Intelligent measurement switch batch production detection device with fault self-diagnosis

Abstract

The application discloses a kind of batch production detection devices of intelligent measurement switch with fault self-diagnosis, including rack cabinet body, multi-station detection matrix unit, standard power source unit, self-diagnosis main control unit, crimping execution mechanism and data interaction unit;The multi-station detection matrix unit is arranged in rack cabinet body's mesa in row and column, and each station is provided with independent detection channel and the crimping interface of switch to be measured;The standard power source unit is connected to each station detection channel respectively, and provides standard voltage, current excitation signal for the intelligent measurement switch to be measured;The standard power source unit of the application is configured with hot standby redundant channel, and combines source output real-time monitoring loop, can be switched to standby channel in millisecond level when main output channel appears deviation, avoid the interruption of whole batch detection caused by power source anomaly, further improve the stability of long-term continuous operation of device.

Description

Technical Field

[0001] This invention relates to the field of intelligent measuring switch technology, and in particular to a mass production testing device for intelligent measuring switches with fault self-diagnosis. Background Technology

[0002] With the continuous advancement of smart grid construction, intelligent metering switches with functions such as power metering, fault protection, and remote communication have become core equipment in low-voltage distribution network terminals, and market demand is increasing year by year. In the process of large-scale production of intelligent metering switches, factory performance testing is a key process to ensure the metering accuracy and functional reliability of the products. Currently, the industry generally adopts multi-station batch testing devices to improve testing efficiency.

[0003] Existing intelligent measurement switch batch testing devices primarily focus on testing parameters such as measurement accuracy, electrical performance, and protection functions of the switches under test, generally prioritizing increasing the number of workstations and optimizing the testing process as the main directions for efficiency improvement. However, in practical applications involving long-term mass production, these devices still suffer from the following significant technical shortcomings: Firstly, the device itself lacks a systematic self-diagnostic capability, and the verification of the equipment's operating status relies on manual periodic calibration and maintenance. Because the detection device operates under high current and high frequency of start-stop cycles for extended periods, latent faults such as component drift in the sampling circuit, oxidation of wiring terminals, and unstable communication links will gradually accumulate. Since the periodic calibration cycle is usually several weeks long, the device operating with faults during this period can easily lead to false detections and missed detections in the entire batch of products. This not only increases rework costs but also poses a risk of uncontrolled product quality upon leaving the factory.

[0004] Secondly, single-station failures can easily lead to machine shutdowns, resulting in poor continuity of batch production. Most existing batch testing devices adopt a centralized sampling and control architecture. When an abnormality occurs in the testing channel of a single station, it is often impossible to automatically identify and isolate the problem, requiring the entire machine to be shut down for manual troubleshooting and repair. This severely disrupts the production cycle, especially in 24-hour continuous production lines, where the capacity loss caused by a single shutdown is very significant.

[0005] Third, the contact reliability of the automatic crimping process cannot be monitored online. Batch testing devices generally use pneumatic or electric crimping structures to quickly connect the switch under test to the detection circuit. As the number of crimping cycles increases, the copper crimping joints will experience wear, oxidation, and elasticity decay, leading to increased contact resistance and distorted test data. Existing devices can only manually check the condition of the crimping joints periodically, and cannot accurately judge the contact quality during each crimping, resulting in frequent invalid tests and data anomalies due to poor connections.

[0006] Fourth, the fault location is coarse-grained, resulting in low operation and maintenance efficiency. The self-test functions of existing devices are mostly limited to the macro level, such as the overall power supply and the main communication link. When abnormal test data is detected, it is impossible to accurately locate the fault to a specific workstation, phase, or functional circuit. Maintenance personnel need to check point by point, resulting in a long fault repair cycle.

[0007] Fifth, there is insufficient environmental adaptability and a lack of dynamic compensation and diagnosis for temperature drift. The temperature and humidity in the production workshop are prone to fluctuations with the seasons and day and night, and the performance of precision components such as metering chips and current transformers is easily affected by temperature and drifts. Most existing devices are only calibrated at room temperature when leaving the factory, and the accuracy deviation caused by environmental changes in actual production cannot be identified and corrected in real time, resulting in poor detection consistency under long-term operation.

[0008] In addition, some studies have proposed self-testing schemes for testing equipment, but most of them only use a single reference source for simple comparison and do not establish a cross-verification mechanism in combination with the structural characteristics of multi-station batch equipment. When the reference source itself drifts, it is easy to cause misjudgment. At the same time, the existing schemes do not establish a hierarchical fault handling system, which cannot maximize production continuity while ensuring the reliability of testing, and is difficult to adapt to the testing needs of large-scale mass production of intelligent measurement switches. Summary of the Invention

[0009] In order to overcome the shortcomings of the prior art, one of the objectives of this invention is to provide a mass production testing device for intelligent measuring switches with fault self-diagnosis.

