A method for quality assessment of fault arc circuit breakers

Abstract

This invention discloses a method for quality assessment of fault arc circuit breakers, belonging to the field of electrical safety testing technology. The method includes acquiring a fault arc reference signal and a background noise reference signal, performing superposition processing to generate a composite test signal, which is then applied to the fault arc circuit breaker under test. The circuit breaker's response signal is collected and decoupled to separate the arc characteristic components and noise suppression residuals, calculating the arc identification index and noise suppression index. Based on the arc identification index and noise suppression index, a weighted fusion algorithm is used to perform a fusion calculation to obtain a comprehensive quality assessment score. A quality assessment report is generated based on the comprehensive quality assessment score. By applying the composite test signal to the circuit breaker under test and decoupling its response signal to quantify the arc identification and noise suppression, a deep quantitative assessment of the circuit breaker's signal processing capabilities can be achieved.

Description

Technical Field

[0001] This invention relates to the field of electrical safety testing technology, and in particular to a method for quality assessment of fault arc circuit breakers. Background Technology

[0002] An arc fault circuit interrupter (AFS), also known as an arc fault circuit interrupter (AFS), is an intelligent protective electrical device used to detect dangerous arc faults in a circuit and promptly disconnect the power supply. Arc faults are one of the main causes of electrical fires; therefore, the detection accuracy and operational reliability of AFS are crucial for ensuring electrical safety. A comprehensive and effective quality assessment is a prerequisite for ensuring that it fulfills its intended protective function.

[0003] In existing technologies, the quality assessment of fault arc circuit breakers typically employs functional testing methods. These methods mainly rely on relevant standards, applying a standard fault arc signal to the circuit breaker under test to verify whether it can accurately trip within a specified time; simultaneously, specific interference signals are applied to verify whether unnecessary false tripping will occur. The assessment conclusion is often a binary judgment of "qualified" or "unqualified".

[0004] However, existing functional testing methods have significant limitations. They can only evaluate the final operating result of the circuit breaker, failing to delve into its internal signal processing and reveal the underlying reasons for its performance differences. This evaluation method is rather coarse, unable to quantify the performance margin differences between different products that pass the test, and also unable to provide specific fault attributions and improvement directions for poorly performing products, resulting in insufficient depth and refinement in the evaluation. Summary of the Invention

[0005] To address the aforementioned issues, this invention provides a method for evaluating the quality of fault arc circuit breakers. By applying a composite test signal to the circuit breaker under test and decoupling its response signal to quantify the arc identification and noise suppression, a deep quantitative evaluation of the circuit breaker's signal processing capabilities can be achieved.

[0006] The above objectives can be achieved through the following approach: A method for quality assessment of a fault arc circuit breaker includes: acquiring a fault arc reference signal and a background noise reference signal; superimposing the fault arc reference signal and the background noise reference signal to generate a composite test signal; applying the composite test signal to the fault arc circuit breaker under test and acquiring the circuit breaker response signal output from the internal circuit of the fault arc circuit breaker under test; performing signal decoupling processing on the circuit breaker response signal to separate the arc characteristic component and the noise suppression residual; calculating an arc identification index based on the arc characteristic component and the fault arc reference signal, and calculating a noise suppression index based on the noise suppression residual and the background noise reference signal; performing a weighted fusion algorithm to calculate a comprehensive quality assessment score based on the arc identification index and the noise suppression index; and generating a quality assessment report based on the comprehensive quality assessment score.

[0007] Optionally, generating the composite test signal includes: acquiring a fault arc reference signal and a background noise reference signal; acquiring a signal-to-noise ratio (SNR) adjustment parameter for quantifying the relative intensity of the fault arc signal and the background noise; calculating the energy ratio between the fault arc reference signal and the background noise reference signal based on the SNR adjustment parameter; adjusting the background noise reference signal based on the energy ratio; and superimposing the adjusted signal with the fault arc reference signal to synthesize the composite test signal.

[0008] Optionally, the step of performing signal decoupling processing on the circuit breaker response signal to separate the arc characteristic component and the noise suppression residual includes: performing multi-scale decomposition on the circuit breaker response signal to obtain time-frequency coefficients in different frequency bands; determining the arc characteristic frequency band based on the frequency band energy distribution law of the fault arc reference signal; reconstructing the arc characteristic component from the portion of the time-frequency coefficients belonging to the arc characteristic frequency band; and subtracting the arc characteristic component from the circuit breaker response signal to obtain the noise suppression residual.

