An online monitoring and fault diagnosis system for XLPE cable sheath current

Abstract

The present invention discloses an online monitoring and fault diagnosis system for XLPE cable sheath current, which is composed of a current sensor and an online monitoring device. The current sensor is installed on the ground wire of the cross-connection box of the cable under test. The current sensor and the online monitoring device are connected by a high-shielded coaxial cable. The online monitoring device can upload the monitoring results to the upper system platform in the form of a network port or an optical port. Different online monitoring devices can operate in a self-ring network. The device has an edge computing function and a built-in fault diagnosis algorithm to realize information processing, fault diagnosis and alarm on site. The present invention can accurately and effectively determine whether the insulation of the XLPE cable in operation is broken down, use the cable sheath current as a characteristic signal, perform signal feature extraction and fault identification, and provide corresponding criteria to characterize the insulation performance of the power cable.

Description

Technical Field

[0001] The invention relates to an online monitoring system for a high-voltage cable, and in particular to an online monitoring and fault diagnosis system for an XLPE cable sheath current. Background Art

[0002] For cross-linked polyethylene (XLPE) power cables with voltage levels of 66kV and above in my country's power grid system, insulation damage or line failure is easy to occur due to production quality, external force damage, insulation aging and other factors. At present, the detection of XLPE cable status mainly uses the method of regular inspection and power outage preventive test. This method belongs to offline monitoring, and there are problems such as inaccurate test model and introduction of test damage risk. XLPE cables with higher voltage levels generally use live detection. The detection results of this method are consistent with the actual operation of the cable, but there are problems such as high operation and maintenance costs and inability to continuously monitor. Existing cable online monitoring methods include optical fiber temperature measurement, sheath current, partial discharge and other monitoring methods. Compared with existing online monitoring methods, online monitoring of sheath current is a method that is simple to operate and has strong engineering applicability. However, the current fault diagnosis of this method is generally implemented in the monitoring host, which increases the system construction cost and the difficulty of connecting to the integrated monitoring system of the substation; and the diagnosis model is relatively simple, and the accuracy of cable operation status identification needs to be further improved. Summary of the invention

[0003] In order to accurately and effectively determine whether the insulation of an XLPE cable in operation is broken down, the cable sheath current is used as a characteristic signal to extract signal features and identify faults, and corresponding criteria are given to characterize the insulation performance of the power cable. The present invention provides an XLPE cable sheath current online monitoring and fault diagnosis system, which uses edge computing technology to embed a fault diagnosis model into the device layer, thereby realizing real-time monitoring and fault diagnosis of the operating status of the power cable.

[0004] In order to solve the technical problem, the technical solution adopted by the present invention is: an XLPE cable sheath current online monitoring and fault diagnosis system, including a current sensor and an online monitoring device, the current sensor is installed on the ground wire of the cross-connection box of the tested cable, and is used to monitor the sheath current of the tested cable. The online monitoring device includes a current acquisition module, a communication module, a power supply module and an MCU main control module. The power supply module supplies power to the current acquisition module, the communication module and the MCU main control module. The current acquisition module is connected between the current sensor and the MCU main control module. The current acquisition module collects 4 sheath current signals, including phase A, phase B, phase C and a total current signal, and uploads the data to the MCU main control module after preprocessing. The MCU main control module is connected to the monitoring platform through the communication module.

[0005] Furthermore, the current acquisition module includes a current acquisition circuit and an electric energy acquisition chip. The current acquisition circuit includes resistors R20, R21, R22, R122 and capacitors C35 and C36. Resistor R21 is connected between the positive input terminal of the sheath current and the positive output terminal of the circuit, resistor R22 is connected between the negative input terminal of the sheath current and the negative output terminal of the circuit, resistor R122 is connected between the negative input terminal of the sheath circuit and ground, resistor R20 is connected between the positive input terminal of the sheath current and the negative input terminal of the sheath current, capacitors C35 and C36 are connected in series between the positive output terminal and the negative output terminal of the circuit, and capacitor C35 and capacitor C36 are grounded, the positive input terminal and the negative input terminal of the sheath current are connected to the output terminal of the current sensor, and the positive output terminal and the negative output terminal of the current acquisition circuit are connected to the input terminal of the electric energy acquisition chip.

