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CN-121996966-A - Intelligent online detection method and system for fatigue degree of wires and cables

CN121996966ACN 121996966 ACN121996966 ACN 121996966ACN-121996966-A

Abstract

The invention belongs to the technical field of cable fatigue detection, and particularly discloses an intelligent online detection method and system for wire and cable fatigue, wherein the intelligent online detection method and system for wire and cable fatigue comprise the steps of laying initial detection points and synchronously collecting multidimensional state signals based on a topological structure diagram of a cable circuit and priori state information; the method comprises the steps of calculating fatigue degree of each point, generating a fatigue degree distribution heat map set which continuously covers the whole length of a circuit through spatial interpolation, identifying high-risk and low-risk sections through threshold comparison and section combination based on the heat map set, further calculating detection point density of each section, respectively generating a detection point supplement scheme for the high-risk section and a detection point simplification scheme for the low-risk section, combining and then performing reconfiguration to form an optimized network, and finally triggering optimization adjustment when a preset optimized triggering condition is achieved based on continuous monitoring of the optimized network.

Inventors

  • HU YUAN

Assignees

  • 广东玖祥电缆制造有限公司

Dates

Publication Date
20260508
Application Date
20260127

Claims (10)

  1. 1. An intelligent online detection method for the fatigue degree of a wire and a cable is characterized by comprising the following steps: Based on a topological structure diagram of the cable line and prior state information, laying initial detection points, and synchronously collecting multidimensional state signals of all the initial detection points; calculating and generating a fatigue distribution diagram set of the cable line based on the multi-dimensional state signal; Identifying high-risk and low-risk sections based on the fatigue distribution diagram set, and generating an optimized adjustment scheme by combining the arrangement of the initial detection points; And according to the optimal adjustment scheme, reconfiguring detection points to form an optimized detection point network, continuously performing data acquisition and fatigue analysis based on the optimized detection point network, and triggering and executing optimal adjustment on the detection point network when a preset optimal triggering condition is met.
  2. 2. The intelligent online detection method for the fatigue degree of the electric wires and the cables according to claim 1, wherein the initial detection point comprises the following steps: identifying structural key points in the cable line from the topological structure diagram, and marking each structural key point as a first type of initial detection point; When the prior state information is historical operation data, historical fault records are extracted from the historical operation data, and sections which are aggregated in space and have the fault occurrence times exceeding a preset frequency threshold value on the cable circuit are identified as sensitive sections; judging whether a first type initial detection point exists in each sensitive section, if so, not additionally arranging detection points in the sensitive section, and if not, arranging detection points in the sensitive section and marking the detection points as a second type initial detection point; And forming an initial detection point set by all the first type initial detection points and the second type initial detection points, and finishing the layout of the initial detection points.
  3. 3. The intelligent online detection method for wire and cable fatigue according to claim 1, wherein the calculating and generating the fatigue profile set of the cable line comprises: acquiring characteristic values of each signal dimension in each initial detection point at each time point from the multi-dimensional state signals to form a characteristic value time sequence of each signal dimension; Respectively calculating the fatigue degree of each initial detection point at each time point based on the characteristic value time sequence; mapping the comprehensive fatigue index of all initial detection points at each time point onto a topological structure diagram of a cable line to obtain the discrete fatigue space distribution at each time point; Based on the discrete fatigue space distribution of each time point, performing fatigue estimation on the position on the cable line where no detection point is arranged through space interpolation to generate a fatigue distribution curved surface covering the whole length of the cable line, and further obtaining a fatigue distribution diagram of each time point; The fatigue profiles at each time point are collected in time sequence to form a fatigue profile set of the cable line.
  4. 4. The method for intelligently detecting the fatigue of the electric wire and the cable according to claim 3, wherein the calculating the fatigue of each initial detection point at each time point comprises the following steps: acquiring a data subsequence from a set starting time point to a current time point of each initial detection point from a characteristic value time sequence of each signal dimension; trend analysis is carried out on the data subsequences of each signal dimension, and the change rate of the data subsequences is calculated to serve as a preliminary fatigue index of each signal dimension; And selecting the maximum value from the preliminary fatigue indexes of all signal dimensions of the initial detection points at each time point, and taking the maximum value as the fatigue of each initial detection point at each time point.
