A low-voltage switch cabinet operation data abnormality analysis processing method and system

Abstract

The application belongs to the technical field of data processing, and particularly relates to a low-voltage switch cabinet operation data abnormality analysis processing method and system, which comprises the following steps: obtaining standardized data of a low-voltage switch cabinet; using three-phase load current, key contact temperature and cabinet internal environment temperature in the standardized data to calculate effective contact resistance of key contacts of each phase branch and to calculate a weighted arithmetic mean value, to obtain a normal reference contact resistance, and taking a ratio of the two as an abnormal contact degree of each phase at each time; constructing a time sequence sliding window based on the abnormal contact degree, obtaining a time sequence segment of each phase contact state, fitting to obtain a contact deterioration degree by a least square method, calculating a standard deviation to obtain a contact fluctuation degree, combining the abnormal contact degree and the contact deterioration degree to obtain a comprehensive risk score, taking a maximum value as a final risk score and generating a risk assessment result. The application improves the accuracy of low-voltage switch cabinet operation data abnormality detection.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for analyzing and processing abnormal operating data of low-voltage switchgear. Background Technology

[0002] As the terminal power distribution equipment in a power system, the operational reliability of low-voltage switchgear directly affects power supply quality and safety. With the development of smart grids, real-time monitoring of key parameters such as contact temperature and load current within the switchgear has become standard practice, and various anomaly analysis technologies are also being applied to assess operational status.

[0003] Existing low-voltage switchgear operation data anomaly analysis technologies mostly rely on the spatial distribution of data at a single sampling moment as the core judgment basis. The core idea is to determine whether there is an anomaly by analyzing the sparsity of the distribution of data points in the parameter space. These methods generally treat the data points at each sampling moment as independent discrete samples, only focusing on whether the absolute value of the parameter at the current moment exceeds the threshold or deviates from the normal distribution range, but ignoring the core characteristic of low-voltage switchgear operation data, namely, the time sequence dependency.

[0004] In the actual operation of low-voltage switchgear, typical faults such as contact oxidation and increased contact resistance caused by loose connections are not sudden extreme anomalies, but rather manifest as a slow, gradual trend of operating parameters over a long period of time. Under the same load, contact temperature will continue to rise and contact resistance will gradually increase, which are typical characteristics of fault development. Because existing analysis techniques lack the ability to perceive the evolution of time, they cannot capture these early fault characteristics that do not reach extreme outliers but have a clear trend of deterioration. They are often confused with normal parameter fluctuations, ultimately leading to the underreporting of gradual faults. This limitation makes it difficult for existing technologies to achieve early warning of potential equipment hazards and cannot meet the actual needs of power systems for predictive maintenance of low-voltage switchgear throughout its entire life cycle. Summary of the Invention

[0005] To address the technical problem that existing low-voltage switchgear operation data anomaly analysis technologies ignore data time-series dependencies, making it difficult to capture gradual early faults that have not reached extreme outliers but show a clear trend of deterioration, and easily leading to missed reports, this invention provides a method and system for low-voltage switchgear operation data anomaly analysis and processing.

[0006] In a first aspect, the present invention provides a method for analyzing and processing abnormal operating data of a low-voltage switchgear, comprising: real-time acquisition and preprocessing of operating state sequence data of the low-voltage switchgear to obtain standardized operating state sequence data; based on the thermal balance principle of Joule's law combined with dynamic heat dissipation characteristics, using the three-phase load current, critical contact temperature, and ambient temperature inside the cabinet in the standardized operating state sequence data to calculate the effective contact resistance of critical contacts in each phase branch; acquiring the effective contact resistance during the normal operation phase of the low-voltage switchgear and calculating the weighted arithmetic mean to obtain the normal reference contact resistance of critical contacts in each phase branch; and using the effective contact resistance of critical contacts in each phase branch... The abnormal contact degree of each phase branch critical contact is obtained by comparing the ratio of the abnormal contact resistance to the normal reference contact resistance of the corresponding phase. Based on the abnormal contact degree of each phase branch critical contact at each time, a time-series sliding window is constructed to obtain the time-series segment of the contact state of each phase. The time-series segment is fitted using the least squares method, and the fitting slope is used as the contact deterioration degree. The standard deviation of the time-series segment is calculated as the contact fluctuation degree. Combining the abnormal contact degree, contact deterioration degree, and contact fluctuation degree of each phase branch critical contact, a comprehensive risk score of each phase branch critical contact is obtained. The maximum value of the score is used as the final risk score, and the risk assessment result of the low-voltage switchgear is generated based on the final risk score.

