CN-121984212-A - Multifunctional intelligent monitoring system and early warning method for insulating soft suspender

CN121984212ACN 121984212 ACN121984212 ACN 121984212ACN-121984212-A

Abstract

The invention provides a multifunctional intelligent monitoring system and an early warning method for an insulating soft sling, belongs to the technical field of power safety equipment, and solves the technical problems that an existing insulating sling is single in monitoring parameter, weak in anti-interference capability, incapable of early warning, predictive maintenance and the like. Comprises a sensing layer, a transmission layer, a processing layer and a management layer. The early warning method comprises a real-time monitoring early warning method and an analog early warning method. The intelligent closed loop covering the whole life cycle is constructed, the traditional manual management mode is changed from real-time monitoring, digital twin simulation to automatic maintenance decision, high fidelity of monitoring data and long-term reliability of the system in a severe environment are ensured through a flexible sensing design and anti-interference mechanism, early warning and optimal maintenance strategy recommendation are realized by utilizing an intelligent algorithm, and the operation and maintenance efficiency is optimized while the safety is improved. The method realizes intelligent early warning of active prediction and decision support by constructing a complete cooperative early warning system and combining real-time response and digital twin prediction.

Inventors

WANG SHENLI
HU HONGWEI
CHEN WEN
DUAN PENG
WANG JIAN
ZHANG WEI
LI JUN
Zhu Manni
DONG QIONG

Assignees

湖北省超能电力有限责任公司
国网湖北省电力有限公司超高压公司

Dates

Publication Date: 20260505
Application Date: 20251224

Claims (10)