[0010] One of the objectives of this invention is achieved through the following technical solution: A batch production testing device for intelligent measurement switches with self-diagnosis includes a rack cabinet, a multi-station detection matrix unit, a standard power source unit, a self-diagnosis main control unit, a crimping actuator, and a data interaction unit. The multi-station detection matrix unit is arranged in rows and columns on the rack cabinet platform, with each station having an independent detection channel and a crimping interface for the switch under test. The standard power source unit is connected to each station's detection channel, providing standard voltage and current excitation signals to the intelligent measurement switch under test. The self-diagnosis main control unit is electrically connected to the standard power source unit, each station's detection channel, and the crimping actuator. The main control unit has a built-in device-level self-diagnostic module and a device-under-test (DUT) detection module. The device-level self-diagnostic module is configured to perform standard source accuracy self-verification, channel loop continuity diagnosis, crimp contact resistance monitoring, and communication link integrity detection in three stages: before detection, during detection, and after detection. When a device fault is detected, it automatically locks the corresponding workstation and triggers an alarm. The crimping actuator is set for each workstation to realize the automatic crimping and separation of the terminal block of the intelligent measurement switch under test and the detection channel. The data interaction unit is connected to the self-diagnostic main control unit to upload detection data and diagnostic logs and receive production scheduling instructions.

[0011] Furthermore, the device-level self-diagnostic module includes a cross-validation submodule. The multiple station detection channels in each row of the multi-station detection matrix unit are interconnected through an electronic switch matrix. The cross-validation submodule is configured to periodically select one station as a reference channel and compare the sampling data of the other stations with the reference channel. When the deviation exceeds a preset threshold, it is determined that the sampling circuit of the corresponding station has a drift fault.

[0012] Furthermore, each workstation's detection channel is connected in series with a high-precision standard current transformer and a standard voltage divider network. The device-level self-diagnosis module has a built-in reference metering chip, which is independent of the sampling circuit of each workstation. During the self-diagnosis phase, a fixed standard signal is output by the standard power source unit. The device-level self-diagnosis module compares the sampled values ​​of each workstation with the acquired values ​​of the reference metering chip point by point to complete the self-diagnosis and correction of channel gain error and phase error.

[0013] Furthermore, the crimping actuator includes a lifting drive assembly, a copper column crimping head array, and a pressure sensor. The copper column crimping head array corresponds to the inlet and outlet terminals of the intelligent measurement switch under test. The pressure sensor is located on the transmission path of the copper column crimping head. The device-level self-diagnostic module is configured to collect the pressure value and loop contact resistance value of each copper column crimping head after crimping. When the contact resistance of any copper column is greater than a preset resistance threshold or the pressure value deviates from the set range, it is determined that there is a poor contact fault at the crimping point and a re-crimping process is triggered.

[0014] Furthermore, the standard power source unit includes a three-phase programmable power source, a source output monitoring circuit, and a redundant backup channel. The source output monitoring circuit collects the output amplitude, frequency, and phase parameters of the power source in real time and feeds them back to the self-diagnostic main control unit. The device-level self-diagnostic module is configured to perform a closed-loop comparison between the source output monitoring value and the set command value. When the deviation exceeds the allowable range, the redundant backup channel is automatically invoked to switch to operation, and the faulty channel is marked and isolated.

[0015] Furthermore, the self-diagnostic main control unit also has a built-in fault classification processing module, which is configured to classify the device's own faults into Level 1 fatal faults, Level 2 workstation faults, and Level 3 early warning faults. Among them, Level 1 fatal faults trigger the entire machine to shut down and issue a general alarm, Level 2 workstation faults only lock the corresponding faulty workstation while the other workstations continue to run, and Level 3 early warning faults generate early warning logs and perform automatic calibration and repair during the detection interval.

[0016] Furthermore, each workstation is equipped with an independent pulse acquisition interface and a communication interface, which are used to acquire the electrical pulse signal of the intelligent measuring switch under test and to perform protocol communication, respectively. The device-level self-diagnosis module is configured to inject a simulated pulse signal into the pulse acquisition interface under no-load conditions and send a protocol test frame to the communication interface to verify the functional integrity of the pulse acquisition channel and the communication link.