[0007] This invention overcomes the limitations of existing technologies that rely on static threshold determination at a single moment by integrating a contact resistance quantification model optimized for dynamic heat dissipation characteristics, time-series trend feature extraction, and multi-dimensional risk fusion assessment technology. It effectively isolates the impact of load fluctuations, environmental interference, and changes in heat dissipation efficiency. It achieves precise quantification of contact status using normal reference contact resistance, extracts dual dynamic features of contact degradation and contact fluctuation through a time-series sliding window, and combines these with abnormal contact levels to form a comprehensive risk scoring system. The maximum comprehensive risk score of key contacts in each phase branch is taken as the final risk score. Based on this final risk score, graded early warning is implemented, accurately capturing early signs of gradual faults, reducing false alarm rates caused by instantaneous interference, and achieving predictive maintenance throughout the entire lifecycle from post-fault response to pre-fault warning, thereby improving the operational reliability and power supply safety of low-voltage switchgear.

[0008] Preferably, the calculation of the effective contact resistance of the critical contacts in each phase branch includes: In the formula, yes The critical contact of the phase branch is in the first Effective contact resistance at any given moment; It is the first Moment Key contact temperature of phase branch; It is the first Moment Phase load current; It is the first time Dynamic heat dissipation coefficient of key contacts in phase branches; It is a non-zero correction constant; yes The critical contacts of the phase branch circuit and the internal environment of the cabinet are in the first The temperature difference at any given time.

[0009] This invention integrates dynamic heat dissipation coefficient and temperature difference, and combines load current to construct an effective contact resistance calculation formula. It accurately isolates the interference of ambient temperature, heat dissipation efficiency changes and load fluctuations, and realizes the scientific quantification of the contact status of key contacts in each phase branch, providing reliable data support for subsequent abnormal contact degree judgment and comprehensive risk assessment.

[0010] Preferably, the first time Methods for obtaining the dynamic heat dissipation coefficient of key contacts in a phase branch include: In the formula, It is the first time Dynamic heat dissipation coefficient of key contacts in phase branches; It is the steady-state heat dissipation coefficient; This is the rated ambient temperature; This is a correction factor for heat dissipation at ambient temperature. This is the temperature rise heat dissipation correction factor.

[0011] This invention constructs a dynamic heat dissipation coefficient calculation formula by using the steady-state heat dissipation coefficient as a basis, combined with the deviation between the ambient temperature and the rated ambient temperature, and the contact temperature difference, and introducing ambient temperature heat dissipation correction coefficient and temperature rise heat dissipation correction coefficient. It accurately quantifies the dynamic changes in heat dissipation efficiency under different operating conditions, effectively isolates the interference of ambient temperature fluctuations and contact temperature rise on the heat dissipation effect, and provides reliable parameter support for the accurate calculation of effective contact resistance.

[0012] Preferably, the calculation of the comprehensive risk score of the critical contacts of each phase branch includes: In the formula, It is the first Moment Comprehensive risk score of key contacts in the phase branch circuit; It is the first weight; As the second weight; It is the third weight; It is the first Moment The degree of abnormal contact of critical contacts in the phase branch; It is the first Moment The degree of contact degradation of key contacts in the phase branch; It is the first Moment The degree of contact fluctuation of key contacts in the phase branch; This is the function for finding the maximum value.

[0013] This invention constructs a comprehensive risk scoring formula that integrates the first, second, and third weights, combining three core characteristics: abnormal contact degree, contact degradation degree, and contact fluctuation degree. By using a maximum value function to screen effective risk contributions, it accurately quantifies the comprehensive fault urgency of key contacts in each phase branch at each moment, providing a scientific basis for the final risk score calculation and the graded risk assessment of low-voltage switchgear.

[0014] Preferably, obtaining standardized operating status sequence data includes: using the time axis of the sensor with the highest sampling frequency as a reference, interpolating and aligning the data in each dimension to complete timestamp alignment; removing data without timestamps and invalid data that exceeds a reasonable physical range; applying a first-order low-pass digital filter to each data channel independently for noise filtering; and using a linear interpolation method based on time neighborhood to fill in missing values ​​in the filtered data.

[0015] Preferably, the noise filtering using a first-order low-pass digital filter includes: the discrete-time domain relationship of the first-order low-pass digital filter is: ;in, and Each represents the current time. Compared to the previous moment The filtered output value, For the current moment The original sampled values, For indexing time, The filtering smoothing coefficient is... Between 0 and 1.

[0016] Preferably, the step of collecting the effective contact resistance during the normal operation of the low-voltage switchgear and calculating the weighted arithmetic mean to obtain the normal reference contact resistance of the key contacts of each phase branch includes: collecting effective contact resistance data during the steady-state operation phase and under rated load conditions 30 minutes after the low-voltage switchgear is started, removing temperature drift data and interference data from non-rated loads during the start-up and break-in phase, calculating the weighted arithmetic mean of the effective contact resistance data, and using the weighted arithmetic mean as the normal reference contact resistance of the key contacts of the corresponding phase branch.