[0009] Optionally, the step of calculating the arc identification index based on the arc characteristic components and the fault arc reference signal, and calculating the noise suppression index based on the noise suppression residual and the background noise reference signal, includes: calculating the signal energy of the arc characteristic components to obtain a first energy value; calculating the signal energy of the fault arc reference signal to obtain a second energy value, and using the ratio of the first energy value to the second energy value as the arc identification index; calculating the signal energy of the noise suppression residual to obtain a third energy value; and calculating the signal energy of the background noise reference signal to obtain a fourth energy value, and using the ratio of the third energy value to the fourth energy value as the noise suppression index.

[0010] Optionally, obtaining the comprehensive quality assessment score includes: while applying the composite test signal, monitoring the tripping action of the tested fault arc circuit breaker and recording the tripping time to obtain the response time parameter; and based on the preset dynamic weighting coefficient, performing a fusion calculation on the arc identification index, the noise suppression index, and the response time parameter to obtain the comprehensive quality assessment score.

[0011] Optionally, the method further includes: obtaining the application scenario type parameter corresponding to the faulty arc circuit breaker under test; and dynamically adjusting the dynamic weighting coefficient according to the application scenario type parameter.

[0012] Optionally, generating a quality assessment report based on the comprehensive quality assessment score includes: retrieving historical assessment data of fault arc circuit breakers of the same model or batch as the tested fault arc circuit breaker from a preset historical quality assessment database; comparing and analyzing the comprehensive quality assessment score with the historical assessment data to generate a horizontal performance comparison analysis result; and integrating the horizontal performance comparison analysis result with the comprehensive quality assessment score to generate the quality assessment report.

[0013] Optionally, the method further includes: performing fault attribution analysis based on the values ​​of the arc identification index and the noise suppression index to generate fault attribution analysis results; and generating diagnostic suggestion information based on the fault attribution analysis results and integrating it into the quality assessment report.

[0014] Optionally, the method further includes: obtaining the model information of the tested faulty arc circuit breaker; associating the comprehensive quality assessment score, the arc identification index, the noise suppression index with the model information to generate associated data; and storing the associated data in the quality assessment historical database.

[0015] Based on the same inventive concept, this invention also provides a quality assessment system for fault arc circuit breakers. The system includes: a test signal generation module for acquiring a fault arc reference signal and a background noise reference signal, and superimposing the fault arc reference signal and the background noise reference signal to generate a composite test signal; a response signal acquisition module for applying the composite test signal to the fault arc circuit breaker under test and acquiring the circuit breaker response signal output from the internal circuit of the fault arc circuit breaker under test; a signal decoupling processing module for performing signal decoupling processing on the circuit breaker response signal to separate the arc characteristic component and the noise suppression residual; a performance calculation module for calculating an arc identification index based on the arc characteristic component and the fault arc reference signal, and calculating a noise suppression index based on the noise suppression residual and the background noise reference signal; a comprehensive evaluation module for performing a weighted fusion calculation based on the arc identification index and the noise suppression index to obtain a comprehensive quality assessment score; and a report generation module for generating a quality assessment report based on the comprehensive quality assessment score.

[0016] Compared with the prior art, the present invention has the following advantages: 1. This invention constructs a composite test signal that includes a fault arc reference signal and a background noise reference signal, and introduces a signal-to-noise ratio adjustment parameter to achieve standardized and quantitative control of the test environment; it ensures that each evaluation is carried out under uniform and repeatable conditions, eliminates evaluation errors caused by inconsistencies in test signals, and improves the objectivity, accuracy and comparability of evaluation results. 2. This invention separates the circuit breaker response signal into arc characteristic components and noise suppression residuals, and calculates two independent quantitative indicators, arc identification and noise suppression, which can evaluate the fault identification capability and anti-interference capability of the circuit breaker from the root of signal processing, and realize a deep insight into the intrinsic performance of the product. 3. This invention weights and fuses internal signal processing performance indicators with external response time parameters, and can also dynamically adjust the weight coefficients according to different application scenario types. This makes the evaluation conclusions not only comprehensive, but also closely aligned with actual application needs, providing a basis for product selection and performance optimization in different scenarios and enhancing the practical value of the evaluation results. 4. By introducing a historical database of quality assessment, this invention enables vertical traceability and horizontal comparison of assessment results. By comparing and analyzing current assessment results with historical data and combining them with fault attribution analysis to generate diagnostic suggestions, the assessment report not only provides a performance score but also becomes a technical document with diagnostic and improvement guidance significance, thus constructing an assessment knowledge system that can self-improve and continuously optimize.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a method for evaluating the quality of a fault arc circuit breaker according to an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of the generation of composite test signals according to an embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of the structure of a fault arc circuit breaker quality assessment system according to an embodiment of the present invention.