[0017] Furthermore, the rack cabinet is equipped with a temperature and humidity acquisition module and a heat dissipation duct. The temperature and humidity acquisition module is connected to the self-diagnostic main control unit. The device-level self-diagnostic module is configured to perform real-time compensation calculations for the temperature drift error between the standard power source and the sampling circuit based on the temperature and humidity data inside the cabinet, and to trigger environmental fault alarms when the temperature and humidity exceed the allowable operating range.

[0018] Furthermore, the electronic switch matrix consists of multiple relays and signal conditioning circuits. The cross-verification submodule adopts a round-robin reference method, using different workstations in each row as reference channels to complete the cross-verification of the entire row. The cross-verification process is automatically executed during the feeding interval of each batch of switches to be tested, without occupying the production testing cycle.

[0019] Furthermore, the data interaction unit includes a local storage module and an industrial Ethernet interface. The self-diagnosis main control unit forms a self-diagnosis log by recording the results of each self-diagnosis, the time of the fault occurrence, the fault station number, and the repair status. This log is then bound and stored with the test result data of the tested intelligent measuring switch and synchronized to the production MES system via the industrial Ethernet interface, thereby achieving full traceability management of the test data and the health status of the device.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention sets up a three-stage device-level self-diagnosis process: before detection, during detection, and after detection. It completes comprehensive self-inspection during batch feeding intervals, realizes online dynamic monitoring during formal detection, and performs drift trend review and diagnosis after the batch ends, thus realizing state perception throughout the entire life cycle of device operation.

[0021] 2. This invention adopts a dual diagnostic architecture of independent reference measurement module + multi-station round-by-round cross-verification: on the one hand, a high-precision reference measurement chip independent of the station circuit is used as the traceability reference to realize the accurate calibration of the gain and phase error of each channel; on the other hand, an electronic switch matrix is ​​used to realize the round-by-round cross-verification of the same group of stations, and the misjudgment caused by the drift of a single reference is eliminated by mutual verification of multiple references.

[0022] 3. This invention classifies the device's own faults into three levels: fatal faults, workstation faults, and early warning faults. Differentiated handling strategies are implemented for different levels of faults: Level 1 faults trigger the entire machine to shut down to ensure safety; Level 2 faults isolate only the corresponding workstation while the other workstations operate normally; and Level 3 faults are automatically repaired online.

[0023] 4. This invention integrates pressure sensing and four-wire contact resistance detection functions at each copper column crimping joint. After each crimping is completed, the contact status is automatically verified, and an automatic re-pressing process is performed on unqualified points.

[0024] 5. This invention binds and stores the device's self-diagnostic logs and product testing data for the corresponding time period using batch IDs, supporting bidirectional traceability. When product testing quality disputes arise, the device's health status during the testing period can be quickly verified, accurately distinguishing between device malfunctions and product defects. This provides reliable data support for production quality analysis and process optimization, adapting to the management needs of digital factories.

[0025] 6. The standard power source unit of the present invention is equipped with a hot standby redundant channel. Combined with the source output real-time monitoring circuit, it can switch to the backup channel in milliseconds when the main output channel deviates, avoiding the interruption of the entire batch of testing due to power source abnormality, and further improving the stability of the device for long-term continuous operation.

[0026] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0027] Figure 1 This is the main flowchart for the overall detection and self-diagnosis in this embodiment; Figure 2 This is a flowchart of the multi-station cross-verification and benchmark comparison process in this embodiment. Detailed Implementation

[0028] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0029] It should be noted that when a component is said to be fixed to another component, it can be directly on the other component or it may have a component in between. When a component is said to be connected to another component, it can be directly connected to the other component or it may have a component in between. When a component is said to be set to another component, it can be directly set to the other component or it may have a component in between. The terms vertical, horizontal, left, right, and similar expressions used in this document are for illustrative purposes only.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The terminology used herein includes, and / or encompasses, any and all combinations of one or more of the associated listed items.

[0031] I. Overall Device Structure The intelligent measurement switch mass production testing device with fault self-diagnosis described in this embodiment includes a frame cabinet, a multi-station detection matrix unit, a standard power source unit, a self-diagnostic main control unit, a crimping actuator, and a data interaction unit. The frame cabinet is welded from 1.5mm thick cold-rolled steel plate, with overall dimensions of 1800mm in length, 800mm in width, and 1600mm in height. The lower cabinet is a sealed cavity used to house the standard power source unit and the main control power supply module. The upper platform is made of insulated bakelite board, where the multi-station detection matrix unit and the crimping actuator are arranged. An acrylic safety cover and an audible and visual alarm light are installed above the platform.

