decision rule base. This rule base defines the final health diagnosis results corresponding to different state combinations. For example, the rule base might define: if any one of the three states is an alarm state, the final health diagnosis result is a critical alarm, requesting immediate maintenance; if there is no alarm state but one or more warning states exist, the health diagnosis result is a general warning, requesting planned maintenance; if all states are normal, the health diagnosis result is healthy. The system matches the three input states against the rule base to generate the final diagnostic conclusion. The generated health diagnosis result is not just a simple status label, but can also be a detailed text description that clearly indicates which dimension(s) of performance are experiencing problems, thus providing clear guidance for maintenance personnel. For example, the output result might be: "Health diagnosis result is a warning, mainly because the electrical life is approaching the warning threshold; please pay attention to subsequent high current interruption situations."

[0112] In one possible implementation, a health diagnosis result for the power supply switch is generated by comprehensively considering the mechanical life status, electrical life status, and operational performance status, specifically including steps S1051-S1053, as follows: Step S1051: Construct a health index model for the power supply switch, input the mechanical life status, electrical life status, and operating performance status into the health index model, and calculate the health index of the power supply switch.

[0113] In step S1051, the power supply switch health index model refers to a mathematical formula or algorithm used to quantitatively assess the overall health status of the power supply switch. This model can integrate multiple performance status indicators into a single value. Mechanical life status represents the percentage of the power supply switch's remaining mechanical operating capacity relative to its total design capacity. Electrical life status represents the percentage of the power supply switch's remaining electrical load and breaking capacity relative to its total design capacity. Operational performance status represents the real-time performance of the power supply switch's mechanical actuators, typically quantified by the deviation of key parameters such as closing time and opening time from standard values. The power supply switch health index is a value calculated using the health index model that directly reflects the current overall health level of the power supply switch.

[0114] Specifically, the system first calls a pre-built and stored health index model for the power supply switch. This model is typically a weighted summation function, such as the health index equal to the mechanical lifespan state multiplied by a weight coefficient W1, plus the electrical lifespan state multiplied by a weight coefficient W2, and plus the operational performance state multiplied by a weight coefficient W3. The weight coefficients W1, W2, and W3 are pre-set based on expert experience or historical data analysis, reflecting the importance of different states on the overall health of the power supply switch. The system then obtains the latest values ​​for the mechanical lifespan state, electrical lifespan state, and operational performance state. Subsequently, the system uses these three state values ​​as input variables and substitutes them into the calculation formula of the health index model. The system executes the calculation and finally obtains a comprehensive value, which is the health index of the power supply switch.

[0115] Step S1052: Classify the health index according to the preset health level criteria to obtain the health level of the power supply switch.

[0116] In step S1052, the preset health level criterion refers to a set of predefined rules that map continuous health index value ranges to discrete, clearly defined health levels. The health index is the comprehensive score calculated in step S1051. The health level of the power supply switch refers to the category classified according to the health index, such as excellent, good, average, poor, etc., used to qualitatively describe the health status of the power supply switch.

[0117] Specifically, the system accesses preset health level criteria stored internally. These criteria include threshold ranges for multiple health indices. For example, the criteria can be defined as follows: a health index of 90 or above is excellent; between 75 and 90 is good; between 60 and 75 is average; and below 60 is poor. The system compares the health index of the power supply switch calculated in the previous step with each threshold range in the preset health level criteria. The system determines which specific range the health index value falls into. Once the range is determined, the system assigns the corresponding health level, such as good, to the current power supply switch. The final output of this process is the health level of the power supply switch.

[0118] Step S1053: Generate the health diagnosis results of the power supply switch. The health diagnosis results include health index, health level, mechanical life status, electrical life status, and operating performance status.

[0119] In step S1053, the health diagnosis result of the power supply switch refers to a comprehensive report or dataset that fully displays the health assessment information of the power supply switch. The health index is a quantitative comprehensive health score. The health level is a qualitative classification of the health status. Mechanical lifespan, electrical lifespan, and operational performance status are the three key dimensions that form the basis of the health assessment.