[0017] Preferably, obtaining the time segment of each phase contact state includes: using Taking the key contact of the phase branch as an example, the construction length is A time-sliding window to capture the first... Time and the past Data on abnormal contact levels at each moment, forming The time segment of the phase contact state is denoted as Exemplary It adapts to the degree of abnormal contact within 1 hour with a sampling interval of 1 minute.

[0018] Preferably, the step of generating the risk assessment result of the low-voltage switchgear based on the final risk score includes: taking the maximum value of the comprehensive risk scores of the critical contacts of each phase branch as the final risk score. ;like The low-voltage switchgear is determined to be in a normal and stable state; if ,and The system determines that the low-voltage switchgear has an early, gradual-type potential hazard and issues a warning; if The system was determined to be in a serious fault state in the low-voltage switchgear and issued an emergency alarm and trip command; among which... These are the preset primary risk threshold and intermediate risk threshold, respectively.

[0019] This invention uses the maximum value of the comprehensive risk score of the key contacts of each phase branch as the final risk score, classifies the operating status level according to the primary risk threshold and the intermediate risk threshold, and combines the positive judgment condition of the degree of contact deterioration to achieve accurate classification of normal stable state, early gradual hidden danger and serious fault state, and issues corresponding non-intervention prompts, early warning prompts, emergency alarms and tripping commands, which not only ensures the safe operation of low-voltage switchgear, but also avoids false alarms caused by instantaneous interference, and provides a clear basis for operation and maintenance decision-making.

[0020] Secondly, the present invention provides a low-voltage switchgear operation data anomaly analysis and processing system, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned low-voltage switchgear operation data anomaly analysis and processing method is implemented.

[0021] By adopting the above technical solution, a computer program is generated from the above-mentioned method for analyzing and processing abnormal operating data of low-voltage switchgear, and stored in the memory so that it can be loaded and executed by the processor. In this way, a terminal device can be made based on the memory and the processor for convenient use.

[0022] The beneficial effects of this invention are as follows: By integrating a contact resistance quantification model optimized for dynamic heat dissipation characteristics, time-series trend feature extraction, and multi-dimensional risk fusion assessment technology, it overcomes the limitations of existing technologies that rely solely on static threshold judgments at a single moment, effectively eliminating the impact of load fluctuations, environmental interference, and changes in heat dissipation efficiency on contact status monitoring. It achieves accurate quantification of contact status through a normal benchmark contact resistance constructed using a weighted arithmetic mean, and extracts dual dynamic features of contact degradation and contact fluctuation using a time-series sliding window. The contact degradation is represented by the least squares fitting slope of the time-series segment, and the contact fluctuation by the standard deviation of the time-series segment. Combined with abnormal contact levels, a multi-dimensional comprehensive risk scoring system is formed. Finally, the maximum value of the comprehensive risk score for each phase branch's key contacts is used to obtain the final risk score. Based on this final risk score, graded early warning is implemented. This not only accurately captures early signs of gradual faults such as screw fretting wear and contact oxidation, but also significantly reduces the false alarm rate caused by instantaneous interference, achieving predictive maintenance throughout the entire lifecycle from post-fault response to pre-fault warning, greatly improving the operational reliability and power supply safety of low-voltage switchgear. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating an abnormal analysis and processing method for low-voltage switchgear operating data according to the present invention;

[0024] Figure 2 It is shown schematically. Schematic diagram of abnormal contact degree of key contacts in a phase branch;

[0025] Figure 3 It is shown schematically. A schematic diagram of the comprehensive risk assessment of key contacts in a phase branch circuit;

[0026] Figure 4 This is a schematic diagram illustrating the final risk score and status determination of a low-voltage switchgear.

[0027] Figure 5 This is a schematic diagram illustrating the comparison of fault detection time between this method and existing methods. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0030] This invention discloses a method for analyzing and processing abnormal operating data of low-voltage switchgear, referring to... Figure 1 This includes steps S1 to S3:

[0031] S1. The operating status sequence data of the low-voltage switchgear is collected in real time by the sensor group pre-installed in the low-voltage switchgear, and pre-processed to obtain standardized operating status sequence data.

[0032] It should be noted that the pre-installed sensor group in the low-voltage switchgear includes: three-phase load current sensors deployed at the busbar inlet and outlet ends, key contact temperature sensors attached to the contact positions of core components such as disconnect switches, and an ambient temperature sensor fixed in the unobstructed area in the middle of the cabinet. This layout ensures the targeted and spatial accuracy of the acquisition of three key data types: load, contact temperature rise, and environmental baseline. However, the raw acquired data suffers from problems such as inconsistent dimensions, high-frequency noise, timing misalignment, and random missing data due to sensor heterogeneity, strong electromagnetic interference, and communication fluctuations. If used directly for analysis, it will seriously interfere with subsequent state quantification and time-series trend feature extraction based on physical models.