[0032] The multi-station testing matrix unit is fixed on the table with 24 stations arranged in a row and column configuration of 4 rows and 6 columns. The horizontal spacing of each station is 120mm and the vertical spacing is 100mm, which is compatible with the installation dimensions of mainstream 1P, 2P, and 3P intelligent measurement switches on the market. Each station is equipped with an independent testing channel and a crimping interface for the switch under test. The testing channels of all stations are connected to the self-diagnostic main control unit through a backplane bus, realizing centralized management of power supply, sampling, and communication.

[0033] II. Specific Structure of Each Functional Unit 1. Standard power source unit The standard power source unit adopts a three-phase programmable high-precision power source with an output voltage range of 0~450V, an output current range of 0~100A, a basic accuracy class of 0.05, a frequency adjustment range of 45~65Hz, and a phase adjustment range of 0~360°, capable of simulating various power grid operating conditions and fault waveforms. The power source integrates an independent source output monitoring circuit, employing 0.02-class precision voltage and current transformers in conjunction with a 16-bit high-speed AD sampling chip. With a sampling frequency set to 10kHz, it can acquire the voltage amplitude, current amplitude, frequency, and phase parameters at the power source output in real time and feed the monitoring data back to the self-diagnostic main control unit.

[0034] The standard power source unit is configured with three sets of redundant backup output channels. Under normal operating conditions, the main output channel powers all 24 stations, while the backup channels are in hot standby mode, with output parameters synchronized with the main channel in real time. The device-level self-diagnostic module performs a closed-loop comparison between the source output monitoring values ​​and the set command values ​​issued by the main control unit. When the output deviation exceeds the allowable threshold of 0.1%, the self-diagnostic main control unit completes seamless switching of the backup channel within 100ms, while simultaneously marking and isolating the faulty main channel and pushing the fault log to prevent the entire batch of test data from becoming invalid due to power source malfunction.

[0035] 2. Multi-station detection matrix unit and electronic switch matrix Each workstation corresponds to an independent testing channel board, which integrates a 0.1-class precision current transformer, a high-precision resistor voltage divider network, an energy metering chip, a pulse acquisition circuit, and an RS485 communication interface. The energy metering chip uses the RN8302B three-phase metering chip, enabling high-precision acquisition of parameters such as voltage, current, active power, reactive power, and energy. The pulse acquisition circuit has opto-isolation capabilities and can acquire passive energy pulse signals output by the switch under test, with a pulse frequency supporting 0~10kHz. The RS485 communication interface supports mainstream power communication protocols such as DL / T645 and Modbus, used to read the internal metering data and fault information of the switch under test.

[0036] The 24 workstations are divided into 4 independent verification groups, with each group corresponding to 6 workstations per row. Each workstation's detection channel input is connected to an electronic switch matrix. This matrix consists of 24 magnetically latched relays and second-order RC signal conditioning circuits. The on-resistance of a single relay is less than 50mΩ, and crosstalk suppression between channels is better than -60dB. The electronic switch matrix is ​​controlled by a self-diagnostic main control unit, allowing arbitrary selection of sampling loops from two workstations within the same group, enabling interconnection of sampling signals and providing the hardware foundation for cross-verification.

[0037] 3. Self-diagnostic main control unit The self-diagnostic main control unit adopts a three-layer hardware architecture consisting of an industrial-grade main controller, a reference measurement module, and FPGA logic control. The main controller uses an NXP.MXRT1064 industrial-grade microcontroller with a main frequency of 600MHz, equipped with 512KB of on-chip SRAM and 8MB of external Flash, responsible for overall testing process scheduling, fault logic judgment, and data interaction processing. The reference measurement module uses an ADIADE7880 high-precision measurement chip, paired with a 2.5V low-temperature drift reference source, with a temperature drift coefficient as low as 2ppm / ℃ and an overall accuracy level of 0.02. As the internal measurement reference of the device, this module is independent of the sampling loops of all stations and is only connected to the loop during the self-diagnostic stage. The FPGA chip uses a Xilinx Artix-7 series, responsible for the timing control of the electronic switch matrix, the logic drive of the pressing actuator, and the preprocessing of high-speed sampling data.

[0038] The self-diagnostic main control unit has a built-in device-level self-diagnostic module and a device-under-test (DUT) detection module. The device-level self-diagnostic module is divided into three execution stages according to the testing process: pre-test self-test, online monitoring during testing, and post-test review and diagnosis. Pre-test self-test stage: Automatically executed after power-on initialization or during the feeding interval of each batch of products, sequentially completing power source output accuracy verification, full-channel circuit continuity test, crimp contact resistance test, pulse acquisition channel test and communication link integrity test. The total time of the entire process does not exceed 8 seconds and does not occupy the formal production cycle. During the online monitoring phase of the test: In the process of formally testing the intelligent measuring switch under test, the sampling data fluctuation, crimping pressure change value, and communication error rate of each station are collected in real time. At the same time, a reference signal is inserted for comparison every 30 seconds to realize the dynamic real-time detection of device faults. Post-inspection review and diagnosis phase: After the inspection of a single batch of products is completed, the historical sampling dataset of all workstations is retrieved, and the drift trend of each channel is analyzed through cross-comparison algorithm to generate a device health assessment report and predict potential hidden faults.