[0022] Figure 4 This is a comparison chart of key performance indicators of embodiments of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Reference Figure 1 One embodiment of the present invention proposes a method for quality assessment of fault arc circuit breakers. By applying a composite test signal to the circuit breaker under test and decoupling its response signal to quantify the arc identification degree and noise suppression degree, a deep quantitative assessment of the circuit breaker's signal processing capability can be achieved.

[0025] The method described in this embodiment specifically includes: Acquire the fault arc reference signal and the background noise reference signal, and superimpose the fault arc reference signal and the background noise reference signal to generate a composite test signal; The composite test signal is applied to the fault arc circuit breaker under test, and the circuit breaker response signal output by the internal circuit of the fault arc circuit breaker under test is collected. The circuit breaker response signal is decoupled to separate the arc characteristic component and the noise suppression residual. An arc identification index is calculated based on the arc characteristic components and the fault arc reference signal, and a noise suppression index is calculated based on the noise suppression residual and the background noise reference signal. Based on the arc identification index and the noise suppression index, a weighted fusion algorithm is used to perform a fusion calculation to obtain a comprehensive quality assessment score. A quality assessment report is generated based on the comprehensive quality assessment score.

[0026] This invention first simulates a controllable and representative complex electrical operating environment by actively synthesizing a composite test signal that includes a standardized fault arc reference signal and a background noise reference signal. The fault arc circuit breaker under test is placed under these standardized test conditions, and the circuit breaker response signal from its internal signal processing stage is collected. This response signal is then decoupled, decomposing it into an arc characteristic component reflecting effective signal processing capability and a noise suppression residual characterizing interference suppression level. Subsequently, by comparing these two separated components with the original reference signal, two independent performance indicators—arc recognition and noise suppression—are quantified and calculated. Finally, these two performance indicators are weighted and fused to form a comprehensive quality assessment score, which is used to generate the final evaluation report, thereby achieving a deep quantitative assessment of the circuit breaker's internal signal processing capability.

[0027] This invention enhances the objectivity, precision, and depth of quality assessment for arc fault circuit breakers (AFS). It overcomes the limitations of traditional functional testing, which only provides a binary conclusion of pass or fail. By offering quantified comprehensive evaluation scores and independent performance indicators, it enables precise comparisons of performance differences between different products. It reveals performance shortcomings at the root of signal processing, clarifying whether the issue lies in insufficient fault identification sensitivity or defects in noise immunity. This provides diagnostic information and directional guidance for product design optimization and quality improvement. Standardized test signals and analysis processes ensure high repeatability and fairness of the evaluation results, making it possible to establish a unified industry performance evaluation benchmark and ultimately achieve quality assessment of AFS.

[0028] Optionally, generating the composite test signal includes: Acquire the fault arc reference signal and the background noise reference signal; Obtain the signal-to-noise ratio adjustment parameters used to quantify the relative intensity of the fault arc signal and the background noise; Based on the signal-to-noise ratio adjustment parameters, calculate the energy ratio between the fault arc reference signal and the background noise reference signal; The background noise reference signal is adjusted based on the energy ratio, and the adjusted signal is superimposed with the fault arc reference signal to synthesize a composite test signal.

[0029] Specifically, such as Figure 2 As shown, firstly, two basic signals need to be obtained from a pre-set signal library: a fault arc reference signal and a background noise reference signal. The former is standardized data characterizing the current or voltage waveforms when a typical series or parallel fault arc occurs, while the latter simulates non-faulty electromagnetic interference generated by various electrical devices in a normal power environment. Next, to quantify the rigor of the test, a signal-to-noise ratio (SNR) adjustment parameter needs to be obtained. This parameter is a preset value designed to define the relative strength of the fault arc reference signal and the background noise reference signal in the final synthesized composite test signal, thereby simulating different levels of operating environments from low noise to strong interference. Based on the obtained SNR adjustment parameter, the energy ratio required for this SNR is calculated. This process uses an adjustment coefficient. To implement this specifically, the calculation formula is as follows: ; in, The adjustment coefficient to be determined; The total energy of the pre-calculated fault arc reference signal; The total energy of the background noise reference signal; This is the signal-to-noise ratio (SNR) adjustment parameter, measured in decibels (dB). The total energy of the signal can be obtained by integrating or summing the square of the signal amplitude over its entire time length. This adjustment coefficient... The calculation results directly reflect the required energy ratio. Finally, based on this energy ratio, the calculated adjustment coefficient is multiplied by each sampling point of the background noise reference signal to obtain the adjusted noise signal. This adjusted noise signal is then superimposed point-by-point with the original fault arc reference signal in the time domain to finally synthesize a composite test signal for subsequent testing.