[0006] Furthermore, a power supply control circuit is provided between the MCU main control module and the power collection chip. The power supply control circuit includes a transistor V1, an inductor L3, a capacitor C95 and a resistor R37. The POWER_CTRL end of the MCU main control module is connected to the base of the transistor V1, the 3.3V voltage source is connected to the collector of the transistor V1, and the emitter of the transistor V1 is connected to the power supply pin of the power collection chip through the inductor L3. One end of the inductor L3 connected to the power supply pin of the power collection chip is grounded through the capacitor C95, and the capacitor C95 is grounded through the resistor R37.

[0007] Furthermore, the communication module includes LC optical port communication, RJ-45 network port communication and RS485 serial port communication.

[0008] Furthermore, the RS485 serial port communication adopts a self-transceiver controlled RS485 communication circuit, including an isolation chip, an RS485 transceiver chip and a filtering protection circuit. The transceiver port of the isolation chip is connected to the transceiver port of the MCU main control module, and the output end of the isolation chip is connected to the input end of the RS485 transceiver chip through a resistor R43 and a transistor Q4. The filtering protection circuit includes a TVS device D30, a TVS device D31 and a common-mode filter T4. The common-mode filter T4 is connected after the 485A and 485B pins of the RS485 chip. The RS485 transceiver interface J7 connected to the monitoring platform is led out between the common-mode filter T4 and the TVS devices D30 and D31.

[0009] Furthermore, a plurality of online monitoring devices use an optical fiber ring network to communicate with each other, and upload data to the main station system via a core switch.

[0010] Furthermore, the current sensor adopts an outdoor split-type current transformer.

[0011] Furthermore, the steps of performing fault judgment in the system of the present invention are as follows:

[0012] S01), periodically collect the A, B, C three-phase and total sheath current signals, and construct a composite information sequence that suppresses background noise according to the different characteristics of the sheath current signal and the background noise signal after complex wavelet transformation, and filter out the background information in the cable tunnel;

[0013] S02), extracting characteristic parameters of the sheath current signal, including current amplitude Am, phase Φ, average value Avg, change rate r, growth rate v and unbalance rate u of three phases A, B and C, and constructing a characteristic vector of the sheath current;

[0014] S03), statistically analyzing and storing the extracted characteristic parameters;

[0015] S04) Analyze the cable operation status according to the set threshold parameters and historical data comparison, which is divided into normal operation status and fault status. The fault status sets different level thresholds according to the severity, and is divided into warning and serious status, and different disposal strategies are given. In the warning status, the monitoring frequency is increased, and 24-hour continuous tracking monitoring and comparative analysis are carried out. The comparative analysis characteristic quantities include the proportion of sheath current threshold exceeding the limit, the proportion of exceeding the limit time, the increase in each power frequency cycle, the increase in amplitude / average value per minute, and the increase in three-phase imbalance rate; in the serious status, it is recommended to carry out on-site maintenance and operation according to the cause of the fault;

[0016] S05) Record the original waveform of the current signal for 24 hours under fault conditions for fault identification or expert diagnosis;

[0017] S06) An expectation maximization clustering algorithm based on an improved Gaussian mixture model with historical data analysis is used to identify fault types. Sheath current feature vectors are used to construct five common cable fault types: cable overload, cable break, loose cable joints, cross-connection box flooding, and cable joint prefabricated component breakdown. Feature areas are divided according to feature vectors of various discharge types. The monitoring samples are tested using a classification model to achieve preliminary fault diagnosis and give the probability of the fault type. Based on the feature vectors of the continuous monitoring data within 24 hours in step 4, a horizontal comparative analysis is performed to correct the fault type and its probability.