[0120] Specifically, after completing the health index calculation and health level classification, the system begins to generate the final health diagnosis result. The system first gathers all relevant assessment information, including: the health index calculated in step S1051, the health level assessed in step S1052, and the raw values ​​of the mechanical life status, electrical life status, and operational performance status as the basis for the assessment. Then, the system integrates these five data points into a structured data record. This record is formatted for easy viewing and display, ultimately forming a complete health diagnosis result for the power supply switch. This result includes both a macro-level comprehensive evaluation and retains detailed underlying status data, providing comprehensive data support for subsequent equipment maintenance and management decisions.

[0121] In one possible implementation, after generating the health diagnosis result of the power supply switch, the method further includes steps S106-S109, as follows: Step S106: Determine the mechanical life status value and electrical life status value of the power supply switch. The mechanical life status value is the percentage of mechanical life remaining, and the electrical life status value is the preset value minus the percentage of electrical life consumed. The percentage of electrical life consumed is the cumulative electrical wear value divided by the preset theoretical total wear amount.

[0122] In step S106, the mechanical life status value represents the percentage of the remaining mechanical operation count of the power supply switch relative to the total designed operation count. The electrical life status value represents the remaining current carrying and breaking capacity of the power supply switch. The remaining mechanical life percentage refers to the ratio of the remaining operable counts of the switch to the total designed operation count. The preset value is usually set to 100%, representing the initial full electrical life. The electrical life consumption percentage refers to the proportion of the accumulated electrical wear of the switch relative to its total designed wear. The accumulated electrical wear value is the sum of contact losses caused by each interruption of fault current since the switch was put into operation. The preset theoretical total wear is the total electrical wear that the switch can withstand before it is scrapped, as specified by the manufacturer.

[0123] Specifically, the system first determines the mechanical lifespan status value. The system retrieves the total designed mechanical operation count of the power supply switch from the equipment file and calculates the total number of currently executed operations from the operation records. The remaining percentage of mechanical lifespan is calculated using the formula (Total designed mechanical operation count - Total currently executed operations) / Total designed mechanical operation count × 100%, and this result is the mechanical lifespan status value. Next, the system determines the electrical lifespan status value. The system retrieves the current value during each switching operation and calculates the electrical wear amount for a single operation based on a specific wear model, such as the I²t model. Then, the electrical wear amounts for all historical operations are summed to obtain the cumulative electrical wear value. The system then retrieves the preset theoretical total wear amount from the equipment file. The percentage of electrical lifespan consumption is calculated using the formula (Cumulative electrical wear value / Preset theoretical total wear amount) × 100%. Finally, the electrical lifespan status value is obtained by subtracting the calculated percentage of electrical lifespan consumption from the preset value of 100%.

[0124] Step S107: Calculate the imbalance value based on the mechanical life state value and the electrical life state value. The imbalance value is the absolute value of the difference between the mechanical life state value and the electrical life state value.

[0125] In step S107, the imbalance value is an indicator used to quantify the difference in the rate of mechanical wear and electrical wear of the power supply switch.

[0126] Specifically, the system uses the mechanical lifespan state value and electrical lifespan state value calculated in step S106. The system subtracts these two percentage values ​​to obtain a difference. Since the system is only concerned with the magnitude of the difference rather than its direction, it takes the absolute value of this difference. For example, if the mechanical lifespan state value is 80% and the electrical lifespan state value is 60%, then the imbalance value is |80% - 60%|, or 20%. This calculation result is determined by the system as the imbalance value for subsequent judgments.

[0127] Step S108: Compare the imbalance value with the preset imbalance threshold.

[0128] In step S108, the preset imbalance threshold is a pre-set reference value used to determine whether the degree of imbalance between mechanical life and electrical life exceeds an acceptable range.

[0129] Specifically, the system reads the preset imbalance threshold set for a specific model or operating condition of the power supply switch from its own configuration parameter library. This threshold is usually set by experienced power engineers based on equipment characteristics and operating requirements, for example, 30%. The system compares the imbalance value calculated in step S107 with this preset imbalance threshold.

[0130] Step S109: When the imbalance value is greater than the preset imbalance threshold, generate a working condition diagnostic label based on the relative size relationship between the mechanical life state value and the electrical life state value, and attach the working condition diagnostic label to the health diagnosis result.

[0131] In step S109, the operating condition diagnostic label is a text identifier used to describe a specific operating mode that leads to an imbalance in mechanical and electrical lifespan consumption. The health diagnosis result is a conclusion about the overall condition of the power supply switch drawn from a comprehensive evaluation.

