Intelligent monitoring method, device and system for partial discharge of high-voltage cable of transformer substation

Abstract

The invention provides a transformer substation high-voltage cable partial discharge intelligent monitoring method, device and system. The method comprises the steps that pulse current signals of any one or more of a high-voltage cable of a transformer substation, a ground wire of the high-voltage cable and a neutral point wiring of the high-voltage cable are acquired; analyzing a phase-amplitude distribution map and a phase resolution pulse sequence map of the pulse current signal, determining whether the high-voltage cable discharges or not and a discharge type according to the phase-amplitude distribution map, and determining an insulation degradation process of the high-voltage cable according to the phase resolution pulse sequence map; monitoring results are displayed through the upper computer, and man-machine interaction is achieved. According to the scheme, the partial discharge condition of the high-voltage cable of the transformer substation can be monitored in real time, the insulation level and the degradation degree of the cable can be intelligently evaluated, meanwhile, fault diagnosis is carried out, the operation and maintenance work of the high-voltage cable is changed from passive to active, productivity is liberated, the management level is improved, and meanwhile the personal safety of operation and maintenance personnel is better guaranteed.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of transformer substations, and particularly relates to a method, device and system for intelligently monitoring partial discharge of high-voltage cables in a transformer substation. BACKGROUND

[0002] At present, power cables are core equipment for power transmission and play an important role in safe operation of the entire power system. The performance and operating state of the power cables are directly related to the safety of power production. With the rapid development of urban construction and power distribution networks, the laying of high-voltage power distribution cables is growing rapidly. Influenced by various factors such as production and installation technology, maintenance, and environment, and with the increase of the service life of the cables, the insulation performance of the cables will inevitably deteriorate, and even potential damage will occur, resulting in partial discharge. The damage of partial discharge to the cable insulation is a slow development process, which will also lead to an increase in the number of partial discharges and discharge capacity as the insulation and dielectric are damaged, thus forming a vicious cycle. If not handled in time, the cable insulation will eventually break down, causing failure and even a major safety accident.

[0003] The environment in a transformer substation is complex, and there are many electrical devices. Currently, the detection and repair of partial discharge of cables in a transformer substation mainly adopt a traditional management mode, i.e., regular disassembly and maintenance. Due to the long detection cycle, power outage during detection, long detection time, and large workload, real-time monitoring of the devices cannot be guaranteed, and the operation and management requirements of modern devices cannot be met. SUMMARY

[0004] Therefore, the present application aims to at least solve one of the above technical problems in the prior art. Through online intelligent monitoring of partial discharge of high-voltage cables in a transformer substation, the insulation level and degradation of the cables are evaluated, and fault diagnosis is performed, so that the operation and maintenance of high-voltage cables are changed from passive to active, the safety of operation and maintenance personnel is further ensured, production is liberated, and the management level is improved.

[0005] To achieve the above purpose, the present application provides the following technical solutions: A method for intelligently monitoring partial discharge of high-voltage cables in a transformer substation, characterized in that the intelligent monitoring method comprises: acquiring a pulse current signal of any one or more of a high-voltage cable, a grounding wire of the high-voltage cable, and a neutral point connection of the high-voltage cable in a transformer substation; analyzing a phase-amplitude distribution map and a phase-resolved pulse sequence map of the pulse current signal, determining whether the high-voltage cable discharges and the discharge type according to the phase-amplitude distribution map, and determining the insulation degradation process of the high-voltage cable according to the phase-resolved pulse sequence map; displaying the monitoring results and human-computer interaction through an upper computer.

[0006] Optionally, a high-voltage cable insulation degradation degree prediction model is constructed, and the obtained pulse current signal is sent to the high-voltage cable insulation degradation degree prediction model, the high-voltage cable insulation degradation degree prediction model extracts multi-dimensional features of the pulse current signal and further identifies a corresponding high-voltage cable insulation degradation mode.

[0007] In a second aspect, an embodiment of the present application provides a substation high-voltage cable partial discharge intelligent monitoring device, comprising: a monitoring module configured to detect a pulse current signal of any one or more of a high-voltage cable, a grounding wire of the high-voltage cable, and a neutral point connection of the high-voltage cable in a substation; an Internet of Things concentrator connected to the monitoring module, configured to receive the detected pulse current signal from the monitoring module and perform analysis, calculation, and storage; a host computer connected to the Internet of Things concentrator, configured to display monitoring results and perform human-computer interaction.