[0030] Optionally, the step of performing signal decoupling processing on the circuit breaker response signal to separate the arc characteristic component and the noise suppression residual includes: The circuit breaker response signal is decomposed into multiple scales to obtain time-frequency coefficients in different frequency bands; Based on the frequency band energy distribution pattern of the fault arc reference signal, the characteristic frequency band of the arc is determined; The portion of the time-frequency coefficients belonging to the arc characteristic frequency band is reconstructed to obtain the arc characteristic components. The noise suppression residual is obtained by subtracting the arc characteristic component from the circuit breaker response signal.

[0031] Specifically, the composite test signal generated in the preceding steps is first applied to the fault arc circuit breaker under test, and the circuit breaker response signal is acquired at key nodes of its internal signal processing circuit, such as the output of a filter or feature extraction unit. This signal is the internal electrical signal response of the circuit breaker to an input that mixes the fault arc reference signal and the background noise reference signal. Subsequently, multi-scale decomposition is performed on the circuit breaker response signal. Multi-scale decomposition is an advanced signal processing technique, such as wavelet transform or wavelet packet transform, which can decompose the signal into different frequency scales while preserving time information, thereby obtaining a series of time-frequency coefficients in different frequency bands. These coefficients matrix-wise describe the frequency components of the signal at various times. Before this, based on the spectral characteristics of the fault arc reference signal itself, the specific frequency bands in which its energy is mainly concentrated need to be determined by performing the same energy analysis; these frequency bands are defined as arc characteristic frequency bands. Next, based on the determined arc characteristic frequency bands, the time-frequency coefficients obtained from the decomposition of the circuit breaker response signal are screened. Only time-frequency coefficients belonging to the arc characteristic frequency band are retained, while coefficients in other frequency bands are set to zero or discarded. These filtered coefficients are then used for signal reconstruction, i.e., an inverse transform process, to synthesize a new time-series signal. This signal is the arc characteristic component, which theoretically represents the successfully identified and processed fault arc portion of the circuit breaker response signal. Finally, to obtain the noise suppression residual, the reconstructed arc characteristic component is subtracted from the original circuit breaker response signal, as calculated below: , in, Represents the noise suppression residual that varies over time. The acquired raw circuit breaker response signal, It is the arc characteristic component obtained from the reconstruction. This subtraction operation is performed point by point in the time domain, and the resulting difference signal is the noise suppression residual, which contains the background noise that the circuit breaker under test could not effectively filter out, as well as the distortion that may be introduced during signal processing.

[0032] Optionally, the step of calculating the arc identification index based on the arc characteristic components and the fault arc reference signal, and calculating the noise suppression index based on the noise suppression residual and the background noise reference signal, includes: Calculate the signal energy of the characteristic components of the electric arc to obtain a first energy value; The signal energy of the fault arc reference signal is calculated to obtain a second energy value, and the ratio of the first energy value to the second energy value is used as the arc identification index. Calculate the signal energy of the noise suppression residual to obtain the third energy value; The signal energy of the background noise reference signal is calculated to obtain a fourth energy value, and the ratio of the third energy value to the fourth energy value is used as a noise suppression index.

[0033] Specifically, this step aims to transform the signal components separated in the previous step into key indicators that can quantify and evaluate the performance of the arc fault circuit breaker. This process consists of two parallel computational tasks, corresponding to the evaluation of arc identification capability and noise suppression capability, respectively. First, to calculate the arc identification index, the signal energy of the arc characteristic components needs to be calculated. The signal energy is usually obtained by integrating or summing the square of the signal amplitude over the entire signal duration. The value obtained from this calculation is the first energy value. At the same time, the same signal energy calculation is performed on the fault arc reference signal, which serves as an ideal reference, to obtain the second energy value. The arc identification index is defined as the ratio of the first energy value to the second energy value, and its calculation formula is: , in, This is an indicator of arc recognition. It is the signal energy of the calculated characteristic components of the electric arc, i.e., the first energy value; The first energy value is the signal energy of the calculated fault arc reference signal, i.e., the second energy value. Both energy values ​​are obtained by summing the squares of their respective instantaneous amplitudes. Next, a similar method is used to calculate the noise suppression index. The signal energy of the noise suppression residual is calculated to obtain the third energy value. Then, the signal energy of the original injected background noise reference signal is calculated to obtain the fourth energy value. The noise suppression index is determined by the ratio of the third energy value to the fourth energy value, calculated using the following formula: , in, This is an indicator of noise suppression performance. It is the signal energy of the noise suppression residual obtained from the calculation, i.e., the third energy value; This is the calculated signal energy of the background noise reference signal, also known as the fourth energy value. This indicator reflects the ratio of noise energy that the circuit breaker under test failed to suppress and remains in its internal signal to the initial input noise energy.