  5. 5. The intelligent online detection method for wire and cable fatigue according to claim 1, wherein the identifying high risk and low risk sections comprises: sequencing the fatigue degree values of all time points in the set from large to small, and further selecting the fatigue degree corresponding to the preset high-level statistical percentile as a fatigue degree threshold; dividing a cable line into micro-sections, further comparing the fatigue degree of each micro-section at each detection time point within the preset time period with a fatigue degree threshold value, if all the fatigue degrees in the fatigue degree time sequence of a certain micro-section are larger than the fatigue degree threshold value, marking the micro-section as a high risk micro-section, otherwise marking the micro-section as a low risk micro-section; and merging all adjacent high-risk micro-sections in the space to form each high-risk section, and merging all adjacent low-risk micro-sections in the space to form each low-risk section.
  6. 6. The intelligent online detection method for the fatigue of the wires and the cables according to claim 1, wherein the generating the optimized adjustment scheme comprises the following steps: calculating the current detection point density based on the total space length of each high-risk section and low-risk section and the number of initial detection points contained in the space length; For each identified high-risk section, if the current detection point density of the high-risk section is lower than the preset detection density threshold value of the section, calculating the total number of detection point targets required by the section according to the threshold value and the total length of the section space, and further determining the number of detection points to be supplemented; Determining the layout positions of the supplementary detection points based on the layout positions of all the initial detection points in the section and the number of the detection points to be supplemented, aiming at optimizing detection coverage uniformity, and generating a supplementary scheme; for each identified low-risk section, if the current detection point density of the low-risk section is higher than the preset allowable detection density threshold value of the section, calculating the expected total number of detection point targets of the section according to the threshold value and the total length of the section space, and further determining the number of reduced detection points; Evaluating the information redundancy of each detection point by analyzing the correlation of each initial detection point in the section on the multidimensional state signal, and determining a simplified object according to the number of the detection points to be simplified and the information redundancy to generate a simplified scheme; Combining the supplement scheme of each high-risk section with the simplification scheme of each low-risk section to comprehensively generate an optimization adjustment scheme.
  7. 7. The intelligent online detection method for wire and cable fatigue according to claim 6, wherein the determining the layout position of the supplementary detection point comprises: identifying the distances of the cabling between all adjacent initial detection points in the high risk section; and inserting supplementary detection points between adjacent detection point pairs with the largest distance in sequence according to the sequence from the large distance to the small distance until the number of inserted supplementary detection points reaches the number of detection points needing supplementary, wherein when inserting supplementary detection points between the adjacent detection points, the layout positions of the inserted detection points are determined in an equidistant mode.
  8. 8. The intelligent online detection method for wire and cable fatigue according to claim 6, wherein the evaluating the information redundancy of each detection point comprises: calculating the average value of the correlation between each signal dimension and all other initial detection points in the section in the dimension to obtain the average correlation of each signal dimension; And selecting the maximum value from the average correlation degree of all signal dimensions of the initial detection points as the information redundancy of each initial detection point.
  9. 9. The intelligent online detection method for fatigue of wires and cables according to claim 1, wherein the preset optimized triggering condition comprises at least one of the following: after the self-detection point network finishes the last optimizing configuration, the continuous running time of the self-detection point network reaches a preset optimizing period threshold value; Identifying that a new high risk section exists when analyzing based on the latest fatigue distribution diagram set generated since the last optimal configuration; based on the multidimensional state signals acquired in real time, identifying that the characteristic value of at least one signal dimension of any detection point is suddenly changed beyond a preset threshold value.
  10. 10. An intelligent online detection system for the fatigue degree of wires and cables is characterized by comprising the following components: the signal acquisition module is used for laying initial detection points based on a topological structure diagram and priori state information of the cable line and synchronously acquiring multidimensional state signals of each initial detection point; the distribution diagram generation module is used for calculating and generating a fatigue distribution diagram set of the cable line based on the multi-dimensional state signals; The scheme optimizing module is used for identifying high-risk and low-risk sections based on the fatigue distribution diagram set and generating an optimizing adjustment scheme by combining the arrangement of the initial detection points; The optimization adjustment module is used for performing reconfiguration of detection points according to the optimization adjustment scheme to form an optimized detection point network, continuously performing data acquisition and fatigue analysis based on the optimized detection point network, and triggering and executing optimization adjustment on the detection point network when a preset optimization triggering condition is met.