[0008] Optionally, the monitoring module comprises a high-frequency current transformer, which is arranged on a connecting cable between a transformer and a high-voltage cabinet in a substation and configured to collect a pulse current signal of any one or more of A, B, and C three-phase cable bodies, a grounding wire, and a neutral point connection of the connecting cable.

[0009] Optionally, the high-frequency current transformer comprises a magnetic core, a Rogowski coil, a filter unit, a sampling unit, and an electromagnetic shielding box. The Rogowski coil is wound around the magnetic core, and the Rogowski coil, the filter unit, and the sampling unit are installed in the electromagnetic shielding box.

[0010] Optionally, the high-frequency current transformer is buckled to a detection part of the connecting cable in an open CT mounting mode.

[0011] Optionally, the Internet of Things concentrator analyzes a phase-amplitude distribution map and a phase-resolved pulse sequence map of the pulse current signal, determines whether the high-voltage cable discharges and a discharge type according to the phase-amplitude distribution map, and determines an insulation degradation process of the high-voltage cable according to the phase-resolved pulse sequence map.

[0012] Optionally, the Internet of Things concentrator comprises a high-voltage cable insulation degradation degree prediction model provided with multiple high-voltage cable insulation degradation modes, the high-voltage cable insulation degradation degree prediction model extracts multi-dimensional features of the pulse current signal and further identifies a corresponding high-voltage cable insulation degradation mode.

[0013] Optionally, the intelligent monitoring device further comprises a signal preprocessing module, the signal preprocessing module comprises a signal amplification unit and a signal filtering unit connected in sequence; The signal amplification unit is connected with the output end of the monitoring module, and the signal filtering unit is connected with the input end of the Internet of Things concentrator.

[0014] In a third aspect, the embodiment of the present application provides a substation high-voltage cable partial discharge intelligent monitoring system, which comprises a transformer, a switch cabinet and a high-voltage cable, and comprises the above-mentioned substation high-voltage cable partial discharge intelligent monitoring device.

[0015] In the embodiment of the present application, the pulse current signal of the high-voltage cable can be detected in real time, which is not limited by time, place, environment and the like, and there is no subjective error of artificial detection. The partial discharge monitoring is more timely and accurate, and manpower and material resources are saved. At the same time, the collected pulse current signal is wirelessly transmitted to the Internet of Things concentrator, so that the multiple high-voltage cables of the substation can be monitored at the same time. In addition, through the upper computer, the staff can diagnose and operate in real time. Therefore, in the embodiment of the present application, the partial discharge condition of the high-voltage cable of the substation can be monitored in real time, the insulation level and the degradation degree of the cable can be intelligently evaluated, and fault diagnosis can be performed, so that the operation and maintenance work of the high-voltage cable is changed from passive to active, the productivity is liberated, the management level is improved, and the personal safety of the operation and maintenance personnel is better ensured. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of the provided drawings.

[0017] Figure 1 is a flow chart of the intelligent monitoring method provided by an embodiment of the present application; Figure 2 is a structural schematic diagram of the intelligent monitoring device provided by another embodiment of the present application; Figure 3 is a structural schematic diagram of the intelligent monitoring device provided by another embodiment of the present application.

[0018] In Figures 1-3 , the following are provided: 1, monitoring module; 11, high-frequency current transformer; 2, Internet of Things concentrator; 3, upper computer; 4, signal preprocessing module; 41, signal amplification unit; 42, signal filtering unit. DETAILED DESCRIPTION

[0019] Embodiments of the present application are described below in detail with reference to the accompanying drawings, wherein the same or similar components or components having the same or similar functions are denoted by the same or similar reference numerals throughout. The embodiments described below by reference to the accompanying drawings are exemplary and are for the purpose of explaining the present application only, and are not to be construed as limiting the present application.

[0020] In the description of the present application, it should be understood that the orientation description, such as the orientation or position relationship indicated by up, down, front, back, left, right, etc., is based on the orientation or position relationship shown in the drawings, and is only for the purpose of facilitating the description of the present application and simplifying the description, and therefore cannot be understood as limiting the present application, which indicates or implies that the device or component referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0021] In the description of the present application, the meaning of several is one or more, the meaning of multiple is more than two, greater than, less than, more than, etc. are understood to exclude the number, above, below, etc. are understood to include the number. If the first, second is described, it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of technical features indicated.