[0034] Optionally, the obtained comprehensive quality assessment score includes: While applying the composite test signal, the tripping action of the tested fault arc circuit breaker is monitored and the tripping time is recorded to obtain the response time parameter; Based on preset dynamic weighting coefficients, the arc identification index, the noise suppression index, and the response time parameter are fused and calculated to obtain a comprehensive quality assessment score.

[0035] Specifically, the goal of this step is to integrate the multiple independent performance indicators obtained from the previous steps into a single comprehensive quality assessment score to provide a holistic evaluation conclusion. This process introduces a key physical quantity: the response time parameter. While applying the composite test signal to the circuit breaker under test (CBRT) with the fault arc, the on / off state of its main contacts needs to be monitored in real time. The moment the test begins is recorded as the start time. When the CBRT correctly identifies the fault arc and executes its protection function, i.e., when a tripping action occurs, this moment is recorded as the tripping moment. The response time parameter is the time difference between the tripping moment and the start time. To achieve the integration of multi-dimensional performance, each indicator needs to be normalized first. This is because the arc identification rate and noise suppression rate indicators are dimensionless ratios, while the response time parameter has a time dimension; directly weighting them does not conform to physical laws. Therefore, the response time parameter needs to be transformed into a standardized score through a preset mapping function; for example, the shorter the response time, the higher the score. Subsequently, based on a set of preset dynamic weighting coefficients, the arc identification index, the transformed noise suppression index, and the standardized response time score are weighted and fused together. The fusion calculation formula can be expressed as follows: , in, This is the final comprehensive quality assessment score; It is a normalized arc identification index; It is a noise suppression index that has been normalized and positively evaluated, for example, by subtracting the original index value from 1. It is a standardized score obtained by converting response time parameters; , , These are dynamic weighting coefficients representing arc recognition, noise suppression, and response time, respectively. They are all preset values ​​and their sum is usually 1, used to adjust the importance of different performance dimensions in the total score.

[0036] Optionally, the method further includes: Obtain the application scenario type parameters corresponding to the faulty arc circuit breaker under test; The dynamic weighting coefficient is dynamically adjusted based on the application scenario type parameter.

[0037] Specifically, this step introduces scenario adaptability into the calculation process of the comprehensive quality assessment score, enabling it to dynamically adjust according to the intended use of the tested arc fault circuit breaker. Before performing the weighted fusion calculation, a key input is first obtained: the application scenario type parameter corresponding to the tested arc fault circuit breaker. This parameter is a predefined identifier, such as "residential," "commercial," "industrial," or "data center," which characterizes the typical electrical environment in which the circuit breaker will be deployed and its specific protection performance requirements. Subsequently, the system queries or matches a pre-defined weight strategy database based on the obtained application scenario type parameter. This database stores the mapping relationship between different application scenarios and multiple sets of dynamic weight coefficients. For example, in scenarios like "data center," where power supply continuity is extremely important, the weight strategy assigns a higher weight to the noise suppression index to minimize false tripping caused by interference; while in "industrial" scenarios, the weights of arc identification and response time may be emphasized simultaneously to address complex fault modes and rapid protection requirements. This adjustment process can be formally described as follows: , in, The input is the application scenario type parameter; This represents a function that searches and matches data from a weighted strategy database. It is the final output set of dynamic weight coefficients. Once a set of dynamic weight coefficients matching a specific application scenario is determined, the system will use them to replace the default or general weights, thereby completing the fusion calculation of the comprehensive quality assessment score.

[0038] Optionally, generating a quality assessment report based on the comprehensive quality assessment score includes: Retrieve historical assessment data of faulty arc circuit breakers of the same model or batch as the faulty arc circuit breaker under test from the preset quality assessment historical database. The comprehensive quality assessment score is compared and analyzed with the historical assessment data to generate a horizontal performance comparison analysis result; The results of the horizontal performance comparison analysis are integrated with the comprehensive quality assessment score to generate the quality assessment report.