[0033] Specifically, real-time data acquisition of the operating status sequence of the low-voltage switchgear includes: three-phase load current, the temperature of key contacts corresponding to each phase current branch, and the ambient temperature inside the cabinet. Specifically, the three-phase load current includes: Phase A load current. B-phase load current C-phase load current The critical contact temperature specifically includes: the critical contact temperature of phase A branch. Key contact temperature of phase B branch C-phase branch critical contact temperature The collected operating status sequence data of the low-voltage switchgear is timestamped and aligned. Using the time axis of the sensor with the highest sampling frequency as the reference, other dimensions of data are interpolated and aligned to ensure that the three-phase load current, key contact temperature, and cabinet ambient temperature at the same moment correspond one-to-one. Data without timestamps caused by communication fluctuations and invalid data with values ​​exceeding reasonable physical ranges are simultaneously removed, such as negative current values ​​or temperatures exceeding the melting point of the core component materials of the low-voltage switchgear.

[0034] Furthermore, to suppress electromagnetic noise while preserving the trend information of the slow change in contact state, a first-order low-pass digital filter is independently used for each data channel, and its discrete-time domain relationship is as follows:

[0035] ;

[0036] in, and Each represents the current time. Compared to the previous moment The filtered output value, For the current moment The original sampled values, For indexing time, Here, the filter smoothing coefficients are: Conditions to be met: The smaller the value, the stronger the filtering effect, but the more obvious the lag. For example, take the filter smoothing coefficient. .

[0037] Specifically, the filtered data undergoes integrity verification. For any missing values ​​detected, a linear interpolation method based on time neighborhood is used to accurately fill them in, ensuring the continuity and integrity of the data in the time dimension. The first-order low-pass digital filter and the linear interpolation method are both well-known technologies. Through the above preprocessing operations, standardized, low-noise, highly complete, and strictly time-aligned operational state sequence data is finally obtained, providing reliable input for subsequent contact state quantification and dynamic risk assessment.

[0038] S2. Based on standardized operating state sequence data, the thermal balance principle of Joule's law, and dynamic heat dissipation characteristics, the abnormal contact degree of key contacts of each phase branch at each moment is obtained.

[0039] It should be noted that the temperature change of critical contacts is affected by the combined effects of the corresponding branch load current thermal effect, the ambient temperature inside the cabinet, the contact state of the contacts themselves, and the dynamic heat dissipation efficiency of the switchgear. The absolute value change of critical contact temperature alone cannot distinguish between normal temperature rise caused by load current fluctuations and abnormal temperature rise caused by contact state deterioration, such as oxidation, loosening, or poor contact. Contact resistance is the essential physical quantity characterizing its contact state. Joule's law clearly defines the quantitative relationship between current thermal effect and resistance and current. Combining the thermal balance principle of dynamic heat dissipation characteristics, a precise quantitative model of phase load current, environmental parameters, and corresponding contact temperature can be established. This model eliminates multiple interferences from load current, ambient temperature, and heat dissipation efficiency, transforming the change of contact resistance into a quantifiable multi-dimensional abnormal contact degree index, thus enabling accurate determination of the abnormality degree of critical contact contact state at each moment.

[0040] Specifically, core parameters are obtained from standardized operating state sequence data, including the A-phase load current at each moment. B-phase load current C-phase load current and the critical contact temperature of phase A branch corresponding to each phase branch. Key contact temperature of phase B branch C-phase branch critical contact temperature and the ambient temperature inside the cabinet Data matching is completed according to the principle of phase-to-phase correspondence, i.e., the load current of phase A. Matching the critical contact temperature of phase A branch Phase B load current Matching the critical contact temperature of phase B branch C-phase load current Matching the critical contact temperature of the C-phase branch For ease of explanation, parameters are set. .

[0041] Furthermore, based on the thermal balance principle of Joule's law, the temperature difference between the critical contact and the cabinet environment is positively correlated with the square of the load current and the actual contact resistance of the critical contact, and negatively correlated with the dynamic heat dissipation coefficient. To eliminate the dual interference of cabinet environment temperature and dynamic heat dissipation efficiency on the critical contact temperature, the temperature difference between the critical contact temperature of each phase branch and the cabinet environment temperature is calculated. For example, the temperature difference between the critical contact temperature and the cabinet environment temperature is calculated. The temperature difference between the critical contact temperature of the phase branch and the ambient temperature inside the cabinet is denoted as: Based on the inherent properties of the key contacts in the low-voltage switchgear, the steady-state heat dissipation coefficient is obtained, denoted as . The room temperature is taken as the rated ambient temperature of the low-voltage switchgear, denoted as ; For example, the value is 25℃; calculate the first... time The dynamic heat dissipation coefficient of the key contacts in the phase branch is expressed by the following formula:

[0042] ;