Description

Intelligent online detection method and system for fatigue degree of wires and cables Technical Field The invention belongs to the technical field of cable fatigue detection, and relates to an intelligent online detection method and system for wire and cable fatigue. Background The reliability of the long-term operation of the electric wires and cables is directly related to the safety of energy transmission and the stability of information transmission. In actual operation, the cable bears multiple stress coupling actions such as electricity, heat, machinery and the like for a long time, and accumulated damages such as insulation material aging, conductor fatigue, accessory connection degradation and the like can be caused, so that performance degradation is caused. Therefore, the real-time and accurate on-line monitoring and evaluation of the fatigue degree of the cable are key for realizing predictive maintenance and improving operation safety. The current cable state monitoring technology mainly utilizes an online sensor to carry out multi-parameter acquisition and data analysis. For example, chinese patent publication No. CN116818510a discloses a system for detecting fatigue of wires and cables, which collects detection data of a plurality of wires and cables by laying detection points, processes and analyzes the data, and uses environmental data in combination, thereby evaluating the safety in use and the remaining service life of the cables, reducing the waste of the wires and cables in use, and improving the safety of the wires and cables in use. However, the wire and cable detection technology has obvious limitations that firstly, the method only evaluates the fatigue degree of the wire and the cable based on discrete data collected by limited detection points, the result can only reflect the state of an isolated point, a fatigue degree spatial distribution diagram reflecting the continuous change of the whole wire of the cable cannot be constructed, further, the specific section of the risk is difficult to quickly locate by operation and maintenance staff, the risk gradient is identified, and meanwhile, the overall health trend of the cable cannot be accurately mastered. Secondly, the layout of the detection points is preset and fixed, however, the fatigue degradation of the cable is a dynamic process, the high risk section may shift or spread along with the change of time and working conditions, and the static network layout cannot respond to the change, so that the problem of insufficient detection on the high risk area and excessive detection resources on the low risk area is caused. Therefore, an online detection method and system capable of fusing multidimensional state information, realizing visualization of the cable full-line fatigue state, and intelligently and dynamically optimizing the monitoring resource layout according to the evaluation result are needed to solve the above problems. Disclosure of Invention In view of this, in order to solve the problems set forth in the background art, an intelligent online detection method and system for fatigue of wires and cables are provided. The intelligent online detection method for the fatigue degree of the electric wire and the cable is realized by the following technical scheme that the intelligent online detection method for the fatigue degree of the electric wire and the cable comprises the steps of laying initial detection points based on a topological structure diagram and priori state information of a cable circuit, and synchronously collecting multidimensional state signals of all the initial detection points. And calculating and generating a fatigue degree distribution diagram set of the cable line based on the multi-dimensional state signal. And identifying high-risk and low-risk sections based on the fatigue distribution diagram set, and generating an optimized adjustment scheme by combining the layout of the initial detection points. And according to the optimal adjustment scheme, reconfiguring detection points to form an optimized detection point network, continuously performing data acquisition and fatigue analysis based on the optimized detection point network, and triggering and executing optimal adjustment on the detection point network when a preset optimal triggering condition is met. The invention also provides an intelligent online detection system for the fatigue of the electric wires and the cables, which comprises a signal acquisition module, an initial detection point layout module and a multi-dimensional state signal acquisition module, wherein the initial detection point layout module is used for laying initial detection points based on a topological structure diagram and priori state information of a cable line, and synchronously acquiring multi-dimensional state signals of each initial detection point. The distribution map generation module calculates and generates a fatigue distribution map set of the cable line