[0039] Specifically, after calculating the comprehensive quality assessment score of the tested arc fault circuit breaker, the system first accesses a preset historical quality assessment database. This database stores a large amount of historical assessment data for previously tested arc fault circuit breakers of the same model or production batch, including their comprehensive quality assessment scores and various sub-indicators. The system retrieves relevant historical datasets from the database using the model or batch information of the tested circuit breaker as an index. Next, the system performs statistical analysis on this historical assessment data, calculating key statistical indicators, such as the average score, score distribution range, standard deviation, and highest and lowest performance values ​​for that model or batch of products. Subsequently, the comprehensive quality assessment score of the current tested circuit breaker is compared with these statistical indicators to generate a horizontal performance comparison analysis result. This result clearly indicates the performance ranking of the tested product among similar products, such as whether its performance is at the average level, better than most similar products, or has performance deviations. Finally, the system integrates the comprehensive quality assessment score obtained from this test and the generated horizontal performance comparison analysis result, and outputs it in a formatted manner according to a preset template, ultimately forming a quality assessment report.

[0040] Optionally, the method further includes: Based on the values ​​of the arc identification index and the noise suppression index, a fault attribution analysis is performed to generate the fault attribution analysis results. Based on the failure attribution analysis results, diagnostic recommendations are generated and integrated into the quality assessment report.

[0041] Specifically, after completing the horizontal performance comparison analysis, fault attribution analysis is performed using the previously calculated independent values ​​of the arc recognition index and noise suppression index. This analysis process relies on a pre-defined fault diagnosis rule base, which maps different combinations of index value ranges to specific performance bottlenecks or potential fault modes. For example, if the arc recognition index is low while the noise suppression index is excellent, the rule base will determine that the fault is due to the circuit breaker's insufficient sensitivity to arc characteristics; conversely, if the arc recognition index is high but the noise suppression index is poor, it is attributed to its weak noise interference resistance; if both indices are unsatisfactory, it may point to a more systemic design or hardware defect. Based on this logic, the system automatically generates fault attribution analysis results in text form. Then, the system queries the associated diagnostic suggestion knowledge base based on these results. This knowledge base stores professional suggestions for each specific fault attribution. For example, for issues with insufficient identification sensitivity, diagnostic recommendations might include "checking the gain of the amplifier circuit at the signal acquisition front end" or "optimizing the threshold parameters of the feature extraction algorithm." For issues with weak anti-interference capabilities, recommendations might include "reviewing the shielding design of the hardware circuit" or "strengthening the digital filtering algorithm." Finally, the system integrates this fault attribution analysis result, which includes specific cause determinations, and the clearly guiding diagnostic recommendations into the final quality assessment report.

[0042] Optionally, the method further includes: Obtain the model information of the faulty arc circuit breaker under test; The comprehensive quality assessment score, the arc identification index, the noise suppression index, and the model information are correlated to generate correlated data; The associated data is stored in the historical quality assessment database.

[0043] Specifically, after generating the final quality assessment report containing all analysis results, the first step is to clearly obtain the model information of the tested arc fault circuit breaker. This typically includes unique identifiers such as the manufacturer, product model, and production batch number. Next, the system strongly correlates the core data generated during this assessment process—the final comprehensive quality assessment score—and the key sub-items constituting that score, including arc detection and noise suppression indices, with the obtained model information. This process creates a structured data record that tightly binds the circuit breaker's identity to its multi-dimensional performance data. Finally, this correlated data, containing complete identity information and detailed performance indicators, is stored as a new entry in the aforementioned quality assessment history database. This storage operation is not a simple overwrite but rather an append-only process, continuously expanding the database's capacity and data dimensions.

[0044] Based on the same inventive concept, such as Figure 3 As shown, the present invention also provides a fault arc circuit breaker quality assessment system, the system comprising: The test signal generation module is used to acquire the fault arc reference signal and the background noise reference signal, and to superimpose the fault arc reference signal and the background noise reference signal to generate a composite test signal. The response signal acquisition module is used to apply the composite test signal to the fault arc circuit breaker under test and acquire the circuit breaker response signal output by the internal circuit of the fault arc circuit breaker under test. The signal decoupling processing module is used to perform signal decoupling processing on the circuit breaker response signal to separate the arc characteristic component and the noise suppression residual. The performance calculation module is used to calculate the arc identification index based on the arc characteristic components and the fault arc reference signal, and to calculate the noise suppression index based on the noise suppression residual and the background noise reference signal. The comprehensive evaluation module is used to perform a weighted fusion calculation based on the arc identification index and the noise suppression index to obtain a comprehensive quality evaluation score. The report generation module is used to generate a quality assessment report based on the comprehensive quality assessment score.