[0132] Specifically, the system first checks the comparison result of step S108. Only when the imbalance value is greater than a preset imbalance threshold will the system execute subsequent operations. At this point, the system further compares the relative magnitudes of the mechanical lifespan status value and the electrical lifespan status value. If the mechanical lifespan status value is less than the electrical lifespan status value, it indicates that the mechanical wear rate is much faster than the electrical wear rate, and the system generates a condition diagnostic label with the content "Frequent Operation Condition". Conversely, if the mechanical lifespan status value is greater than the electrical lifespan status value, it indicates that the electrical wear rate is much faster than the mechanical wear rate, and the system generates a condition diagnostic label with the content "Heavy Load Condition". Finally, the system appends the generated condition diagnostic label to the existing health diagnosis results to form a more detailed diagnostic report.

[0133] For example, suppose the initial health diagnosis of a power switch is rated as "good condition". The system then performs an operating condition analysis. The system determines that the switch's design mechanical life is 10,000 cycles, and it has already been operated 8,000 times. The mechanical life status value is calculated as (10,000-8,000) / 10,000, which is 20%. Simultaneously, the system calculates the cumulative electrical wear value as 4,000 units based on historical breaking current records. Since the switch's preset theoretical total wear is 20,000 units, the electrical life consumption percentage is calculated as 4,000 / 20,000, or 20%, resulting in an electrical life status value of 100%-20%, or 80%. Subsequently, the system calculates the absolute value of the imbalance value as |20% - 80%|, which is 60%. The system compares this 60% with the preset imbalance threshold of 30%, finding that 60% is greater than 30%, indicating a significant imbalance in lifespan consumption. Since the mechanical life condition value of 20% is much less than the electrical life condition value of 80%, the system determines that the switch's operating condition is characterized by mechanical wear far exceeding electrical wear, and therefore generates a "frequent operation condition" diagnostic label. Finally, the system attaches this label to the initial diagnostic result, and the final output complete health diagnosis result is "Good condition, operating condition diagnosis: frequent operation condition," thus indicating to maintenance personnel that although the switch's overall condition is acceptable, its operation mode is mainly characterized by high-frequency mechanical actions.

[0134] In one possible implementation, a condition diagnostic label is generated based on the relative magnitude of the mechanical life state value and the electrical life state value, specifically including steps S1091-S1092, as follows: Step S1091: When the mechanical life state value is higher than the electrical life state value, generate an electrical stress too high label.

[0135] In step S1091, the mechanical life status value refers to the percentage of the remaining mechanical operating capacity of the power supply switch relative to its total design capacity. The electrical life status value refers to the percentage of the remaining electrical carrying and breaking capacity of the power supply switch relative to its total design capacity. The excessive electrical stress label is a text identifier used to indicate that the electrical life of the power supply switch is consumed significantly faster than its mechanical life, a condition typically caused by frequent interruptions of large currents or fault currents.

[0136] Specifically, when the system is triggered to generate a diagnostic label, it first obtains the previously calculated mechanical life status value and electrical life status value. The system compares these two percentage values. The condition is met when the system determines that the mechanical life status value is greater than the electrical life status value. This indicates that the electrical performance degradation rate of the power supply switch exceeds the wear rate of the mechanical components. Therefore, the system generates a diagnostic label indicating excessive electrical stress, which is subsequently added to the health diagnosis results.

[0137] Step S1092: When the mechanical life state value is lower than the electrical life state value, generate a frequent mechanical operation tag.

[0138] In step S1092, the mechanical life status value represents the percentage of the power supply switch's remaining mechanical operation count relative to the total design count. The electrical life status value represents the percentage of the power supply switch's remaining carrying and breaking current capacity relative to its initial full capacity. The frequent mechanical operation label is a text identifier used to indicate that the power supply switch's mechanical lifespan is depleted significantly faster than its electrical lifespan; this condition is typically caused by high-frequency closing and opening operations.