[0043] In the formula, It is the first time The dynamic heat dissipation coefficient of the key contacts in the phase branch is used to characterize... The actual heat dissipation power of the critical contact of the phase branch under unit temperature rise; It is the steady-state heat dissipation coefficient; This is the rated ambient temperature; This is the ambient temperature heat dissipation correction coefficient, which characterizes the degree of impact on the heat dissipation efficiency of the contacts when the ambient temperature inside the cabinet deviates from the rated ambient temperature. This is the temperature rise heat dissipation correction factor, characterizing the impact of the contact's own temperature rise deviating from the ambient temperature inside the cabinet on the contact's heat dissipation efficiency; since changes in both ambient temperature and contact temperature rise will cause a decrease in heat dissipation efficiency, and the magnitude of the decrease has a boundary, therefore , The value ranges from 0 to 1, and the specific value is determined through experimental calibration based on the switch cabinet structure and contact installation method. For example, , .

[0044] Specifically, effective contact resistance is a core physical quantity used to characterize the contact state of critical contacts. Its dimension is ohms, conforming to the physical definition of resistance, and its numerical change directly reflects the actual change in the contact resistance of the critical contacts; taking the first... Taking time as an example, we will calculate the first... time The effective contact resistance of the critical contacts in a phase branch is given by the following formula:

[0045] ;

[0046] In the formula, yes The critical contact of the phase branch is in the first The effective contact resistance at any given time is used to reflect... The critical contact of the phase branch is in the first The actual contact state at a given moment, its magnitude and The actual contact resistance of the key contacts in the phase branch is positively correlated; It is the first Moment Key contact temperature of phase branch; It is the first Moment Phase load current; It is a non-zero correction constant, with an example value of 10. -6 The unit is ampere squared, and its core function is to avoid When the phase load current is zero, the denominator shows an abnormal zero value, and this magnitude will not have a substantial impact on the calculation result of the effective contact resistance, thus ensuring the accuracy of quantification. It is the first time Dynamic heat dissipation coefficient of key contacts in phase branches; yes The critical contacts of the phase branch circuit and the internal environment of the cabinet are in the first The temperature difference at any given moment only retains the temperature change caused by the heating effect of the key contacts due to their actual contact resistance, eliminating interference from ambient temperature; when The critical contacts of the phase branch circuit and the internal environment of the cabinet are in the first The greater the temperature difference at any given time, the more... Moment The smaller the phase load current, the more important it is to... Moment The greater the effective contact resistance of the key contacts in a phase branch, the greater the effective contact resistance, and vice versa.

[0047] Specifically, to quantitatively determine the degree of abnormal contact of key contacts in each phase branch, the normal reference contact resistance of key contacts in each phase branch is first obtained. During the normal operation of the low-voltage switchgear, such as 30 minutes after startup, the effective contact resistance data of key contacts in each phase branch under the rated load condition of the low-voltage switchgear are collected. Temperature drift data and interference data from non-rated loads during the startup break-in period are removed, and the weighted arithmetic mean is calculated as the normal reference contact resistance of the corresponding phase branch. For example, the normal reference contact resistance of the corresponding phase branch is... The normal reference contact resistance is denoted as The normal reference contact resistance is the effective contact resistance reference value when there is no contact abnormality in the critical contact. The value remains relatively constant and does not change with time.

[0048] Furthermore, based on the effective contact resistance of the critical contacts in each phase branch and the normal reference contact resistance of the corresponding phase, the abnormal contact degree of the critical contacts in each phase branch at each moment is constructed, with the first... Taking time as an example for analysis, The critical contact of the phase branch is in the first The ratio of the effective contact resistance at any given time to the normal reference contact resistance is used as... Abnormal contact degree of critical contacts in phase branches The physical meaning is the first At this moment The degree of deviation of the current actual contact resistance of the critical contacts in the phase branch from the normal, abnormal state; when When, it indicates The actual contact resistance of the critical contacts in the phase branch is consistent with the normal, non-abnormal state, indicating no contact abnormalities; when When, it indicates The actual contact resistance of the critical contacts in the phase branch is increased compared to the normal, unaffected state. The larger the value, the higher the degree of contact abnormality of the critical contacts, and the more severe the oxidation and loosening of the contacts. Time, characterization The actual contact resistance of the key contacts in the phase branch is 50% higher than that under normal conditions, indicating a serious contact abnormality.

[0049] For example, Figure 2 For the present invention A schematic diagram illustrating the abnormal contact degree of key contacts in a phase branch; whereby, Figure 2 By drawing The evolution curves of abnormal contact degree of critical contacts in phase branches over time cover three curves: abnormal contact degree of phase A, abnormal contact degree of phase B, and abnormal contact degree of phase C. A normal baseline is simultaneously marked, intuitively reflecting the dynamic changes in the contact state of critical contacts in each phase branch: In the early stage of normal operation, the abnormal contact degree of each phase is stable near the normal baseline, indicating that the contact state is within the normal range; as time progresses, the abnormal contact degree of each phase gradually deviates from the normal baseline and continues to rise, clearly showing the deterioration process of the contact state of critical contacts in different phase branches. Simultaneously, the differences in the deterioration rate of the contact state of each phase can be intuitively compared. This demonstrates that the method can accurately quantify the contact state of critical contacts in each phase branch, effectively distinguish between the normal operation state and the deterioration state of the contacts, and clearly capture the dynamic evolution trend of the contact state of each phase. This provides accurate and reliable basic data support for subsequent calculation of comprehensive risk scores and risk assessment of low-voltage switchgear.