[0045] To verify the feasibility of this invention in practice, it was applied to the quality control department of Company A, an electrical equipment manufacturer. This department is responsible for conducting pre-shipment performance evaluations of its fault arc circuit breakers (AFCI / AFDD). Traditional evaluation methods can only provide a binary conclusion of "pass / fail," failing to quantify the specific performance of the product in complex electromagnetic environments and making it difficult to pinpoint performance bottlenecks.

[0046] In this embodiment, Company A's quality control engineer tested three randomly selected AFDD-S200 samples, designated Sample A, Sample B, and Sample C. First, the system retrieved a standard series fault arc reference signal and a switching power supply background noise reference signal simulating common household appliance interference from the signal library. To simulate challenging real-world operating conditions, the engineer set the signal-to-noise ratio adjustment parameter to -5dB, meaning the background noise energy was higher than the fault arc signal. Based on this parameter, the system automatically calculated the energy ratio and generated a standardized composite test signal.

[0047] Subsequently, the composite test signal was applied to the three test samples. The system simultaneously acquired the circuit breaker response signals output by the internal signal processing circuits and monitored their tripping actions to record the response time. Next, the evaluation system performed signal decoupling processing on the acquired response signals, used wavelet packet transform for multi-scale decomposition, and successfully separated the arc characteristic components and noise suppression residuals based on the frequency band energy distribution law of the fault arc reference signal.

[0048] Based on the separated signal components, the system calculated the key performance indicators for each sample, as shown in Table 1. The arc recognition index is derived by comparing the energy of the arc characteristic components with the energy of the fault arc reference signal, reflecting the sample's ability to capture effective fault signals. The noise suppression index is derived by comparing the energy of the noise suppression residual with the energy of the background noise reference signal, reflecting the sample's ability to resist electromagnetic interference.

[0049] Finally, as Figure 4 As shown, the system, based on the preset application scenario type parameter "residential," calls a set of matching dynamic weight coefficients, including the arc recognition weight. Noise suppression weight Response time weight The system performs weighted fusion calculations on the normalized indicators to obtain a comprehensive quality assessment score. It also retrieves historical assessment data for the AFDD-S200 model from the historical quality assessment database, with a historical average score of 90, generating a quality assessment report that includes horizontal performance comparisons and fault attribution analysis.

[0050] This invention transforms the abstract performance of circuit breakers into specific numerical indicators. Sample A performed best, with an arc detection accuracy of 0.92 and a noise suppression accuracy as low as 0.11, resulting in a comprehensive score of 93, indicating a good balance between effectively identifying fault arcs and suppressing noise interference. Sample B had an arc detection accuracy of only 0.75, leading to a response time of 35ms and the lowest comprehensive score, clearly indicating its performance weakness lies in insufficient sensitivity to fault signal recognition. Although Sample C had a high arc detection accuracy, its noise suppression accuracy was as high as 0.30, indicating weak anti-interference capability. Despite its fast response time, it may pose a risk of false tripping in practical applications.

[0051] It should be noted that the electrical connections between the various units described above do not necessarily represent direct or indirect connections. Any method of indirect connection is applicable to the embodiments of the present invention as long as it achieves the purpose of the present invention. The above descriptions are merely exemplary embodiments of the present invention and should not be construed as limiting the scope of the present invention.

[0052] All equivalent changes and modifications made in accordance with the teachings of this invention are still within the scope of this invention. Those skilled in the art will readily conceive of other embodiments of this invention upon considering the specification and the disclosure of practical truth. This application is intended to cover any variations, uses, or adaptations of this invention that follow the general principles of this invention and include common knowledge or conventional techniques in the art not described herein.

Claims

1. A method for quality assessment of fault arc circuit breakers, characterized in that, The method includes: Acquire the fault arc reference signal and the background noise reference signal, and superimpose the fault arc reference signal and the background noise reference signal to generate a composite test signal; The composite test signal is applied to the fault arc circuit breaker under test, and the circuit breaker response signal output by the internal circuit of the fault arc circuit breaker under test is collected. The circuit breaker response signal is decoupled to separate the arc characteristic component and the noise suppression residual. An arc identification index is calculated based on the arc characteristic components and the fault arc reference signal, and a noise suppression index is calculated based on the noise suppression residual and the background noise reference signal. Based on the arc identification index and the noise suppression index, a weighted fusion algorithm is used to perform a fusion calculation to obtain a comprehensive quality assessment score. A quality assessment report is generated based on the comprehensive quality assessment score.