[0022] In the description of the present application, unless otherwise explicitly limited, the words such as "arrangement", "installation", "connection" should be broadly understood, for example, "connection" includes but is not limited to physical connection, electrical connection, signal connection, etc., and the specific meaning of the above words in the present application can be reasonably determined by the person skilled in the art in combination with the specific content of the technical solution.

[0023] Reference Figure 1 The embodiment of the present application provides a kind of intelligent monitoring method for substation high voltage cable partial discharge, which includes but is not limited to steps S10, S20 and S30.

[0024] S10, the pulse current signal of any one or more of the high voltage cable, the grounding wire of high voltage cable, the neutral point connection of high voltage cable of substation is acquired.

[0025] It should be noted that the present embodiment selects the high voltage cable of transformer to high voltage cabinet 35kV in substation for partial discharge on-line monitoring, according to the monitoring in the working process of substation for many years, the cable here is more prone to aging, and the probability of generating partial discharge is higher. A set of cable partial discharge on-line monitoring device can be deployed at the cable terminal of transformer cabinet of high voltage cabinet in substation room, and the partial discharge sensor is installed on the three-phase cable body and grounding wire in high voltage switch cabinet to monitor the pulse current signal generated when monitoring cable partial discharge, so as to facilitate observation of partial discharge on-line monitoring result.

[0026] When partial discharge occurs in the insulation layer of the cable, the rapidly changing charge in the discharge channel forms nanosecond pulse currents between the conductor and the shielding layer, which propagate along the outer shielding layer or ground wire of the cable. The partial discharge sensor transmits the collected pulse current signals to the downstream device through wireless LORA.

[0027] S20, analyze the phase-amplitude distribution map and the phase-resolved pulse sequence map of the pulse current signal, determine whether the high-voltage cable is discharging and the type of discharge according to the phase-amplitude distribution map, and determine the insulation deterioration process of the high-voltage cable according to the phase-resolved pulse sequence map.

[0028] The embodiment first analyzes the phase-amplitude distribution map (PRPD) of the pulse current signal. The PRPD is a two-dimensional map, the X-axis is the power frequency phase angle (0-360°), the Y-axis is the discharge amplitude (pC), each point represents a discharge event, and the discharge frequency is represented by color or brightness using the density map mode. If the PRPD map is uniformly distributed, it is judged to be a healthy cable; if there is a phase aggregation phenomenon, such as the formation of characteristic discharge clusters near 90° and 270°, that is, the formation of symmetric peaks near 90° and 270°, it is judged to be an aging cable, and the discharge type is corona discharge; in addition, if there is an asymmetric cluster, it is judged to be an aging cable, and the discharge type is surface discharge. After judging to be an aging cable through the PRPD map, further analyze the phase-resolved pulse sequence map (PRPS) of the pulse current signal. The PRPS is a three-dimensional map, the X-axis is the power frequency phase angle (0-360°), the Y-axis is the discharge amplitude (pC), and the Z-axis is the time sequence, which is used to show the continuity and dynamic change of the discharge pulse. The discharge of the aging cable usually presents a continuous deterioration in the time dimension, such as increasing pulse intensity or phase distribution spreading. By observing the evolution of discharge intensity and phase distribution over time (such as amplitude increasing due to aging) through the PRPS map, the stability of the discharge can be confirmed, such as continuous deterioration or sporadic noise.

[0029] For example, in the case of air gap discharge, the phase distribution is symmetric in the PRPS, but the amplitude increases over time, reflecting the expansion of the internal air gap of the insulation. In the case of surface discharge, the phase is asymmetric and the pulse cluster gradually intensifies, corresponding to the expansion of the insulation surface crack. By observing the repeatability and amplitude change of the discharge pulse on the time axis of the PRPS, if the discharge frequency or intensity shows an upward trend, it indicates that the insulation is accelerating deterioration. In addition, aging cables often have mixed discharges (such as air gap + surface discharge), and PRPS can separate the time evolution characteristics of different discharge modes. In other optional embodiments, for the aging judgment of the cable, a high-voltage cable insulation deterioration degree prediction model is constructed, which comprises the following steps: first, random forest or support vector machine (SVM) is used for defect classification, and through feature importance analysis, it can be found that pulse rise time and discharge amplitude have the highest contribution to air gap defect identification; second, long short-term memory network (LSTM) is used to process time sequence features, and its gating mechanism can effectively capture the dynamic evolution law of discharge frequency, phase distribution and other parameters; and finally, an insulation deterioration degree prediction model is constructed through XGBoost integrated learning. The high-voltage cable insulation deterioration degree prediction model extracts multi-dimensional feature data of pulse current signals, and realizes accurate prediction of the insulation deterioration degree of the high-voltage cable through pattern recognition.