1. The multifunctional intelligent monitoring system comprises a sensing layer, a transmission layer, a processing layer and a management layer, and is characterized in that the sensing layer comprises a flexible sensing module, a state monitoring module and an environment adaptation module, the transmission layer comprises a data acquisition module, a wireless communication module and an edge processing module, the processing layer comprises a digital twin module and an intelligent early warning module, and the management layer comprises a full-period archive module and a maintenance decision module; The flexible sensing module is used for measuring tension and strain parameters in real time, the state monitoring module is used for evaluating the insulation health of hanging strips through a distributed anti-interference design, monitoring insulation resistance, leakage current and dielectric parameters in real time, the environment adapting module is used for enhancing robustness of the system under severe working conditions, the data acquisition module is used for synchronously converging and intelligently acquiring multichannel signals, the wireless communication module is used for monitoring reliable and safe transmission of data, the edge processing module is used for locally preprocessing and caching the data in real time, the digital twin module is used for establishing a high-fidelity three-dimensional digital twin body for each hanging strip, the stress distribution, the deformation state and the insulation aging process of the physical hanging strips are dynamically simulated and mapped through real-time data driving, the intelligent early warning module is used for intelligent judging and grading alarming based on multi-source data fusion, the full-period archive module is used for managing full-life-period data of the hanging strips, and the maintenance decision module is used for predictively supporting maintenance based on the health state.
2. The multifunctional intelligent monitoring system of the insulated soft sling according to claim 1, wherein the flexible sensing module is composed of a plurality of sensing units distributed along the axial direction of the sling at equal intervals, the core of each sensing unit is a porous net-shaped laser-induced graphene conductive layer, the sensing units and the sling body deform cooperatively under the working conditions of repeated stretching, bending and torsion, no interface slipping phenomenon is caused, the strain transmission efficiency is more than or equal to 95%, high-fidelity axial tension signals and local micro-strain signals are synchronously output, and the sampling frequency can be adaptively adjusted within the range of 0.1Hz to 10kHz according to instructions; The state monitoring module consists of a plurality of monitoring nodes which are distributed and implanted into an insulating layer of the hanging strip, each monitoring node comprises a pair of micro-ring electrodes and is used for measuring loss factors and equivalent capacitances of a hanging strip medium through electric field coupling in a passive mode, deriving insulating resistance parameters through dielectric losses and equivalent capacitances and sensitively reflecting early wetting and aging, meanwhile, each monitoring node is also integrated with a micro-Cheng Xielou current sensor based on electromagnetic induction energy taking, all the micro-ring electrodes and the micro-range leakage current sensor are covered in the insulating layer of the insulating hanging strip, the outer side of the micro-ring electrodes and the micro-range leakage current sensor are covered with a braided copper-nickel alloy shielding net, and interference current is guided through single-point grounding, so that stable measurement is realized, and extra electromagnetic interference is not introduced.
3. The multifunctional intelligent monitoring system of the insulated soft sling according to claim 2, wherein the environment adapting module consists of a digital temperature and humidity sensor and a broadband electromagnetic field probe, the temperature, the relative humidity and the space electromagnetic interference intensity of the working environment are quantified in real time to form a standardized environment data stream, the standardized environment data stream is input into a built-in environment-performance correlation model constructed based on the principles of insulation materials, dielectric physics and electromagnetic compatibility, and the environment-performance correlation model is utilized to compensate and correct the original monitoring data from the flexible sensing module and the state monitoring module in real time based on physical mechanism; The data acquisition module adopts a synchronous acquisition card based on the expansion of a sigma-delta analog-to-digital converter, is driven by a constant temperature crystal oscillator clock source, ensures that the time synchronization error of multipath mechanical, electrical and environmental signals is less than or equal to 1ms, is provided with a self-adaptive sampling controller arranged in the synchronous acquisition card, continuously monitors the change of a strain signal output by the flexible sensing module, automatically switches to a low-power sampling mode of 0.1Hz when the change rate is lower than a threshold value, instantaneously switches to a high-speed sampling mode of 10kHz when a sudden change or a preset triggering condition is detected, and recovers after an event is ended, and provides a standard I2C, SPI digital interface for accessing a digital sensor to realize parallel synchronous acquisition of analog and digital signals.
4. The multifunctional intelligent monitoring system of the insulated soft sling according to claim 3, wherein the wireless communication module adopts a LoRa remote spreading unit and a 5G industrial module, a communication strategy engine dynamically selects a link according to data priority, conventional periodic state data is transmitted through the LoRa remote spreading unit, an emergency early warning signal and high-speed dynamic waveform data are automatically switched to the link of the 5G industrial module, and all transmission data are encrypted by an AES-256 algorithm and encoded by a Base64 in hardware security chips embedded in the LoRa remote spreading unit and the 5G industrial module, so that end-to-end transmission is ensured to be in accordance with the DL/T5210.5 electric power data security specification.
5. The multifunctional intelligent monitoring system of the insulated soft sling according to claim 4, wherein the edge processing module is a microprocessor and a flash memory with an AI acceleration core, and is used for preprocessing the acquired real-time original signals, namely, sequentially carrying out DB4 wavelet three-layer decomposition and threshold denoising on the original signals, extracting time domain features and frequency domain features to generate multidimensional feature vectors, inputting the feature vectors into a lightweight convolutional neural network model, carrying out initial judgment on the local real-time state of the sling, automatically caching all original data and feature data in the flash memory when the whole process processing delay is less than or equal to 10ms, and supplementing and transmitting according to priority after network recovery, so as to ensure data continuity.
6. The multifunctional intelligent monitoring system of the insulated soft hanging strip according to claim 5, wherein the digital twin module maintains a unique high-fidelity digital twin body for each hanging strip at the cloud end, the twin body firstly forms a parameterized physical simulation engine based on a CAD geometric model and a nonlinear constitutive relation of materials, the physical model is driven to carry out dynamic simulation by continuously receiving real-time characteristic data from the edge processing module, a three-dimensional stress/strain field distribution cloud image of the whole hanging strip is output in real time, simulation results and measured data are continuously compared, material parameters in the physical model are dynamically corrected, simulation errors are always less than or equal to 2%, and mapping of the virtual body to the state of the physical hanging strip and deduction prediction of future working conditions are realized.