[0039] The self-diagnostic main control unit also has a built-in fault classification and processing module, which can classify the device's own faults into three levels: Level 1 fatal faults, Level 2 station faults, and Level 3 early warning faults. Level 1 fatal faults include failure of both the main and backup power source channels, interruption of main control bus communication, and abnormal main power supply. These faults trigger a complete machine shutdown and a total audible and visual alarm, and immediately push emergency fault information to the production system. Level 2 station faults include single station sampling channel failure, poor contact of a single crimping contact, and single station communication interruption. These faults only lock the corresponding faulty station, while the other stations can continue to operate normally without interrupting the entire production line. Level 3 early warning faults include slight channel drift, temperature and humidity approaching thresholds, and slight fluctuations in crimping pressure. These faults do not stop the current detection process, but only generate an early warning log and automatically perform calibration or parameter adjustment during the detection interval to clear the early warning status.

[0040] 4. Press-fit actuator The crimping actuator is equipped with four independent lifting drive components for each of the four workstations. Each drive component drives the crimping head array of six workstations in one row to lift synchronously. The lifting drive uses a servo electric cylinder in conjunction with a high-precision linear guide rail, with a stroke of 50mm and a positioning accuracy of up to 0.05mm. The pressing speed and holding time can be flexibly set through the main control unit.

[0041] Each workstation corresponds to 6 copper crimp connectors, arranged in a 3-in, 3-out configuration to accommodate the input and output terminals of a three-phase intelligent measuring switch. The copper pillars are made of gold-plated copper, with a diameter of 6mm. Each crimp connector has a rated current carrying capacity greater than 100A, meeting the requirements for high-current testing. A thin-film pressure sensor is connected in series at the tail of each copper crimp connector, with a range of 0~50N and a detection accuracy of 2%. Simultaneously, the crimping circuit integrates a four-wire contact resistance detection circuit, which can accurately measure contact resistance in the millimeter range, effectively identifying poor contact problems such as incomplete connections and oxidation.

[0042] After the crimping actuator descends to its designated position, the device-level self-diagnostic module collects the pressure value and circuit contact resistance value of each copper column point by point. The preset acceptable contact resistance threshold is 50mΩ, and the acceptable pressure range is 20~40N. When the contact resistance of any copper column is greater than 50mΩ or the pressure value deviates from the acceptable range, it is determined that there is a poor contact fault at that crimping point, and the lifting-re-crimping process is automatically executed. If the crimping fails three times consecutively, the station is locked, triggering a station-level alarm and prompting maintenance personnel to check the status of the fixture and crimping connector.

[0043] 5. Environmental monitoring and temperature drift compensation module The rack cabinet houses three digital temperature and humidity sensors, installed in the power source area, workstation sampling area, and main control area. The temperature measurement range is -20~80℃ with an accuracy of 0.5℃, and the humidity measurement range is 0~95%RH with an accuracy of 3%RH. Two sets of axial flow fans and air ducts are located at the rear of the cabinet, forming a forced air cooling path from bottom to top. The fan speed is adjusted in real-time by the self-diagnostic main control unit based on the internal temperature of the cabinet.

[0044] The device-level self-diagnostic module incorporates a temperature drift compensation algorithm. Based on real-time data collected by three temperature and humidity sensors, and combined with a pre-calibrated temperature drift coefficient matrix for each channel, it performs real-time compensation calculations for voltage and current sampling values. When the cabinet temperature exceeds the rated operating range of 0~40℃ or the relative humidity exceeds 85%RH, a level three environmental warning is triggered; when the temperature exceeds the extreme operating range of -10~50℃, a level two shutdown protection is triggered to prevent damage to precision components due to high temperature and humidity.

[0045] 6. Data Interaction Unit The data interaction unit includes a 32GB industrial-grade solid-state storage module and a gigabit industrial Ethernet interface, while also reserving local debugging interfaces such as RS232 and USB. The self-diagnostic main control unit records the results of each self-diagnosis, the time of fault occurrence, the fault station number, the fault type, and the repair status along a timeline, forming a complete self-diagnosis log. Each log entry is bound to the test results of the intelligent measuring switch under test for the corresponding time period through a unique batch ID, enabling bidirectional full traceability of test data and device health status. All data can be synchronized to the production MES system via the industrial Ethernet interface, supporting remote retrieval of device health status reports and product test details.