[0030] S30, display the monitoring result and human-computer interaction through the upper computer.

[0031] The upper computer 3 is connected with the Internet of Things concentrator 2, has a human-computer interface, and is used for displaying the monitoring result and human-computer interaction.

[0032] The substation high-voltage cable partial discharge intelligent monitoring method of the embodiment of the application is applied to a substation high-voltage cable partial discharge intelligent monitoring device, and the intelligent monitoring device is composed of a cable partial discharge sensing part (a monitoring module 1, i.e., a perception layer), a convergence operation forwarding part (an Internet of Things concentrator 2, i.e., a network layer), and a background monitoring part (an upper computer 3, i.e., a service layer). The perception layer is mainly responsible for the collection and transmission of partial discharge signals, the network layer is mainly responsible for collecting the partial discharge data collected by the sensing device through wireless communication and realizing the analysis, calculation, transparent transmission, and instruction forwarding of the data, and the service layer is mainly responsible for the display, storage, and output of relevant analysis and statistics of the data calculation results. Through testing, the intelligent monitoring method can early warn the insulation deterioration of the high-voltage cable for more than 8 months, reduce the failure rate by more than 40%, and effectively realize the state evaluation of the cable from passive maintenance to active prevention.

[0033] As shown in Figure 2 The embodiment of the application provides a substation high-voltage cable partial discharge intelligent monitoring device, which comprises a monitoring module 1, an Internet of Things concentrator 2, and an upper computer 3.

[0034] The monitoring module 1 is used for detecting the pulse current signals of any one or more of the high-voltage cable, the grounding wire, and the neutral point connection of the substation. When partial discharge occurs in the insulation layer of the cable, the rapidly changing charges in the discharge channel will form nanosecond pulse current between the conductor and the shielding layer, and the pulse current will propagate along the outer shielding layer or the grounding wire of the cable. The monitoring module 1 is provided with a sensor, and the sensor transmits the collected pulse current signals to the Internet of Things concentrator 2 through wireless LORA.

[0035] The IoT concentrator 2, with its input end connected to the output end of the monitoring module 1, receives the pulse current signal detected by the monitoring module 1 and performs analysis, calculation, and storage. As a relay device between the monitoring module 1 and the host computer 3, it has the functions of self-organizing a network and sensor terminal access. After receiving the detected pulse current signal from the monitoring module 1, it performs edge-side calculation, analysis, and storage of raw and newly generated data, realizing intelligent reception and transparent transmission of partial discharge sensor data and command forwarding. The IoT concentrator 2 is installed around the partial discharge sensor, typically wall-mounted.

[0036] For example, an IoT concentrator 2 can be installed in the substation switchgear room. It can be box-type or shell-type. It serves as a relay device for communication between the online monitoring sensors for partial discharge of high voltage cables in the substation, and is also an edge gateway. It has the functions of self-organizing network and partial discharge sensor terminal access, realizes the reception and transparent transmission of partial discharge sensor data and command forwarding, and also has the functions of edge-side computing and analysis.

[0037] The host computer 3 is connected to the IoT concentrator 2 and has a human-machine interface for displaying monitoring results and human-machine interaction.

[0038] In this embodiment, partial discharge (PD) monitoring is primarily conducted on the 35kV high-voltage cable from the transformer to the high-voltage switchgear in a substation. Based on the characteristics of cable PD, when a partial discharge occurs inside the cable, a high-frequency current signal is generated, which propagates along the cable's outer shield or grounding wire. The intelligent monitoring device consists of three parts: a cable PD sensing section (monitoring module 1, i.e., the sensing layer), a convergence and forwarding section (IoT concentrator 2, i.e., the network layer), and a background monitoring section (host computer 3, i.e., the service layer). The sensing layer is mainly responsible for the acquisition and transmission of PD signals; the network layer mainly collects PD data from the sensing devices via wireless communication and performs data analysis, calculation, transmission, and command forwarding; the service layer mainly displays and stores the data calculation results and outputs relevant analysis and statistics. Testing shows that this intelligent monitoring device can provide early warning of high-voltage cable insulation degradation more than eight months in advance, reducing the failure rate by more than 40%, effectively shifting cable condition assessment from passive maintenance to proactive prevention.