[0050] S3. Based on the abnormal contact degree and time sequence feature extraction of the key contacts of each phase branch at each time, the comprehensive abnormal risk assessment result of the low-voltage switchgear is obtained.

[0051] It should be noted that while the obtained abnormal contact degree can quantify the physical contact state at the current moment, for early latent faults in low-voltage switchgear, such as the slow increase in contact resistance caused by screw fretting wear, it is difficult to make accurate early warnings based solely on the magnitude of the value at a single moment, and it is also highly susceptible to instantaneous interference leading to false alarms. The existing methods mentioned in the background technology lack perception of the time evolution pattern. Therefore, this step introduces the time-series sliding window technology to extract the evolution trend characteristics representing the fault development rate and the fluctuation stability characteristics representing the contact stability from the time series of abnormal contact degree, upgrading the static threshold judgment to dynamic trend judgment, thereby realizing early identification of gradual faults and predictive maintenance throughout the entire life cycle.

[0052] Specifically, with Taking the key contact of the phase branch as an example, the construction length is A time-sliding window to capture the first... Time and the past The degree of abnormal contact at each moment forms The time segment of the phase contact state is denoted as Exemplary It adapts to the degree of abnormal contact within one hour with a sampling interval of 1 minute; it uses the least squares method to... Linear fitting is performed on the data within the time segment of the phase contact state, and the slope of the fitted line is extracted as the first... time The degree of contact degradation of the critical contacts in a phase branch is denoted as... The physical meaning lies in reflecting The rate of deterioration of the contact condition of the critical contacts in the phase branch, when Furthermore, when the resistance continues to increase, it indicates that the contact resistance is showing an irreversible upward trend. Even if the current abnormal contact level has not yet reached the serious fault threshold, the gradual fault signs of contact aging can be identified in advance.

[0053] Furthermore, The standard deviation of the data within the time segment of the phase contact state is used as the first... time The degree of contact fluctuation of the critical contacts in the phase branch is denoted as... The physical meaning is to reflect the mechanical stability of the contact interface, when When it increases abnormally, it indicates Micro-motion or intermittent poor contact of key contacts in a phase branch under vibration or electrodynamic action is a typical early characteristic of loose connection.

[0054] Specifically, based on the degree of abnormal contact, the degree of contact degradation, and the degree of contact fluctuation at each time point, a comprehensive risk score is obtained for each time point; the risk score for the [missing information] time point is then calculated. Moment The comprehensive risk score for the critical contacts of the phase branch is expressed by the following formula:

[0055] ;

[0056] In the formula, It is the first Moment Comprehensive risk score of key contacts in the phase branch circuit; The first weight corresponds to the weight of the degree of abnormal contact; The second weight corresponds to the weight of the degree of contact degradation; The third weight corresponds to the weight of the degree of contact volatility; It is the first Moment The degree of abnormal contact of critical contacts in the phase branch; It is the first Moment The degree of contact degradation of key contacts in the phase branch; It is the first Moment The degree of contact fluctuation of key contacts in the phase branch; The function to find the maximum value; function The aim is to extract deviations that exceed the normal baseline, i.e., those greater than 1. If the function is empty, then the contribution is 0; The aim is to focus only on deteriorating trends with a positive slope, ignoring improving trends with a negative slope.

[0057] Among them, when the first Moment The greater the degree of abnormal contact, contact deterioration, and contact fluctuation of the critical contacts in the phase branch, the more severe the impact. Moment The higher the overall risk score of the critical contact of the branch, the greater the risk score, and vice versa.

[0058] It should be noted that the first weight, the second weight, and the third weight must satisfy a specific logical relationship: ,and The physical basis for setting this weighting relationship is as follows: The first weight describes the severity of the current state, i.e., whether the absolute value of the contact resistance exceeds the standard, which directly determines whether the equipment is at risk of immediate burnout, hence its highest weight; the second weight describes the rate of fault development, i.e. how quickly the condition worsens, although it represents future risk, its urgency is less than the current absolute value exceeding the standard, hence its middle weight; the third weight describes the instability of the state, although it can reflect signs of loosening, it is also susceptible to transient electromagnetic interference, hence its lowest weight to reduce the false alarm rate; for example, setting... .