[0046] III. Working Principle of the Core Self-Diagnosis Process 1. Benchmark Measurement Comparison and Diagnostic Process During the pre-test self-check phase, the device-level self-diagnostic module controls the standard power source unit to output a set of fixed standard signals, including a power frequency sinusoidal signal with a rated voltage of 220V and a rated current of 5A. The reference measurement module independently collects various parameters of this standard signal as reference values. Simultaneously, each station's testing channel synchronously collects the same signal and uploads the sampled values ​​to the main control unit. The device-level self-diagnostic module compares the sampled values ​​of each station with the reference values ​​of the reference measurement module point by point, calculating the voltage gain error, current gain error, and phase error of each channel. When the error exceeds the preset allowable range of 0.2%, it is determined that the corresponding channel has a gain drift fault, and the calibration coefficient is automatically called to correct the channel; if the error still does not meet the standard after correction, the channel is marked as faulty.

[0047] 2. Multi-station cross-validation process During the intervals between batches of product loading, the self-diagnostic main control unit controls the electronic switch matrix to perform round-robin cross-checks on each of the six workstations in each row. Taking the first row of workstations as an example, workstation 1 is first selected as the reference channel, and the standard power source outputs a standard test signal. The sampled values ​​of workstations 2 to 6 are compared with the sampled values ​​of workstation 1 in turn, and the relative deviation is calculated. Then, workstation 2 is switched as the reference channel, and the sampling deviations of workstations 1 and 3 to 6 are compared in turn. This process is repeated to complete the full cross-check of all six workstations in the row.

[0048] By using a multi-reference comparison method, misjudgments caused by drift in a single reference channel can be eliminated, improving the reliability of fault diagnosis. When the average deviation between a certain workstation and all other workstations exceeds 0.2%, a drift fault is determined in the sampling circuit of that workstation, and the reference measurement module is automatically invoked for single-point precise calibration. If the deviation still does not meet the accuracy requirements after calibration, the workstation is locked and prohibited from use for testing. The entire cross-calibration process is executed automatically during the material loading interval, without occupying the formal production testing cycle and without affecting the production line's operating efficiency.

[0049] 3. Pulse and Communication Link Self-Diagnosis Process Each workstation's pulse acquisition and communication interfaces are equipped with self-diagnostic functions. During the self-diagnostic phase, the device-level self-diagnostic module injects a 1kHz analog pulse signal into the pulse acquisition interface. By statistically analyzing the difference between the number of received pulses and the number injected, the functional integrity of the pulse acquisition channel is verified. Simultaneously, a fixed-length protocol test frame is sent to the RS485 communication interface. By verifying the accuracy and response time of the returned frames, it is determined whether there are faults such as open circuits or excessively high bit error rates in the communication link. This diagnostic process can be completed independently under no-load conditions without connecting the switch under test, effectively avoiding detection failures caused by communication link abnormalities.

[0050] IV. Experimental Verification Process and Results Data To verify the self-diagnostic performance, detection reliability, and production efficiency improvement of this device, three sets of control experiments were conducted under a standard metrological experimental environment. The experimental process and results are as follows.

[0051] 1. Experimental Environment and Experimental Samples The experiment was conducted in a Class I metrology laboratory with a room temperature of 25℃-2℃ and a relative humidity of 50%-10%. The device was powered by a regulated three-phase AC 380V, and a 0.01-class three-phase standard energy meter was configured as an external metrological reference to calibrate the device's detection accuracy. The experimental sample included 24 qualified Class I accuracy intelligent measurement switches, 6 detection channel boards pre-set with gain drift faults, 3 sets of crimping fixtures to simulate excessive contact resistance, 2 sets each of test fixtures to simulate communication circuit breaks and pulse failures, and a power source output deviation simulation control program.

[0052] 2. Self-diagnostic fault detection rate experiment This experiment was conducted to verify the device's ability to identify various common faults. Five typical production line faults were implanted into the device, including sampling channel gain drift, excessive crimp contact resistance, communication link breakage, power source output deviation, and pulse acquisition channel failure. Each type of fault was tested 20 times, and the fault detection rate and false positive rate of the device's self-diagnosis were statistically analyzed.