[0039] like Figure 3 As shown, in a preferred embodiment, the partial discharge sensor in monitoring module 1 is a high-frequency current transformer 11 (HFCT). The sensor collects pulse current signals from any one or more of the A, B, and C phases of the connecting cable between the transformer and the high-voltage switchgear, the grounding wire, and the neutral point connection. Based on IoT and wireless low-power technology, the HFCT has advantages such as high sensitivity, wide bandwidth, and strong anti-interference capability. By detecting the discharge pulse current signal in the cable and its grounding wire or neutral point connection, it can accurately capture the high-frequency current pulses generated by partial discharge.

[0040] It should be noted that the high-frequency current transformer 11 (HFCT) is composed of a magnetic core, a Rogowski coil, a filter unit, a sampling unit, and an electromagnetic shielding box. The Rogowski coil is wound around the magnetic core which has high permeability at high frequency; the design of the filter unit and the sampling unit takes into account the requirements of measurement sensitivity and signal response frequency band; the Rogowski coil, the filter unit, and the sampling unit are all installed in the electromagnetic shielding box, which can suppress interference and improve signal-to-noise ratio on the one hand, and can also prevent rain and dust, improving safety on the other hand.

[0041] It should be noted that the electromagnetic shielding box shell is designed with a self-locking buckle, which can be opened by pressing, greatly improving the convenience of sensor installation and safety during operation.

[0042] It should be noted that the high-frequency current transformer 11 is installed in an open CT manner, directly clamped on the A, B, C three-phase cable bodies and ground wire of the cable to be measured, detects the pulse current signal generated by partial discharge, and further obtains the partial discharge information of the device being detected. Non-contact detection is achieved, avoiding interference to the main circuit of the cable and improving detection safety.

[0043] The technical parameters of the high-frequency current transformer 11 (HFCT) are as follows: Frequency range: 0.5-30MHz Measurement range: 0-70dB Bandwidth: ≥2MHz Sensor size: inner diameter ≈ 56mm Transmission impedance: ≥6.5mV / mA Sensitivity: minimum measurable partial discharge amount not greater than 50pC Linearity error: ≤±10 (dynamic range 40dB) Detection range: 100pC-10nC Operating temperature: -40-70℃ Operating humidity: 5-95%RH.

[0044] In a preferred embodiment, the Internet of Things concentrator 2 has 4G, RS485, RJ45, and optical fiber interfaces, supports Modbus, IEC61850, and other protocols, receives data monitored by the partial discharge sensor, analyzes the partial discharge map, and discriminates and warns possible insulation defects.

[0045] The related parameters of the Internet of Things concentrator 2 are as follows: Rated voltage frequency: 100-240VAC, 501z / 60Hz Power consumption: s13w Downlink communication mode: wireless LORA, 4G / 5G, RS485, Ethernet Uplink communication methods: RS485, Ethernet, fiber optic, 4G Uplink communication protocols: MQTT, HTTP, Modbus, EC61850, etc. RS485 communication baud rate: minimum measurable partial discharge quantity not greater than 50pC.

[0046] It should be noted that the IoT concentrator 2 first analyzes the phase-amplitude distribution map (PRPD) of the pulse current signal. The PRPD is a two-dimensional map, with the X-axis representing the power frequency phase angle (0-360°) and the Y-axis representing the discharge amplitude (pC). Each point represents a discharge event, and the discharge frequency is represented by color or brightness using a density map pattern. If the PRPD map shows a uniform distribution, it is judged to be a healthy cable. If phase clustering occurs, such as the formation of characteristic discharge clusters near 90° and 270° (i.e., symmetrical peaks near 90° and 270°), it is judged to be an aging cable, and the discharge type is corona discharge. In addition, if asymmetrical clusters occur, it is judged to be an aging cable, and the discharge type is surface discharge. After identifying the cable as aged using PRPD (Pulse Phase Resolved Pulse Diagram), further analysis of the PRPS is conducted. PRPS is a three-dimensional graph, with the X-axis representing the power frequency phase angle (0-360°), the Y-axis representing the discharge amplitude (pC), and the Z-axis representing the time series. It displays the continuity and dynamic changes of the discharge pulses. The discharge of aged cables typically exhibits a continuous deterioration over time, such as increasing pulse intensity or phase distribution diffusion. By observing the evolution of discharge intensity and phase distribution over time using the PRPS graph (e.g., amplitude increases due to aging), the stability of the discharge can be confirmed, such as continuous deterioration or intermittent noise.