[0139] Specifically, the system also acquires the calculated mechanical life status value and electrical life status value. The system compares these two values. The condition is met when the system determines that the mechanical life status value is less than the electrical life status value. This indicates that the wear rate of the mechanical components of the power supply switch exceeds the rate of electrical performance degradation, typically meaning that the switch is frequently operated, but the electrical stress borne by each operation is relatively small. Therefore, the system generates a diagnostic label indicating frequent mechanical operation and prepares this label to be attached to the health diagnosis results.

[0140] For example, for power supply switch A installed on an important transmission line, the system calculates its mechanical lifespan status value to be 92% and its electrical lifespan status value to be 55%. Comparing these two values, the system finds that 92% is greater than 55%, meaning the mechanical lifespan status value is higher than the electrical lifespan status value. This clearly indicates that the electrical lifespan of this power supply switch is depleted much faster than its mechanical lifespan, due to the switch repeatedly interrupting line fault currents or heavy load currents. Therefore, the system generates an excessive electrical stress label. For another power supply switch B installed in a factory's internal power distribution network, used for frequently starting and stopping large motors, the system calculates its mechanical lifespan status value to be 40% and its electrical lifespan status value to be 88%. The system comparison finds that 40% is less than 88%, meaning the mechanical lifespan status value is lower than the electrical lifespan status value. This indicates that the mechanical wear rate of this power supply switch is much faster than its electrical wear rate, because the switch requires a large number of closing and opening operations daily. Therefore, the system generates a frequent mechanical operation label.

[0141] The following describes a power switch health diagnosis system according to an embodiment of the present invention from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the structure of a power supply switch health diagnosis system in an embodiment of this application.

[0142] It should be noted that, Figure 3 The structure of the power switch health diagnosis system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0143] like Figure 3 As shown, a power switch health diagnostic system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 302 or a program loaded from storage section 308 into random access memory (RAM) 303, such as performing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0144] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0145] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0146] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0147] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0148] Specifically, a power switch health diagnosis system according to this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements a power switch health diagnosis method provided in the above embodiment.

[0149] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in a power switch health diagnosis system described in the above embodiments; or it may exist independently and not assembled into the power switch health diagnosis system. The storage medium carries one or more computer programs, which, when executed by a processor of the power switch health diagnosis system, cause the power switch health diagnosis system to implement the power switch health diagnosis method based on IoT data encryption transmission provided in the above embodiments.

Claims

1. A method for diagnosing the health of a power supply switch, characterized in that, The method includes: Determine the operating parameters of the power supply switch, including the cumulative number of opening and closing operations, the breaking current and effective arcing time during each opening process, and the opening and closing action time. Based on the cumulative number of opening and closing cycles and the preset rated number of opening and closing cycles, the mechanical life state of the power supply switch is calculated. Based on the interrupting current and the effective arcing time, the cumulative electrical wear value is calculated using the weighted cumulative method of interrupting current, and the electrical life status of the power supply switch is evaluated based on the cumulative electrical wear value and the preset theoretical total wear amount. Based on the opening and closing action time and the preset normal range of action time, the action performance status of the power supply switch is obtained; By combining the mechanical life status, the electrical life status, and the operational performance status, a health diagnosis result for the power supply switch is generated.

2. The method according to claim 1, characterized in that, The mechanical life status includes mechanical life alarm status, mechanical life warning status, and mechanical life normal status. The calculation of the mechanical life status of the power supply switch based on the cumulative number of opening and closing cycles and the preset rated number of opening and closing cycles specifically includes: Receives the opening and closing operation commands issued by the control system of the power supply switch; By comparing the linkage between the opening and closing operation commands and the cumulative number of opening and closing operations, invalid count values ​​and duplicate count values ​​without corresponding operation commands are filtered out to obtain valid count values; The effective count values ​​are summed to obtain the target cumulative number of opening and closing operations; Based on the equipment model information of the power supply switch, the rated number of opening and closing cycles matching the equipment model is retrieved from the preset equipment parameter library as the preset rated number of opening and closing cycles; The remaining percentage of mechanical life is calculated using the target cumulative number of opening and closing cycles and the preset rated number of opening and closing cycles. The remaining percentage of mechanical life is compared with a first alarm threshold and a second alarm threshold, wherein the first alarm threshold is greater than the second alarm threshold; If the remaining percentage of mechanical life is less than the second alarm threshold, then the mechanical life status is determined to be a mechanical life alarm status. If the remaining percentage of mechanical life is greater than or equal to the second alarm threshold and less than the first alarm threshold, it is determined to be a mechanical life warning state; If the remaining percentage of mechanical life is greater than or equal to the first alarm threshold, it is determined that the mechanical life is in a normal state.