[0018] Beneficial effects of the invention: The invention provides an XLPE cable sheath current online monitoring and fault diagnosis system, which can realize real-time monitoring, statistical comparative analysis and historical data storage of the grounding current of the metal outer sheath of the XLPE high-voltage cable. The invention applies a cluster analysis algorithm to realize fault diagnosis and analysis, and has the characteristics of good technical and economic performance, high monitoring efficiency and accurate diagnosis. It can realize the overall insulation state monitoring of the cable and prevent the sudden change of the current operation state from causing faults and then causing power accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is the principle block diagram of the online monitoring device;

[0020] Figure 2 It is the circuit schematic diagram of the current acquisition circuit;

[0021] Figure 3 The schematic diagram of the power supply control circuit;

[0022] Figure 4 This is the circuit schematic diagram of the RS485 communication circuit;

[0023] Figure 5 It is a communication diagram of multiple online monitoring devices;

[0024] Figure 6 The figure is a flow chart of the fault judgment method. DETAILED DESCRIPTION

[0025] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0026] Example 1

[0027] This embodiment discloses an online monitoring and fault diagnosis system for XLPE cable sheath current, which is composed of a current sensor and an online monitoring device. The current sensor is installed on the ground wire of the cross-connection box of the cable under test. The current sensor and the online monitoring device are connected by a high-shielded coaxial cable. The online monitoring device can upload the monitoring results to the upper system platform in the form of a network port or an optical port. Different online monitoring devices can operate in a self-ring network. The device has edge computing function and built-in fault diagnosis algorithm to realize information processing, fault diagnosis and alarm on site.

[0028] like Figure 1 As shown, the online monitoring device includes a current acquisition module, a communication module, a power module and an MCU main control module. The power module supplies power to the current acquisition module, the communication module and the MCU main control module. The rated input is AC220V and can output multiple voltage signals such as DC5V / DC24V. The current acquisition module is connected between the current sensor and the MCU main control module. The current acquisition module collects 4 sheath current signals, including phase A, phase B, phase C and one total current signal, and uploads the data to the MCU main control module after preprocessing. The MCU main control module is connected to the monitoring platform through the communication module. According to the set diagnostic rules, the monitoring platform statistically compares the A, B, C three-phase and total sheath current signals, combines historical monitoring data, analyzes the change law of data characteristic values, and realizes fault diagnosis and alarm according to the data characteristic values ​​and change law characteristics. The main characteristic values ​​include current signal amplitude, phase, average value, change rate, growth rate and imbalance rate of A / B / C phases.

[0029] In this design, four sampling channels are used to collect A / B / C phases and one total current signal, namely IA+, IB+, IC+, and IN+. Taking IN+ as an example (IA+, IB+, IC+ and IN+ have the same circuit structure), Figure 2 As shown, the current acquisition module includes a current acquisition circuit and an electric energy acquisition chip. The current acquisition circuit includes resistors R20, R21, R22, R122 and capacitors C35 and C36. The resistor R21 is connected between the positive input terminal of the sheath current and the positive output terminal of the circuit, the resistor R22 is connected between the negative input terminal of the sheath current and the negative output terminal of the circuit, the resistor R122 is connected between the negative input terminal of the sheath circuit and the ground, the resistor R20 is connected between the positive input terminal of the sheath current and the negative input terminal of the sheath current, the capacitors C35 and C36 are connected in series between the positive output terminal and the negative output terminal of the circuit, and the capacitor C35 and the capacitor C36 are grounded, the positive input terminal of the sheath current and the negative input terminal of the sheath current are connected to the output terminal of the current sensor, and the positive output terminal and the negative output terminal of the current acquisition circuit are connected to the input terminal of the electric energy acquisition chip. The electric energy acquisition chip outputs a digital signal to the MCU main control chip after analog-to-digital conversion of the received current signal.