[0047] In other optional embodiments, for judging cable aging, the IoT concentrator 2 constructs a prediction model for the degree of insulation degradation of high-voltage cables, including: first, using random forest or support vector machine (SVM) for defect classification, and through feature importance analysis, it can be found that pulse rise time and discharge amplitude contribute the most to air gap defect identification; second, using long short-term memory network (LSTM) to process temporal features, its gating mechanism can effectively capture the dynamic evolution of parameters such as discharge frequency and phase distribution; finally, constructing an insulation degradation prediction model through XGBoost ensemble learning. The high-voltage cable insulation degradation prediction model extracts multi-dimensional feature data of pulse current signals and achieves accurate prediction of the degree of insulation degradation of high-voltage cables through pattern recognition.

[0048] It should be noted that the IoT concentrator 2 can further predict the degradation trend of the cable's insulation performance and its remaining service life by combining data parameters such as the target high-voltage cable's operating time, current insulation degradation level, and operating environment. The host computer 3 is used to display the monitoring results, namely the insulation degradation level and estimated remaining service life of the target high-voltage cable. Of course, the above data parameters are not exhaustive and can be appropriately added or removed according to the application field / scenario of the high-voltage cable.

[0049] In a preferred embodiment, the display interface of the host computer 3 is interactive, and staff can perform relevant operations and settings through the interactive interface. The system can set up timed automatic partial discharge intelligent monitoring or manual command partial discharge monitoring.

[0050] The host computer (HPC) 3 includes system backend software that utilizes internet access technology and features real-time data display capabilities. It can display real-time information such as partial discharge status of high-voltage cables in the monitored substation, cable degradation level, and remaining service life, allowing users to detect anomalies immediately. Simultaneously, users can remotely control, diagnose, query, and access the substation through the system backend software. They can query historical data and perform trend analysis. Furthermore, the system backend software can automatically capture and record partial discharge signals that trigger alarms and can automatically save dynamic events.

[0051] The host computer 3 has management access control, and access permissions can be set via fingerprint, password, face recognition, etc.

[0052] Furthermore, it also has a hierarchical management permission system, with different levels of management permissions corresponding to different data access scopes, data read and write permissions, and operating space.

[0053] It should be noted that the host computer 3 can also be equipped with an alarm device. If the insulation degradation of the target high-voltage cable exceeds the safety threshold and needs to be replaced immediately, the alarm mechanism will be triggered.

[0054] In this embodiment, the host computer 3 system background software has comprehensive functions, is easy to operate, and is fully digitally displayed, making the interface more intuitive and user-friendly.

[0055] In a preferred embodiment, the intelligent monitoring device for partial discharge of high-voltage cables in substations further includes a signal preprocessing module 4, which comprises a signal amplification unit 41 and a signal filtering unit 42 connected in sequence. The input terminal of the signal amplification unit 41 is connected to the output terminal of the monitoring module 1, and is used to amplify the pulse current signal output by the high-frequency current transformer 11, without exceeding the system range. The input terminal of the signal filtering unit 42 is connected to the output terminal of the signal amplification unit 41, and the output terminal of the signal filtering unit 42 is connected to the input terminal of the IoT concentrator 2, and is used to filter external interference signals, i.e., using a high-pass circuit to effectively avoid interference signals in order to obtain the partial discharge signal. In this embodiment, by setting the signal preprocessing module 4, the accuracy and efficiency of partial discharge monitoring are improved.

[0056] This application also provides an intelligent monitoring system for partial discharge of high-voltage cables in substations, including a transformer, switchgear and high-voltage cables, and the aforementioned intelligent monitoring device for partial discharge of high-voltage cables in substations.