[0053] Experimental results show that sampling channel gain drift faults were detected in all 20 tests, achieving a 100% detection rate, and the faults could be accurately located to specific workstations and phases, with no missed or false diagnoses. Excessive crimping contact resistance faults were detected in all 20 tests, also achieving a 100% detection rate, and the faults could be located to individual copper column crimping points, with positioning accuracy meeting maintenance requirements. Communication link open circuit faults were detected in all 20 tests, achieving a 100% detection rate, with a response time of less than 1 second. Power source output deviation faults were accurately detected in 19 out of 20 tests, automatically switching to the backup channel, and triggered a level-three warning once due to deviation values ​​approaching the threshold, resulting in an overall detection rate of 95%. Pulse acquisition channel failure faults were detected in all 20 tests, achieving a 100% detection rate. The average detection rate for the five types of faults was 99%, with no false diagnoses throughout the process. This is far superior to the fault detection capabilities of traditional manual periodic calibration, effectively avoiding false detections caused by the device operating with defects.

[0054] 3. Batch production efficiency comparison experiment This experiment was conducted to verify the efficiency-enhancing effect of the proposed device. The device of this invention and a conventional batch testing device without self-diagnosis were used to perform full-item factory testing on 1000 identical intelligent measuring switches. The total testing time, number of device downtimes due to malfunction, and time spent troubleshooting and repairing were recorded to calculate the overall production efficiency.

[0055] Experimental results show that the device of this invention completed a full-item test of 1000 switches in 8 hours and 22 minutes. Two single-station sampling drift faults occurred during the test, both of which were detected in real time by online self-diagnosis and automatically calibrated, without causing a complete machine shutdown. The cumulative time for handling faults in a single batch did not exceed 1 minute. Under the same test conditions, a traditional non-self-diagnostic testing device took 11 hours and 47 minutes to complete the same number of tests. Three device malfunctions occurred during the test, resulting in the invalidation of the entire batch of data, and the cumulative downtime for troubleshooting was 2 hours and 15 minutes. Calculations show that this device can improve the overall production efficiency of batch factory testing of intelligent measurement switches by approximately 39%, while significantly reducing the product misjudgment rate and rework rate caused by device malfunctions.

[0056] 4. Long-term operational stability test This experiment was conducted to verify the reliability of the device during long-term continuous operation and its predictive self-diagnosis capability. The device was continuously powered on for 72 hours, performing a full-station self-diagnosis every hour. During the experiment, the ambient temperature fluctuated naturally by 3°C. The sampling accuracy of each channel was calibrated periodically using an external 0.01-grade standard meter, and the channel drift and fault prediction accuracy were recorded.

[0057] Experimental results show that after 72 hours of continuous operation, the maximum drift of voltage sampling at all workstations was 0.08%, and the maximum drift of current sampling was 0.11%, both better than the 0.2-level channel accuracy requirement. During the experiment, the self-diagnostic module issued four Level 3 drift warnings, all of which automatically completed coefficient calibration during the detection intervals. After calibration, the channel deviation recovered to within 0.05%, and the fault prediction accuracy reached 100%. Under fluctuating ambient temperature conditions, the temperature drift compensation algorithm can reduce the sampling error caused by temperature by more than 75%, effectively improving the device's adaptability to complex workshop environments.

[0058] The experimental data in summary show that, through a series of technical means such as a three-stage full-process self-diagnosis mechanism, multi-station cyclic cross-verification, independent benchmark measurement comparison, and graded fault handling, this invention can achieve efficient batch testing of intelligent measurement switches, and can diagnose the faults of the device itself in real time and accurately, effectively avoid the detection risks caused by hidden faults of the device, significantly improve the reliability and operating efficiency of production line testing, and has outstanding technical progress and practical value.

[0059] The above embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-substantial changes and substitutions made by those skilled in the art based on the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. A batch production testing device for intelligent measuring switches with self-diagnosis of faults, characterized in that, The system includes a rack cabinet, a multi-station detection matrix unit, a standard power source unit, a self-diagnostic main control unit, a crimping actuator, and a data interaction unit. The multi-station detection matrix unit is arranged in rows and columns on the rack cabinet's platform, with each station having an independent detection channel and a crimping interface for the switch under test. The standard power source unit is connected to each station's detection channel, providing standard voltage and current excitation signals to the intelligent measurement switch under test. The self-diagnostic main control unit is electrically connected to the standard power source unit, each station's detection channel, and the crimping actuator. The self-diagnostic main control unit has a built-in device-level self-diagnostic function. The diagnostic module and the device-under-test (DUT) detection module are configured to perform standard source accuracy self-verification, channel loop continuity diagnosis, crimp contact resistance monitoring, and communication link integrity detection in three stages: before, during, and after testing. When a fault is detected in the device itself, the module automatically locks the corresponding workstation and triggers an alarm. A crimping actuator is provided for each workstation to automatically crimp and disconnect the terminals of the intelligent measurement switch under test from the detection channel. The data interaction unit connects to the self-diagnostic main control unit to upload test data and diagnostic logs and receive production scheduling instructions.

2. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 1, characterized in that, The device-level self-diagnostic module includes a cross-validation submodule. In the multi-station detection matrix unit, multiple station detection channels in each row are interconnected through an electronic switch matrix. The cross-validation submodule is configured to periodically select one station as a reference channel and compare the sampling data of the other stations with the reference channel. When the deviation exceeds a preset threshold, it is determined that the sampling circuit of the corresponding station has a drift fault.

3. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 1, characterized in that, Each workstation's detection channel is connected in series with a high-precision standard current transformer and a standard voltage divider network. The device-level self-diagnosis module has a built-in reference metering chip, which is independent of the sampling circuit of each workstation. During the self-diagnosis phase, a fixed standard signal is output by the standard power source unit. The device-level self-diagnosis module compares the sampled values ​​of each workstation with the acquired values ​​of the reference metering chip point by point to complete the self-diagnosis and correction of channel gain error and phase error.

4. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 1, characterized in that, The crimping actuator includes a lifting drive assembly, a copper column crimping connector array, and a pressure sensor. The copper column crimping connector array corresponds to the inlet and outlet terminals of the intelligent measurement switch under test. The pressure sensor is set on the transmission path of the copper column crimping connector. The device-level self-diagnostic module is configured to collect the pressure value and loop contact resistance value of each copper column crimping connector after crimping. When the contact resistance of any copper column is greater than a preset resistance threshold or the pressure value deviates from the set range, it is determined that there is a poor contact fault at the crimping point and a re-crimping process is triggered.

5. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 1, characterized in that, The standard power source unit includes a three-phase programmable power source, a source output monitoring circuit, and a redundant backup channel. The source output monitoring circuit collects the output amplitude, frequency, and phase parameters of the power source in real time and feeds them back to the self-diagnostic main control unit. The device-level self-diagnostic module is configured to perform a closed-loop comparison between the source output monitoring value and the set command value. When the deviation exceeds the allowable range, the redundant backup channel is automatically invoked to switch to operation, and the faulty channel is marked and isolated.

6. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 1, characterized in that, The self-diagnostic main control unit also has a built-in fault classification and processing module. The fault classification and processing module is configured to classify the faults of the device itself into Level 1 fatal faults, Level 2 workstation faults and Level 3 early warning faults. Among them, Level 1 fatal faults trigger the entire machine to stop and the overall alarm, Level 2 workstation faults only lock the corresponding faulty workstation and the other workstations continue to run, and Level 3 early warning faults generate early warning logs and perform automatic calibration and repair during the detection interval.

7. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 1, characterized in that, Each workstation is also equipped with an independent pulse acquisition interface and a communication interface, which are used to acquire the electrical pulse signal of the intelligent measuring switch under test and to perform protocol communication, respectively. The device-level self-diagnosis module is configured to inject a simulated pulse signal into the pulse acquisition interface in an unloaded state and send a protocol test frame to the communication interface to verify the functional integrity of the pulse acquisition channel and the communication link.

8. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 1, characterized in that, The rack cabinet is equipped with a temperature and humidity acquisition module and a heat dissipation duct. The temperature and humidity acquisition module is connected to the self-diagnostic main control unit. The device-level self-diagnostic module is configured to perform real-time compensation calculation for the temperature drift error between the standard power source and the sampling circuit based on the temperature and humidity data inside the cabinet, and to trigger an environmental fault alarm when the temperature and humidity exceed the allowable operating range.

9. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 2, characterized in that, The electronic switch matrix consists of multiple relays and signal conditioning circuits. The cross-verification submodule adopts a round-robin reference method, using different workstations in each row as reference channels to complete the cross-verification of the entire row. The cross-verification process is automatically executed during the feeding interval of each batch of switches to be tested, without occupying the production testing cycle.

10. The intelligent measurement switch batch production testing device with fault self-diagnosis according to claim 1, characterized in that, The data interaction unit includes a local storage module and an industrial Ethernet interface. The self-diagnosis main control unit records the results of each self-diagnosis, the time of the fault occurrence, the fault station number, and the repair status to form a self-diagnosis log. This log is bound and stored with the test result data of the tested intelligent measuring switch and synchronized to the production MES system through the industrial Ethernet interface, thereby realizing full traceability management of test data and device health status.

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