[0059] For example, Figure 3 For the present invention A schematic diagram illustrating the comprehensive risk assessment of key contacts in a phase branch circuit; among which, Figure 3 By drawing The curves showing the overall risk scores of critical contacts in each phase branch over time include three curves: Phase A, Phase B, and Phase C. Primary and intermediate risk thresholds are also marked, visually reflecting the dynamic evolution of the overall risk of critical contacts in each phase branch. In the early, normal operation phase, the overall risk scores of most phases remain stable below the primary risk threshold, indicating that the contacts are in a normal and stable operating state. As time progresses, the overall risk scores of each phase gradually fluctuate and rise, with some phases' scores exceeding the primary risk threshold first, corresponding to contacts entering a warning state. Subsequently, the scores of each phase continue to climb, with some phases further exceeding the intermediate risk threshold, corresponding to contacts entering a severe fault state. This also visually distinguishes the rate of increase and risk level differences of the overall risk of critical contacts in different phase branches. This demonstrates that the method can accurately quantify the overall risk level of critical contacts in each phase branch, effectively classify the normal and stable operating state, warning state, and severe fault state of the contacts, and clearly capture the dynamic evolution trend of the overall risk of each phase, providing accurate and reliable technical support for the graded early warning and maintenance decisions of low-voltage switchgear.

[0060] further, The phases are A, B, and C. The first... time The maximum value among the three comprehensive risk scores of the critical contact of the phase branch is used as the first... The final risk score for the constant operating status of the low-voltage switchgear is denoted as... The operating status of the low-voltage switchgear is determined based on the final risk score: if If the low-voltage switchgear is determined to be in a normal and stable state, no intervention is required; if ,and The system determined that the low-voltage switchgear had an early, gradual-type potential hazard, issued an early warning, and advised maintenance personnel to pay close attention during the next maintenance cycle; if The system determines that the low-voltage switchgear is in a serious fault state, issues an emergency alarm, and sends a trip command to the control system to trigger the trip protection logic and prevent the accident from escalating; among which... These are preset primary risk thresholds and intermediate risk thresholds, respectively. For example, they are set as follows: .

[0061] For example, Figure 4 This is a schematic diagram illustrating the final risk assessment and status determination of the low-voltage switchgear of the present invention; wherein, Figure 4 By plotting the curve of the final risk score of low-voltage switchgear over time, and simultaneously marking the primary and intermediate risk thresholds, and using different colored areas to distinguish between normal, warning, and emergency states, the dynamic evolution and state switching process of low-voltage switchgear operation risk is intuitively reflected: In the early stage, the final risk score remains stable below the primary risk threshold, corresponding to the normal state, indicating that the switchgear is in a safe and stable operating state; as time progresses, the final risk score gradually rises and exceeds the primary risk threshold, corresponding to the warning state, indicating that the switchgear operation risk has entered a stage requiring close attention; subsequently, the final risk score continues to climb and exceeds the intermediate risk threshold, corresponding to the emergency state, indicating that the switchgear operation risk has reached a level requiring immediate action. This presentation demonstrates that this method can achieve clear classification and determination of the low-voltage switchgear operation status based on the final risk score, accurately capturing the entire process of risk from normal to gradual deterioration, providing clear and intuitive status basis for switchgear operation and maintenance decisions, and effectively supporting targeted handling under different risk levels.

[0062] For example, Figure 5 This is a schematic diagram comparing the fault detection time of the method of the present invention with that of existing methods; wherein, Figure 5By plotting the state changes of this method and existing methods over time, and simultaneously marking the first warning time and first emergency time of this method, as well as the first alarm time of the existing method, the three operating states of this method (normal, warning, and emergency) are distinguished from the two operating states of the existing method (normal and alarm). This visually reflects the difference in fault detection rhythm between the two methods: this method enters the warning state at 620 seconds, while the existing method does not enter the alarm state until 807 seconds. Subsequently, this method enters the emergency state at 961 seconds, while the existing method has no corresponding stage division. This demonstrates that this method has an earlier fault warning capability than the existing method, and can identify risks in advance when the fault is relatively minor, allowing maintenance personnel more time to handle the situation. The existing method lacks a warning stage and can only trigger an alarm when the fault is more serious. This shows that the fault detection timeliness of this method is better and more conducive to avoiding the occurrence of serious faults in advance.

[0063] This invention also discloses a low-voltage switchgear operation data anomaly analysis and processing system, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, a low-voltage switchgear operation data anomaly analysis and processing method according to the present invention is implemented.