2. The method for quality assessment of a fault arc circuit breaker according to claim 1, characterized in that, The generation of the composite test signal includes: Acquire the fault arc reference signal and the background noise reference signal; Obtain the signal-to-noise ratio adjustment parameters used to quantify the relative intensity of the fault arc signal and the background noise; Based on the signal-to-noise ratio adjustment parameters, calculate the energy ratio between the fault arc reference signal and the background noise reference signal; The background noise reference signal is adjusted based on the energy ratio, and the adjusted signal is superimposed with the fault arc reference signal to synthesize a composite test signal.

3. The method for quality assessment of a fault arc circuit breaker according to claim 2, characterized in that, The step of performing signal decoupling processing on the circuit breaker response signal to separate the arc characteristic component and the noise suppression residual includes: The circuit breaker response signal is decomposed into multiple scales to obtain time-frequency coefficients in different frequency bands; Based on the frequency band energy distribution pattern of the fault arc reference signal, the characteristic frequency band of the arc is determined; The portion of the time-frequency coefficients belonging to the arc characteristic frequency band is reconstructed to obtain the arc characteristic components. The noise suppression residual is obtained by subtracting the arc characteristic component from the circuit breaker response signal.

4. The method for quality assessment of a fault arc circuit breaker according to claim 3, characterized in that, The calculation of the arc identification index based on the arc characteristic components and the fault arc reference signal, and the calculation of the noise suppression index based on the noise suppression residual and the background noise reference signal, include: Calculate the signal energy of the characteristic components of the electric arc to obtain a first energy value; The signal energy of the fault arc reference signal is calculated to obtain a second energy value, and the ratio of the first energy value to the second energy value is used as the arc identification index. Calculate the signal energy of the noise suppression residual to obtain the third energy value; The signal energy of the background noise reference signal is calculated to obtain a fourth energy value, and the ratio of the third energy value to the fourth energy value is used as a noise suppression index.

5. The method for quality assessment of a fault arc circuit breaker according to claim 4, characterized in that, The obtained comprehensive quality assessment score includes: While applying the composite test signal, the tripping action of the tested fault arc circuit breaker is monitored and the tripping time is recorded to obtain the response time parameter; Based on preset dynamic weighting coefficients, the arc identification index, the noise suppression index, and the response time parameter are fused and calculated to obtain a comprehensive quality assessment score.

6. The method for quality assessment of a fault arc circuit breaker according to claim 5, characterized in that, The method further includes: Obtain the application scenario type parameters corresponding to the faulty arc circuit breaker under test; The dynamic weighting coefficient is dynamically adjusted based on the application scenario type parameter.

7. The method for quality assessment of a fault arc circuit breaker according to claim 5, characterized in that, The process of generating a quality assessment report based on the comprehensive quality assessment score includes: Retrieve historical assessment data of faulty arc circuit breakers of the same model or batch as the faulty arc circuit breaker under test from the preset quality assessment historical database. The comprehensive quality assessment score is compared and analyzed with the historical assessment data to generate a horizontal performance comparison analysis result; The results of the horizontal performance comparison analysis are integrated with the comprehensive quality assessment score to generate the quality assessment report.

8. The method for quality assessment of a fault arc circuit breaker according to claim 7, characterized in that, The method further includes: Based on the values ​​of the arc identification index and the noise suppression index, a fault attribution analysis is performed to generate the fault attribution analysis results; Based on the failure attribution analysis results, diagnostic recommendations are generated and integrated into the quality assessment report.

9. The method for quality assessment of a fault arc circuit breaker according to claim 7, characterized in that, The method further includes: Obtain the model information of the faulty arc circuit breaker under test; The comprehensive quality assessment score, the arc identification index, the noise suppression index, and the model information are correlated to generate correlated data; The associated data is stored in the historical quality assessment database.

10. A fault arc circuit breaker quality assessment system, characterized in that, The system includes: The test signal generation module is used to acquire the fault arc reference signal and the background noise reference signal, and to superimpose the fault arc reference signal and the background noise reference signal to generate a composite test signal. The response signal acquisition module is used to apply the composite test signal to the fault arc circuit breaker under test and acquire the circuit breaker response signal output by the internal circuit of the fault arc circuit breaker under test. The signal decoupling processing module is used to perform signal decoupling processing on the circuit breaker response signal to separate the arc characteristic component and the noise suppression residual. The performance calculation module is used to calculate the arc identification index based on the arc characteristic components and the fault arc reference signal, and to calculate the noise suppression index based on the noise suppression residual and the background noise reference signal. The comprehensive evaluation module is used to perform a weighted fusion calculation based on the arc identification index and the noise suppression index to obtain a comprehensive quality evaluation score. The report generation module is used to generate a quality assessment report based on the comprehensive quality assessment score.

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