7. The multifunctional intelligent monitoring system of the insulated flexible hanging strip according to claim 6, wherein the full-period archive module allocates a passive RFID tag which accords with the ISO18000-6C standard as a unique digital identity to each hanging strip, the code comprises manufacturer, batch and serial number information, the ID is used as an index, a life digital archive of the hanging strip is built in a cloud distributed database, and four types of data are stored in a structured manner, and the method is as follows: static properties, namely factory material evidence, a dimension drawing and an initial electrical performance report; Dynamic operation log, namely starting and stopping time, GPS position, whole course load spectrum, environment data and associated operation ticket number of each use; health event recording, namely, detailed data snapshot, processing process and closed-loop result of all early warning events; The maintenance history, namely a preventive test report, a maintenance replacement part record and a calibration date, supports bidirectional retrieval and traceability analysis, and provides a complete data chain for insulation sling management, quality traceability and responsibility definition.
8. The multifunctional intelligent monitoring system of the insulated flexible sling according to claim 7, wherein the intelligent early warning module receives real-time characteristic data from the edge processing module, simulation prediction results of the digital twin module and data in the full-period archive module to construct a two-stage fusion frame: Firstly, dynamically distributing weights for mechanical, insulating and environmental evidences by using an entropy weight method, solving the problem of high conflict evidence fusion in a D-S evidence theory by adopting an improved Yager formula, and calculating the initial health state confidence; secondly, inputting the preliminary confidence coefficient and the residual safety coefficient of twin body prediction into an incremental long-short-period memory network model for space-time analysis, wherein the model supports online learning, fine adjustment of parameters is carried out once every 1000 groups of new data are accumulated, and finally, 0-100 comprehensive health indexes and specific risk positioning are output, and the module automatically triggers three-level early warning according to the comprehensive health indexes and descending trends: first-order emergency, comprehensive health index <60; Secondary early warning, wherein the comprehensive health index is less than or equal to 60 and less than 80, and the drop of 24 hours is more than or equal to 10; and (3) three-level prompting, namely, abnormality of the environmental parameters or identification of a specific risk mode.
9. The multifunctional intelligent monitoring system of the insulated soft hanging strip according to claim 8, wherein the maintenance decision module continuously receives the health index of the intelligent early warning module and the residual service life predicted by the digital twin module, synthesizes the current comprehensive health index, the slope of the residual service life prediction curve, the recent operation planning density and the stock condition of spare parts through a built-in decision algorithm, solves through a multi-objective optimization model in combination with the requirement of a power grid safety regulation, automatically generates and pushes an executable maintenance scheme, automatically creates a ' replacement ' work order in a power grid production management system when the system predicts that the residual service life of a certain hanging strip is less than 30 days and important maintenance tasks are carried out in two weeks in the future, recommends the optimal replacement hanging strip in the stock, and generates a work order and a time window suggestion of ' recoating and testing when the insulation performance is only detected to be close to a threshold value, and all the decision suggestions are recorded in the scheme to form a digital management closed loop of ' monitoring-early warning-decision-executing-feedback '.
10. The multifunctional intelligent early warning method of the insulating soft sling is applied to the multifunctional intelligent monitoring system of the insulating soft sling according to any one of claims 1-8, and is characterized in that the real-time monitoring early warning method and the simulation early warning method are as follows: step S1, multi-parameter synchronous acquisition and edge pretreatment: After the system is electrified, each module of the sensing layer synchronously collects parameters of tension, strain, insulation resistance, leakage current, temperature and humidity and electromagnetic field strength according to a preset cooperative strategy, and an edge processing module performs real-time wavelet transformation denoising on an original signal stream and extracts key time domain and frequency domain characteristic values; Step S2, cloud-edge collaborative research and judgment: the edge end fast response is that a lightweight CNN model running on an edge processing module analyzes the characteristic data in millisecond level, immediately triggers a local strong audible and visual alarm to inform a user once the emergency abnormality of which the parameter exceeds a hard safety threshold is identified, and sends an emergency signal through a highest priority channel of a wireless communication module; the cloud end deep analysis, namely after the edge end completes local initial judgment, uploading all the characteristic data and part of key original data to the cloud end synchronously, and calling a long-period memory network model and a D-S evidence theory fusion engine of the harness individuation by the cloud end intelligent early warning module, and carrying out deep state assessment and degradation trend analysis by combining historical file data; step S3, triggering in a multistage early warning mode, namely triggering in a stage mode according to a judging result: The first-level early warning-emergency, namely triggering the audible and visual alarm of a local monitoring center and a remote monitoring center aiming at the clear danger, automatically pushing alarm information containing operation steps for risk positioning and suggesting immediate execution, and informing corresponding staff; second-level early warning-early warning, wherein when the health index shows a definite continuous degradation trend, the system predicts the potential fault risk, and pushes early warning notification and a suggested maintenance plan to staff to prompt attention; third-stage early warning-prompting, namely when an environment sensor detects an extreme working condition or data analysis identifies an abnormal mode similar to a historical hidden fault but does not exceed a threshold value, a system pushes protective prompting suggestion; The simulation early warning method comprises the following steps: step T1, initializing and calibrating a twin body, namely initializing a digital twin body based on design parameters and factory test data of the newly used hanging belt or the hanging belt subjected to major maintenance/upgrading at a cloud end, calibrating material parameters and boundary conditions of the twin body by using actual operation monitoring data in the early stage of the digital twin body through a machine learning algorithm, ensuring that the response error of a virtual model and a physical entity under typical working conditions is less than or equal to 2%, and completing virtual-real consistency alignment; Step T2, real-time data driving and look-ahead simulation, namely continuously injecting working condition data acquired in real time into a calibrated digital twin body in daily monitoring, running simulation of the twin body at a frequency not lower than 50Hz, and not only reproducing the current state of the hanging belt in real time, but also carrying out 'hypothesis analysis' based on a preset or predicted future operation scene, and calculating stress distribution, deformation and insulation aging rate of the hanging belt in the scene in a simulation manner; And step T3, predicting the residual service life of the sling under the specified confidence level by adopting a mixed model formed by an Arrhenius accelerated aging model and a long-period memory network model based on a long-term aging data sequence of digital twin body simulation and combining a historical accumulated damage effect extracted from a full-period file, and automatically generating and pushing a personalized predictive maintenance work order by combining a residual service life prediction result with a future operation plan calendar through a maintenance decision module.