[0064] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

Claims

1. A method for analyzing and processing abnormal operating data of low-voltage switchgear, characterized in that, include: Real-time acquisition and preprocessing of low-voltage switchgear operation status sequence data to obtain standardized operation status sequence data; Based on the thermal balance principle of Joule's law and combined with dynamic heat dissipation characteristics, the effective contact resistance of the key contacts in each phase branch is calculated using standardized operating state sequence data, including three-phase load current, critical contact temperature, and cabinet ambient temperature, to satisfy the following: ； yes The critical contact of the phase branch is in the first Effective contact resistance at any given moment; It is the first Moment Key contact temperature of phase branch; It is the first Moment Phase load current; It is the first time Dynamic heat dissipation coefficient of key contacts in phase branches; It is a non-zero correction constant; yes The critical contacts of the phase branch circuit and the internal environment of the cabinet are in the first Temperature difference over time; satisfy: ； It is the steady-state heat dissipation coefficient; This is the rated ambient temperature; This is a correction factor for heat dissipation at ambient temperature. This is a correction factor for heat dissipation in response to temperature rise. The ambient temperature inside the cabinet; The effective contact resistance during the normal operation of the low-voltage switchgear is collected and the weighted arithmetic mean is calculated to obtain the normal reference contact resistance of the key contacts of each phase branch; the abnormal contact degree of the key contacts of each phase branch at each time is obtained by the ratio of the effective contact resistance of the key contacts of each phase branch to the normal reference contact resistance of the corresponding phase. Based on the abnormal contact degree of each phase branch key contact at each time point, a time-series sliding window is constructed to obtain the time-series segments of the contact state of each phase; the time-series segments are fitted using the least squares method, and the fitting slope is used as the contact deterioration degree, and the standard deviation of the time-series segments is calculated as the contact fluctuation degree; combining the abnormal contact degree, contact deterioration degree, and contact fluctuation degree of each phase branch key contact, a comprehensive risk score of each phase branch key contact is obtained, and its maximum value is used as the final risk score, and the risk assessment result of the low-voltage switchgear is generated based on the final risk score; The overall risk score is: ； It is the first Moment Comprehensive risk score of key contacts in the phase branch circuit; It is the first weight; As the second weight; It is the third weight; It is the first Moment The degree of abnormal contact of critical contacts in the phase branch; It is the first Moment The degree of contact degradation of key contacts in the phase branch; It is the first Moment The degree of contact fluctuation of key contacts in the phase branch; This is the function for finding the maximum value.

2. The method for analyzing and processing abnormal operating data of a low-voltage switchgear according to claim 1, characterized in that, The process of obtaining standardized operational status sequence data includes: using the time axis of the sensor with the highest sampling frequency as a reference, interpolating and aligning the data in each dimension to complete timestamp alignment; removing data without timestamps and invalid data that exceeds a reasonable physical range; applying a first-order low-pass digital filter to each data channel independently for noise filtering; and using a linear interpolation method based on time neighborhood to fill in missing values ​​in the filtered data.

3. The method for analyzing and processing abnormal operating data of a low-voltage switchgear according to claim 2, characterized in that, The application of a first-order low-pass digital filter for noise filtering includes: the discrete-time domain relationship of the first-order low-pass digital filter is as follows: ； in, and Each represents the current time. Compared to the previous moment The filtered output value, For the current moment The original sampled values, For indexing time, The filtering smoothing coefficient is... Between 0 and 1.

4. The method for analyzing and processing abnormal operating data of a low-voltage switchgear according to claim 1, characterized in that, The method of collecting the effective contact resistance during the normal operation of the low-voltage switchgear and calculating the weighted arithmetic mean to obtain the normal reference contact resistance of the key contacts of each phase branch includes: Collect effective contact resistance data of the low-voltage switchgear during steady-state operation and under rated load conditions 30 minutes after startup. Remove temperature drift data and interference data from non-rated loads during the startup break-in period. Calculate the weighted arithmetic mean of the effective contact resistance data and use the weighted arithmetic mean as the normal reference contact resistance of the critical contacts of the corresponding phase branch.

5. The method for analyzing and processing abnormal operating data of a low-voltage switchgear according to claim 1, characterized in that, The time-series segments for obtaining the contact states of each phase include: for The key contact of the phase branch has a construction length of [length missing]. A time-sliding window to capture the first... Time and the past Data on abnormal contact levels at each moment, forming The time segment of the phase contact state is denoted as It adapts to the degree of abnormal contact within 1 hour with a sampling interval of 1 minute.

6. The method for analyzing and processing abnormal operating data of a low-voltage switchgear according to claim 1, characterized in that, The risk assessment results for low-voltage switchgear generated based on the final risk score include: The maximum value among the comprehensive risk scores of the critical contacts of each phase branch is taken as the final risk score. ;like The low-voltage switchgear is determined to be in a normal and stable state; if ,and The system determines that the low-voltage switchgear has an early, gradual-type potential hazard and issues a warning; if The system was determined to be in a serious fault state in the low-voltage switchgear and issued an emergency alarm and trip command; among which... These are the preset primary risk threshold and intermediate risk threshold, respectively.

7. A system for analyzing and processing abnormal operating data of low-voltage switchgear, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a method for analyzing and processing abnormal operating data of a low-voltage switchgear according to any one of claims 1-6 is implemented.

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