Research On Online Detection System For Broken Wire Damage Of Mining Steel Wire Rope Based On Magnetic Leakage Detection

Steel wire rope is a crucial component in mine hoisting due to its light weight,high strength,and good wear resistance.However,long-term use can cause varying degrees of damage,and using damaged steel wire ropes without recognizing their status can pose a great threat to the safety of mine workers and equipment,and even lead to accidents and cause personal and property losses.Detecting steel wire rope damage can ensure the normal operation of the mine and protect the safety of personnel and property.However,online detection and quantitative identification of broken wires in mining ropes using non-destructive testing technology remains a technical challenge.This paper studies the quantitative identification of broken wires in mining ropes based on the principles of magnetic leakage testing and develops an online detection system for broken wire damage in mining ropes based on Lab VIEW.The main research content is as follows:(1)to solve the problem of uneven magnetization of mining steel wire rope structures and weak signals caused by damage,a steel wire rope magnetic dipole analysis model was constructed based on an analysis of the structural characteristics,damage types,and scrapping standards of mining steel wire ropes.The effects of broken wire parameters and lift-off value changes on magnetic leakage of the wire ropes under different conditions were analyzed and visualized in three dimensions.A static simulation model of the steel wire rope excitation structure was established to analyze the effects of different magnetic circuit parameters on the excitation effect of the steel wire rope under a 5mm lift-off value and the magnetic circuit parameters were selected.A dynamic simulation model of the steel wire rope excitation structure was constructed to simulate the internal magnetization and damage leakage of the actual detection process of the steel wire rope,and verify the magnetization effect of the excitation structure.The results showed that the steel wire rope was uniformly magnetized,and the broken wire damage signal was obvious,laying a foundation for the design of the steel wire rope excitation structure.(2)To solve the problem of large environmental noise interference and difficult signal capture during the acquisition of broken wire damage signals in mining steel wire ropes,a sensor array layout scheme was determined based on an analysis of magnetic sensor characteristics.A two-stage amplification circuit with summing,amplification,and zeroing functions was designed based on the analysis of the magnetic leakage signal characteristics and the circuit function was tested through circuit simulation.Circuit testing experiments were carried out by simulating the fluctuation of magnetic leakage fields caused by wire breakage.Based on the experimental feedback,the circuit was adjusted and optimized,and the experiments were verified again.The results showed that the conditioned circuit had good anti-interference and signal amplification capabilities,laying a foundation for the data acquisition of broken wire damage in mining steel wire rope.(3)To obtain the data of broken wire damage,verify the magnetization performance of the excitation structure,and test the signal preprocessing capability of the conditioned circuit,a mining steel wire rope broken wire damage testing platform was established,broken wire damage specimens were produced,and Lab VIEW acquisition programs were designed.The radial and axial components of the broken wire damage leakage were collected from four angular directions,providing a large amount of reliable data for the quantitative identification of broken wire damage in mining steel wire ropes.Experimental data analysis showed that the excitation structure had good magnetization performance,the conditioned circuit had good signal preprocessing capability,but the broken wire damage signal was affected by noise interference.(4)To solve the problem of quantitative identification of broken wire damage in mining steel wire ropes in strong noise environments,four wavelet threshold acquisition methods were compared using three evaluation indicators.The results showed that the wavelet signal processing method based on unbiased risk threshold had the best denoising effect.Twelve features were extracted from the denoised signals to describe the damage information.The radial and axial datasets of the broken wire damage signals were created and fed into BP neural network model,SVM support vector machine model,and Convolutional Neural Network model for quantitative identification of broken wire damage.The results showed that the Convolutional Neural Network model driven by the radial dataset had the highest recognition accuracy.(5)To achieve online detection of broken wire damage in mining steel wire ropes,online detection requirements were analyzed,and an online detection system for broken wire damage in mining steel wire ropes based on the Lab VIEW platform was developed.The system can collect data,process signals,identify damage,and generate reports.The system was tested on external broken wire specimens of mining steel wire ropes,and the results showed that the system can effectively identify the number and position of broken wire in mining steel wire ropes.ropes.