[0030] In this embodiment, the current sensor uses an outdoor split current transformer with a rated input current of 200A and a rated output current of 100mA. The power collection chip is powered by a single 3.3V power supply. The module has functions such as signal collection, filtering and analog-to-digital conversion, and the nonlinear measurement error is less than 0.1%. It adopts synchronous sampling and has harmonic analysis and temperature compensation functions.

[0031] The acquisition chip and MCU use SPI communication. The power supply of the sampling module is controlled by the main chip POWER_CTRL signal through the V1 transistor, and the inductor L3 and electrolytic capacitor C95 are used to isolate the main control module ground (DGND) and the sampling module ground (DGND_1). Figure 3 As shown, a power supply control circuit is provided between the MCU main control module and the power collection chip, and the power supply control circuit includes a transistor V1, an inductor L3, a capacitor C95 and a resistor R37. The POWER_CTRL end of the MCU main control module is connected to the base of the transistor V1, the 3.3V voltage source is connected to the collector of the transistor V1, and the emitter of the transistor V1 is connected to the power supply pin of the power collection chip through the inductor L3. One end of the inductor L3 connected to the power supply pin of the power collection chip is grounded through the capacitor C95, and the capacitor C95 is grounded through the resistor R37.

[0032] In this embodiment, the communication module includes 2 LC optical ports, 4 RJ-45 network ports and 2 RS485 communication ports. It supports TCP / IP protocol and communication rate of 10 / 100M, which can realize high-speed network communication and meet the current sampling frequency requirements. Figure 4 As shown, RS485 serial communication adopts RS485 communication circuit with self-transceiver control, including isolation chip, RS485 transceiver chip and filter protection circuit. The transceiver port of the isolation chip is connected to the transceiver port of the MCU main control module. The output end of the isolation chip is connected to the input end of the RS485 transceiver chip through resistor R43 and transistor Q4. The filter protection circuit includes TVS device D30, TVS device D31 and common mode filter T4. The common mode filter T4 is connected after the 485A and 485B pins of the RS485 chip. The RS485 transceiver interface J7 connected to the monitoring platform is led out between the common mode filter T4 and TVS devices D30 and D31. RS485 serial communication realizes circuit filtering protection through TVS devices D30, D31 and common mode filter T4. At the same time, the ADUM1201BR isolation chip is configured to realize the isolation of the main control circuit from the external circuit to prevent on-site interference. The system complies with the IEC61850 communication protocol for data upload, realizing the communication function of the device at the substation monitoring end.

[0033] In this embodiment, the main control chip adopts the STM32 series controller, which integrates multiple functions such as timer, CAN, SPI, I2C, USB, USART, etc.; the real-time clock circuit adopts the DS1302 clock chip, and uses the SPI three-wire interface to communicate synchronously with the CPU, which can realize functions such as SOE fault recording and file saving; the watchdog circuit uses the IMP706-T chip to monitor the program running status.

[0034] The monitoring platform or MCU main control module is designed with electromagnetic interference suppression and sheath current signal feature extraction methods based on complex wavelet transform. The expectation maximization (EM) clustering algorithm based on historical analysis of Gaussian mixture model (GMM) is used to establish a relationship model between the characteristic parameters of the sheath current and different faults to achieve fault diagnosis. The monitoring data, operating status, fault type and alarm information are sent to the main station system. The specific implementation steps are as follows: S01), periodically collect A, B, C three-phase and total sheath current signals, and construct a composite information sequence that suppresses background noise based on the different characteristics of the sheath current signal and the background noise signal after complex wavelet transform, and filter out the background information in the cable tunnel;

[0035] S02), extracting characteristic parameters of the sheath current signal, including current amplitude Am, phase Φ, average value Avg, change rate r, growth rate v and unbalance rate u of three phases A, B and C, and constructing a characteristic vector of the sheath current;

