CN-121856694-B - Performance test method and system for arc fault detection device based on waveform database

CN121856694BCN 121856694 BCN121856694 BCN 121856694BCN-121856694-B

Abstract

The application discloses a performance test method and a system of an arc fault detection device based on a waveform database, belonging to the technical field of power fault detection equipment test, wherein the method comprises the steps of establishing the arc waveform database and data connection between the arc waveform database and a waveform generation device; the method comprises the steps of establishing electric connection between a waveform generating device and an arc fault detecting device to be detected, generating test waveform data based on an arc waveform database and according to user input and/or autonomy, receiving the test waveform data through the waveform generating device and generating a simulated arc signal according to the test waveform data, outputting the simulated arc signal to the arc fault detecting device to be detected and obtaining a response result of the simulated arc signal to generate performance test data, and actively generating the simulated arc signal through the waveform generating device by establishing the arc waveform database to realize omnibearing performance test of the device to be detected, so that a safe, efficient and low-cost standardized test means is provided for performance evaluation of the arc fault detecting device.

Inventors

WANG YAO
ZHANG ZIZHE
GUO ZHITAO
WANG QINGYUN
Tang Hanjia
LI RUOTONG
WANG ZHUAN

Assignees

英诺电力科技(天津)有限公司

Dates

Publication Date: 20260508
Application Date: 20260317

Claims (10)