3. The method according to claim 1, characterized in that, The cumulative electrical wear value is calculated using the weighted cumulative method of breaking current based on the breaking current and the effective arcing time, specifically including: For each switching operation, the current signal during the switching process is collected; The current signal is subjected to wavelet threshold denoising processing to obtain denoised current waveform data, and the effective value of the current for the current interruption operation is calculated based on the denoised current waveform data. Obtain the arc start time and arc end time of the current interruption operation, and determine the arc time based on the arc start time and arc end time; Anomaly detection is performed on the arcing time. If the arcing time does not exceed the preset range, the arcing time is determined to be a valid arcing time. If the arcing time exceeds the preset range, the average value of multiple target effective arcing times adjacent to the arcing time is used as the effective arcing time. Based on the RMS current value, the denoised current waveform data, and the effective arcing time, the cumulative electrical wear value is calculated using a preset formula, which is: ； Among them, W acc I is the cumulative electrical wear value. i Let i(t) be the effective value of the current during the i-th interruption operation, and i(t) be the instantaneous value of the arc current during the i-th interruption operation. ai The arc start time is the effective arc time, t. ei The arc end time is the effective arc time, and β is an adjustment factor.

4. The method according to claim 1, characterized in that, The process of obtaining the operating performance status of the power supply switch based on the opening and closing action time and the preset normal range of action time specifically includes: The historical opening and closing times of the power supply switch are obtained to form a historical action time sequence. Statistical analysis is performed on the historical action time series to establish a dynamic baseline model, which includes the mean and standard deviation of the historical action time series. Based on the mean and the standard deviation, a preset action time range is set; Compare the opening and closing action time with the preset action time range; If it is determined that the opening and closing action time exceeds the preset action time range, then the action performance state is determined to be a deviation state. Trend analysis is performed on the historical action time series to obtain the rate of change of the opening and closing action time; If the rate of change exceeds a preset trend threshold, the action performance state is determined to be in a deviation state.

5. The method according to claim 2, characterized in that, After generating the health diagnosis result of the power supply switch, the method further includes: The mechanical life status value and electrical life status value of the power supply switch are determined. The mechanical life status value is the percentage of the remaining mechanical life, and the electrical life status value is a preset value minus the percentage of electrical life consumed. The percentage of electrical life consumed is the cumulative electrical wear value divided by the preset theoretical total wear amount. The imbalance value is calculated based on the mechanical life state value and the electrical life state value. The imbalance value is the absolute value of the difference between the mechanical life state value and the electrical life state value. The imbalance value is compared with a preset imbalance threshold. When the imbalance value is greater than the preset imbalance threshold, a working condition diagnostic label is generated based on the relative magnitude of the mechanical life state value and the electrical life state value, and the working condition diagnostic label is attached to the health diagnosis result.

6. The method according to claim 5, characterized in that, The step of generating a condition diagnostic label based on the relative magnitude of the mechanical life state value and the electrical life state value specifically includes: When the mechanical life state value is higher than the electrical life state value, an excessive electrical stress label is generated; When the mechanical life state value is lower than the electrical life state value, a frequent mechanical operation tag is generated.

7. The method according to claim 1, characterized in that, The health diagnosis result of the power supply switch is generated by comprehensively considering the mechanical life status, the electrical life status, and the operational performance status, specifically including: A health index model for the power supply switch is constructed, and the mechanical life state, electrical life state, and operational performance state are input into the health index model to calculate the health index of the power supply switch. The health index is classified into levels based on preset health level criteria to obtain the health level of the power supply switch; Generate a health diagnosis result for the power supply switch, the health diagnosis result including the health index, the health level, the mechanical life status, the electrical life status, and the operating performance status.

8. A power supply switch health diagnosis system, characterized in that, The power supply switch health diagnosis system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the power supply switch health diagnosis system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the power supply switch health diagnosis system, the power supply switch health diagnosis system performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the power supply switch health diagnosis system, the power supply switch health diagnosis system performs the method as described in any one of claims 1-7.

Images