[0036] S03), statistically analyzing and storing the extracted characteristic parameters;

[0037] S04) Analyze the cable operation status according to the set threshold parameters and historical data comparison, which is divided into normal operation status and fault status. The fault status sets different level thresholds according to the severity, and is divided into warning and serious status, and different disposal strategies are given. In the warning status, the monitoring frequency is increased, and 24-hour continuous tracking monitoring and comparative analysis are carried out. The comparative analysis characteristic quantities include the proportion of sheath current threshold exceeding the limit, the proportion of exceeding the limit time, the increase in each power frequency cycle, the increase in amplitude / average value per minute, and the increase in three-phase imbalance rate; in the serious status, it is recommended to carry out on-site maintenance and operation according to the cause of the fault;

[0038] S05) Record the original waveform of the current signal for 24 hours under fault conditions for fault identification or expert diagnosis;

[0039] S06) An expectation maximization clustering algorithm based on an improved Gaussian mixture model with historical data analysis is used to identify fault types. Sheath current feature vectors are used to construct five common cable fault types: cable overload, cable break, loose cable joints, cross-connection box flooding, and cable joint prefabricated component breakdown. Feature areas are divided according to feature vectors of various discharge types. The monitoring samples are tested using a classification model to achieve preliminary fault diagnosis and give the probability of the fault type. Based on the feature vectors of the continuous monitoring data within 24 hours in step 4, a horizontal comparative analysis is performed to correct the fault type and its probability.

[0040] like Figure 5 As shown, in actual engineering applications, an online monitoring device is arranged at each cross-connected grounding box location, and optical fiber ring network communication is adopted between different online monitoring devices, and data is uploaded to the main station system via the core switch.

[0041] The above description is only the basic principle and preferred embodiments of the present invention. Improvements and substitutions made by those skilled in the art based on the present invention belong to the protection scope of the present invention.

Claims

1. An XLPE cable sheath current online monitoring and fault diagnosis system, characterized in that: It includes a current sensor and an online monitoring device. The current sensor is installed on the ground wire of the cross-connection box of the tested cable and is used to monitor the sheath current of the tested cable. The online monitoring device includes a current acquisition module, a communication module, a power module and an MCU main control module. The power module supplies power to the current acquisition module, the communication module and the MCU main control module. The current acquisition module is connected between the current sensor and the MCU main control module. The current acquisition module collects 4 sheath current signals, including phase A, phase B, phase C and a total current signal, and uploads the data to the MCU main control module after pre-processing. The MCU main control module is connected to the monitoring platform through the communication module. The monitoring platform or the MCU main control module performs statistical comparison on the A, B, C three-phase and total sheath current signals according to the set diagnostic rules, analyzes the change law of the data characteristic value in combination with the historical monitoring data, and realizes fault diagnosis and alarm according to the data characteristic value and the change law characteristics; The steps for the MCU main control module or monitoring platform to implement fault diagnosis and alarm are as follows: S01), periodically collect the A, B, C three-phase and total sheath current signals, and construct a composite information sequence that suppresses background noise according to the different characteristics of the sheath current signal and the background noise signal after complex wavelet transformation, and filter out the background information in the cable tunnel; S02), extracting characteristic parameters of the sheath current signal, including current amplitude Am, phase Φ, average value Avg, change rate r, growth rate v and unbalance rate u of three phases A, B and C, and constructing a characteristic vector of the sheath current; S03), statistically analyzing and storing the extracted characteristic parameters; S04) Analyze the cable operation status according to the set threshold parameters and historical data comparison, which is divided into normal operation status and fault status. The fault status sets different level thresholds according to the severity, and is divided into warning and serious status, and different disposal strategies are given. In the warning status, the monitoring frequency is increased, and 24-hour continuous tracking monitoring and comparative analysis are carried out. The comparative analysis characteristic quantities include the proportion of sheath current threshold exceeding the limit, the proportion of exceeding the limit time, the increase in each power frequency cycle, the increase in amplitude / average value per minute, and the increase in three-phase imbalance rate; in the serious status, on-site maintenance and operation are carried out according to the cause of the fault; S05) Record the original waveform of the current signal for 24 hours under fault conditions for fault identification or expert diagnosis; S06) An expectation maximization clustering algorithm based on an improved Gaussian mixture model with historical data analysis is used to identify fault types. Sheath current feature vectors are used to construct five common cable fault types: cable overload, cable break, loose cable joints, cross-connection box flooding, and cable joint prefabricated component breakdown. Feature areas are divided according to feature vectors of various discharge types. The monitoring samples are tested using a classification model to achieve preliminary fault diagnosis and give the probability of the fault type. Based on the feature vectors of the continuous monitoring data within 24 hours in step 4, a horizontal comparative analysis is performed to correct the fault type and its probability.