[0057] This application also provides an intelligent monitoring and linkage system for partial discharge of high-voltage cables in substations. It includes at least two intelligent monitoring systems, each capable of independent operation and recording data separately. Data from multiple intelligent monitoring systems is transmitted via a single data communication bus to a unified management and analysis system on a backend analysis software platform. Remote transmission and real-time monitoring are achieved via the internet, enabling real-time online analysis of the intensity and density of partial discharge signals. A single backend analysis software platform allows for real-time monitoring and analysis of the shifting partial discharge tendencies in multiple substations, assessing the degree of discharge and preventing major accidents.

[0058] The above provides a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A method for intelligent monitoring of partial discharge in high-voltage cables of substations, characterized in that, Intelligent monitoring methods include: Acquire pulse current signals from any one or more of the high-voltage cable of the substation, the grounding wire of the high-voltage cable, and the neutral point connection of the high-voltage cable. Analyze the phase-amplitude distribution spectrum and phase-resolved pulse sequence spectrum of the pulse current signal. Determine whether the high-voltage cable is discharging and the type of discharge based on the phase-amplitude distribution spectrum. Determine the insulation degradation process of the high-voltage cable based on the phase-resolved pulse sequence spectrum. The monitoring results are displayed on the host computer, and human-computer interaction is also possible.

2. The intelligent monitoring method according to claim 1, characterized in that, A high-voltage cable insulation degradation prediction model is constructed. The acquired pulse current signal is sent to the high-voltage cable insulation degradation prediction model. The high-voltage cable insulation degradation prediction model extracts the multidimensional features of the pulse current signal and further identifies the corresponding high-voltage cable insulation degradation mode.

3. A smart monitoring device for partial discharge of high-voltage cables in substations, characterized in that, include: The monitoring module is used to detect the pulse current signal of any one or more of the high-voltage cable, the grounding wire of the high-voltage cable, and the neutral point connection of the high-voltage cable in the substation. An IoT concentrator, connected to the monitoring module, is used to receive detected pulse current signals from the monitoring module and perform analysis, calculation, and storage. The host computer is connected to the IoT concentrator and is used to display monitoring results and facilitate human-computer interaction.

4. The intelligent monitoring device according to claim 3, characterized in that, The monitoring module includes a high-frequency current transformer, which is installed on the connecting cable between the transformer and the high-voltage switchgear in the substation. It is used to collect the pulse current signal of any one or more of the three phases (A, B, and C) of the connecting cable, the grounding wire, and the neutral point connection.

5. The intelligent monitoring device according to claim 4, characterized in that, The high-frequency current transformer includes a magnetic core, a Rogowski coil, a filtering unit, a sampling unit, and an electromagnetic shielding box. The Rogowski coil is wound around the magnetic core, and the Rogowski coil, the filtering unit, and the sampling unit are all installed in the electromagnetic shielding box.

6. The intelligent monitoring device according to claim 4 or 5, characterized in that, The high-frequency current transformer is an open-type CT that is snapped onto the detection part of the connecting cable.

7. The intelligent monitoring device according to claim 3, characterized in that, The IoT concentrator analyzes the phase-amplitude distribution spectrum and phase-resolved pulse sequence spectrum of the pulse current signal, determines whether the high-voltage cable is discharging and the type of discharge based on the phase-amplitude distribution spectrum, and determines the insulation degradation process of the high-voltage cable based on the phase-resolved pulse sequence spectrum.

8. The intelligent monitoring device according to claim 3, characterized in that, The IoT concentrator includes a high-voltage cable insulation degradation prediction model with multiple high-voltage cable insulation degradation modes. The high-voltage cable insulation degradation prediction model extracts multi-dimensional features of the pulse current signal and further identifies the corresponding high-voltage cable insulation degradation modes.

9. The intelligent monitoring device according to claim 3, characterized in that, The intelligent monitoring device also includes a signal preprocessing module, which includes a signal amplification unit and a signal filtering unit connected in sequence. The signal amplification unit is connected to the output of the monitoring module, and the signal filtering unit is connected to the input of the IoT concentrator.

10. A substation high-voltage cable partial discharge intelligent monitoring system, comprising a transformer, switchgear, and high-voltage cable, characterized in that: A substation high-voltage cable partial discharge intelligent monitoring device is provided as described in any one of claims 3 to 9.

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