1. The method for testing the performance of the arc fault detection device based on the waveform database is characterized by comprising the following steps of: establishing a data connection between the arc waveform database (101) and the waveform generating device (200); establishing an electrical connection between a waveform generating device (200) and an arc fault detecting device to be detected; generating test waveform data based on the arc waveform database (101) and according to user input and/or autonomously; receiving the test waveform data by the waveform generation device (200) and generating an analog arc signal therefrom; Outputting the simulated arc signal to an arc fault detection device to be detected, and obtaining a response result of the arc fault detection device to be detected to generate performance test data; wherein establishing the arc waveform database (101) comprises: Acquiring reference arc waveform data under the combined condition of each influence factor and electric appliance parameters, and storing the reference arc waveform data in a correlated manner as a reference data set; Preprocessing the influence factors, the electrical appliance parameters and the reference arc waveform data in the reference data set, and then analyzing and obtaining the association relation between the reference arc waveform data and each influence factor and/or electrical appliance parameter through a correlation analysis algorithm to generate a waveform derivative model; Selecting a set number of influencing factors, electrical parameters and corresponding reference arc waveform data from the reference data set, storing as the arc waveform database (101), and/or Inputting set influence factors and/or electrical parameters, generating derived arc waveforms based on the waveform derived model, and storing the derived arc waveforms in association with the influence factors and/or electrical parameters as an arc waveform database (101); The influence factors comprise circuit layout, electromagnetic radiation intensity of a test environment, temperature and humidity and vibration data; the electrical parameters comprise the type and the number of electrical appliances which are connected into the circuit within a set period.
2. The method for testing the performance of the arc fault detection device based on the waveform database according to claim 1, the performance test method is characterized by further comprising the following steps: acquiring circuit basic noise data corresponding to various circuit layouts and environment electromagnetic radiation intensity combination conditions, and storing the circuit basic noise data in a correlated manner as a circuit basic noise library; different circuit basic noise data are introduced in the test process, and are output to the waveform generation device (200) after being fused with the test waveform data.
3. The method for testing the performance of the arc fault detection device based on the waveform database according to claim 1, the performance test method is characterized by further comprising the following steps: acquiring equipment basic noise data corresponding to the arc fault detection device to be detected under the electromagnetic radiation intensity, the temperature and humidity and the vibration conditions, and storing the equipment basic noise data in a correlated mode as an equipment basic noise library; Different basic noise data of the equipment are introduced in the test process, and are fused with the test waveform data and then output to the waveform generation device (200).
4. A method of testing the performance of an arc fault detection device based on a waveform database according to claim 2 or 3, characterized by autonomously generating test waveform data based on the arc waveform database (101), comprising: Acquiring working scenes suitable for the current arc fault detection device to be detected, acquiring and storing common influence factors and electrical parameter data in the working scenes in a correlated mode, automatically calling the corresponding influence factors and electrical parameter data according to the working scenes input by a user, and searching and outputting corresponding arc waveform data based on the arc waveform database (101) to serve as test waveform data, or And acquiring a detection interval adapted to the current arc fault detection device to be detected, and selecting arc waveform data which is close to the detection interval from the arc waveform database (101) as test waveform data.
5. The method for testing the performance of an arc fault detection device based on a waveform database according to claim 1, wherein obtaining the response result of the arc fault detection device to be tested, generating performance test data, comprises: Setting and storing association relations between each response result of the arc fault detection device to be detected and each arc waveform characteristic; acquiring current test waveform data, confirming arc waveform characteristics contained in the current test waveform data based on a waveform characteristic recognition algorithm, and determining an expected response result; collecting an actual response result of the arc fault detection device to be detected, comparing the actual response result with the expected response result, and outputting corresponding performance test scoring data according to the approximation degree of the actual response result and the expected response result; wherein the response result comprises a response action type and response time.
6. The arc fault detection apparatus performance testing method based on a waveform database of claim 4, wherein the test waveform data is generated autonomously based on the arc waveform database (101), further comprising: The performance test scoring data corresponding to the test waveform data are stored in a correlated mode; counting the correlation between the arc waveform characteristics contained in the test waveform data and the performance test scoring data; selecting arc waveform characteristics with performance test scores lower than a set value as typical waveform characteristic data according to the association relation between the arc waveform characteristics and the performance test score data; and generating test waveform data according to the typical waveform characteristic data expansion.
7. A performance test system of an arc fault detection device based on a waveform database is characterized by comprising A waveform data generation module (100) comprising an arc waveform database (101) and a test waveform generation unit (102), wherein the arc waveform database (101) is configured to be used for storing each influence factor, electrical appliance parameters and corresponding arc waveform data in a correlated manner, and the test waveform generation unit (102) is configured to generate test waveform data based on the arc waveform database (101) and according to user input and/or autonomy; The waveform generation device (200) is configured to be in data connection with the waveform data generation module (100) and is electrically connected with the arc fault detection device to be detected, and is configured to receive the test waveform data, generate an analog arc signal and output the analog arc signal to the arc fault detection device to be detected; the performance test data generation module (300) is configured to acquire a response result of the arc fault detection device to be detected and generate performance test data; the waveform data generation module (100) includes or is connected to a waveform database construction unit (1011), the waveform database construction unit (1011) including: a reference data set generation subunit (1012) configured to acquire reference arc waveform data under the condition of combination of each influence factor and the electrical appliance parameter, and store the reference arc waveform data in association as a reference data set; The derivative model generation subunit (1013) is configured to preprocess the influence factors, the electrical appliance parameters and the reference arc waveform data in the reference data set, analyze and acquire the association relation between the reference arc waveform data and each influence factor and/or electrical appliance parameter through a correlation analysis algorithm, and generate a waveform derivative model; a waveform data generation subunit (1014) configured to select a set number of impact factors, electrical parameters and corresponding reference arc waveform data from the reference data set, store as the arc waveform database (101), and/or Acquiring set influence factors and/or electrical parameters input by a user, generating a derivative arc waveform based on the waveform derivative model, and storing the derivative arc waveform and the influence factors and/or electrical parameters in association with the arc waveform database (101); the influence factors comprise circuit layout, electromagnetic radiation intensity of a test environment, temperature and humidity and vibration data; the electrical parameters comprise the type and the number of electrical appliances which are connected into the circuit within a set period.
8. The waveform database-based arc fault detection device performance test system of claim 7, further comprising a noise data fusion module comprising: The circuit basic noise generation unit is configured to acquire circuit basic noise data corresponding to various circuit layouts and environment electromagnetic radiation intensity combination conditions, and is stored in a correlated manner as a circuit basic noise library; The equipment foundation noise generation unit is configured to acquire equipment foundation noise data corresponding to the arc fault detection device to be detected under the electromagnetic radiation intensity, the temperature and humidity and the vibration conditions, and store the equipment foundation noise data in an associated mode as an equipment foundation noise library; A noise data fusion unit configured to introduce different circuit base noise data during the test based on user instruction or autonomous selection, to fuse with the test waveform data and output to the waveform generation device (200), and/or Different basic noise data of the equipment are introduced in the test process, and are fused with the test waveform data and then output to the waveform generation device (200).
9. The arc fault detection device performance test system based on a waveform database of claim 7, wherein the performance test data generation module (300) comprises: a waveform characteristic-response result storage unit (301) configured to set and store association relations between each response result of the arc fault detection device to be detected and each arc waveform characteristic; A response result anticipation unit (302) configured to acquire current test waveform data and confirm arc waveform characteristics contained in the current test waveform data based on a waveform characteristic recognition algorithm, and determine an anticipated response result; A performance test score generating unit (303) configured to collect an actual response result of the arc fault detecting device to be detected and compare the actual response result with the expected response result, and output corresponding performance test score data according to the approximation degree of the actual response result and the expected response result; wherein the response result comprises a response action type and response time.
10. The arc fault detection device performance test system based on a waveform database of claim 7, wherein the waveform generation device (200) comprises: A digital-to-analog converter (201) configured to receive the test waveform generation data and convert it into an analog arc signal for output; a power amplifier (202) configured to receive the analog arc signal and amplify it for output; -a filtering circuit (203) configured for filtering noise interference in the analog arc signal; A voltage stabilizing circuit (204) configured to stabilize and output the analog arc signal; And the control circuit (205) is configured to receive the test instruction and regulate and control the output parameters of the simulated arc signal according to the instruction.