2. The XLPE cable sheath current online monitoring and fault diagnosis system according to claim 1 is characterized in that: The current acquisition module includes a current acquisition circuit and an electric energy acquisition chip. The current acquisition circuit includes resistors R20, R21, R22, R122 and capacitors C35 and C36. The resistor R21 is connected between the positive input terminal of the sheath current and the positive output terminal of the circuit, the resistor R22 is connected between the negative input terminal of the sheath current and the negative output terminal of the circuit, the resistor R122 is connected between the negative input terminal of the sheath circuit and the ground, the resistor R20 is connected between the positive input terminal of the sheath current and the negative input terminal of the sheath current, the capacitors C35 and C36 are connected in series between the positive output terminal and the negative output terminal of the circuit, and the capacitor C35 and the capacitor C36 are grounded, the positive input terminal and the negative input terminal of the sheath current are connected to the output terminal of the current sensor, and the positive output terminal and the negative output terminal of the current acquisition circuit are connected to the input terminal of the electric energy acquisition chip.

3. The XLPE cable sheath current online monitoring and fault diagnosis system according to claim 2 is characterized in that: A power supply control circuit is provided between the MCU main control module and the power collection chip. The power supply control circuit includes a transistor V1, an inductor L3, a capacitor C95 and a resistor R37. The POWER_CTRL end of the MCU main control module is connected to the base of the transistor V1, the 3.3V voltage source is connected to the collector of the transistor V1, and the emitter of the transistor V1 is connected to the power supply pin of the power collection chip through the inductor L3. One end of the inductor L3 connected to the power supply pin of the power collection chip is grounded through the capacitor C95, and the capacitor C95 is grounded through the resistor R37.

4. The XLPE cable sheath current online monitoring and fault diagnosis system according to claim 1, characterized in that: The communication module includes LC optical port communication, RJ-45 network port communication and RS485 serial port communication.

5. The XLPE cable sheath current online monitoring and fault diagnosis system according to claim 4 is characterized in that: RS485 serial communication adopts RS485 communication circuit with self-transceiver control, including isolation chip, RS485 transceiver chip and filtering protection circuit. The transceiver port of the isolation chip is connected to the transceiver port of the MCU main control module. The output end of the isolation chip is connected to the input end of the RS485 transceiver chip through resistor R43 and transistor Q4. The filtering protection circuit includes TVS device D30, TVS device D31 and common mode filter T4. Common mode filter T4 is connected after the 485A and 485B pins of the RS485 chip. The RS485 transceiver interface J7 connected to the monitoring platform is led out between the common mode filter T4 and TVS devices D30 and D31.

6. The XLPE cable sheath current online monitoring and fault diagnosis system according to claim 1, characterized in that: Multiple online monitoring devices use optical fiber ring network communication to upload data to the main station system via the core switch.

7. The XLPE cable sheath current online monitoring and fault diagnosis system according to claim 1 is characterized in that: The current sensor adopts an outdoor split-type current transformer.

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