Description

Multifunctional intelligent monitoring system and early warning method for insulating soft suspender Technical Field The invention belongs to the technical field of electric power safety equipment, relates to a multifunctional intelligent monitoring system of an insulating soft sling, and in particular relates to a multifunctional intelligent monitoring system of an insulating soft sling and an early warning method. Background In the operation of installing, overhauling, emergency rescue and the like of an electric power system or nearby live bodies, the insulating soft hanging strip is a key personal safety protection and bearing tool, and the mechanical strength and the insulating performance of the insulating soft hanging strip are directly related to the personal safety of operators and the operation reliability of a power grid. Currently, the safety management of insulating harnesses is mainly dependent on the periodic preventive tests prescribed by regulations, the tension and insulation resistance tests once a half year and the manual visual inspection before the operation. The prior art means are usually isolated and passive, part of research attempts are made to integrate a resistance strain gauge or an optical fiber sensor for monitoring tensile force or spot inspection is carried out by adopting a handheld insulation resistance tester, but the methods have obvious defects that real-time, continuous and multi-parameter synchronous monitoring in the operation process cannot be realized, dynamic load impact or instant insulation degradation is difficult to capture, an active compensation mechanism for environmental interference is lacking, the robustness is poor, a management mode is extensive, state data is isolated, service life assessment based on accumulated damage cannot be realized, predictive early warning and decision support cannot be carried out, safety risks caused by hidden defects exist, and resource waste caused by premature equipment replacement is caused. Therefore, a multifunctional intelligent monitoring system and an early warning method of the insulating soft hanging strip are provided. Disclosure of Invention The invention aims at solving the problems of the prior art and provides a multifunctional intelligent monitoring system and an early warning method of an insulating soft sling, and the technical problems to be solved by the invention are how to realize real-time, high-fidelity and anti-interference on-line monitoring of the mechanics and the insulating state of the insulating soft sling, and construct a full life cycle closed-loop management system integrating digital twin simulation, intelligent health state assessment, residual life prediction and maintenance decision automatic generation, so that the traditional periodic test and passive response modes are converted into intelligent management modes of active early warning and predictive maintenance. The aim of the invention can be achieved by the following technical scheme: The multifunctional intelligent monitoring system comprises a sensing layer, a transmission layer, a processing layer and a management layer, wherein the sensing layer comprises a flexible sensing module, a state monitoring module and an environment adapting module, the transmission layer comprises a data acquisition module, a wireless communication module and an edge processing module, the processing layer comprises a digital twin module and an intelligent early warning module, the management layer comprises a full-period archive module and a maintenance decision module, the flexible sensing module measures tensile force and strain parameters in real time, the state monitoring module evaluates the insulation health of the hanging strip through a distributed anti-interference design, monitors insulation resistance, leakage current and dielectric parameters in real time, the environment adapting module is responsible for enhancing the robustness of the system under severe working conditions, the data acquisition module is responsible for gathering and intelligent acquisition of multichannel signals, the wireless communication module is responsible for reliable and safe transmission of monitoring data, the edge processing module is responsible for local real-time preprocessing and buffering of data, the digital twin module is used for establishing a high-fidelity three-dimensional digital twin body for each hanging strip, the intelligent early warning module is responsible for predicting the full-period maintenance and maintenance decision module is responsible for the full-period data, the intelligent decision module is responsible for predicting and supporting the life-period maintenance of the physical hanging strip based on the full-period data. The working principle of the invention is that the sensing layer starts up, the flexible sensing module captures tension and micro-strain signals in real time through the sensing unit integrated in the han