Description

Performance test method and system for arc fault detection device based on waveform database Technical Field The application belongs to the technical field of power fault detection equipment testing, and relates to an arc fault detection device performance testing method and system based on a waveform database. Background The arc fault detecting device (AFDD, arc Fault Detection Device) is a protective electric appliance capable of automatically cutting off power supply by identifying the arc characteristics in a circuit, and the working principle and process thereof can be summarized in that the AFDD acquires current signals in the circuit in real time through a current sensor (such as a line transformer), the current signals are amplified and filtered, a microprocessor analyzes waveform characteristics to distinguish dangerous fault arcs from normal operation arcs, and when the dangerous arcs are confirmed, the device triggers an environment-friendly electromagnetic circuit breaker or an integrated tripping mechanism to realize circuit breaking and circuit cutting, and the arcs are prevented from reaching the temperature possibly causing fire. ‌ A In an ac and dc power system, an arc fault detection device is a core device for preventing an electrical fire, and is required to meet a mandatory standard, and accuracy, safety and compatibility of performance detection and verification are critical. However, the existing AFDD detection technology has a plurality of remarkable defects, and the actual application requirements are difficult to meet. The traditional AFDD testing equipment adopts a passive detection mode of 'power supply + load + manufacturing fault', real fault arc is required to be manufactured artificially, high potential safety hazards such as fire disaster, electric shock and the like exist, the fault strength and the development trend are difficult to control accurately, and the safety and the controllability are extremely poor. Moreover, the detection principle depends on the adaptation of a specific power supply and a load, and as the power supply characteristic and the load demand difference of an alternating-current/direct-current system are obvious, only a single system is usually adapted, two sets of special equipment are required to be purchased when a double scene is covered, and the cost is high and the practicability is insufficient. Meanwhile, the equipment needs to run a high-power load to simulate an arc, the energy consumption is high, the loss is large, the environment-friendly energy-saving trend is not met, the arc simulation effect depends on load brands, parameters and running states, so that the test result has strong randomness and insufficient consistency, and stable reference cannot be provided for the performance evaluation of the arc fault detection device. In addition, the alternating current scene loads are various (such as a motor and electronic equipment) to lead to complex arc characteristics, the direct current scene (such as a photovoltaic 1500V system) is high-voltage in-series weak arc high-frequency noise and the millisecond-level response requirement of parallel large-current impact are further increased, the detection difficulty is further increased, and the common AFDD (automatic guided vehicle) test equipment on the market is low in accuracy and cannot break the core pain point due to the fact that standard arc is simulated through a fault arc generator. In summary, there is a need for a performance detection and verification device for an arc fault detection device, which is safe, controllable, compatible with ac and dc, green, energy-saving, and highly consistent in experiment, so as to fill the gap in the prior art. Disclosure of Invention Aiming at the problems that the detection technology of an Arc Fault Detection Device (AFDD) in practical application has a plurality of remarkable defects and is difficult to meet the requirements of practical application, the application aims to provide the performance test method of the arc fault detection device based on the waveform database, which is used for actively generating arc signals based on the waveform generator, getting rid of the dependence on a traditional power supply and a load, outputting fault arc signals with different types, different intensities and different types to form the arc database, carrying out analog-to-digital conversion and amplification on the signals through a broadband constant current source, and outputting stable analog currents with different gears to the AFDD test sample, thereby accurately verifying the accuracy of the arc fault detection device. In order to implement the performance test method, the second objective of the present application is to provide a performance test system for an arc fault detection device based on a waveform database, which comprises the following specific schemes: a method for testing the performance of an arc fault detection device based on