| The detection technology of lubricating oil metal debris can accurately obtain the wear information of mechanical equipment,and has become an important means of monitoring the health of mechanical equipment and fault diagnosis.The three-coil chip detector has the advantages of simple structure,can distinguish ferromagnetic and nonferromagnetic debris,and has a low rate of missed detection.It has been widely used.However,due to the weak sensing signal and the excitation magnetic field balance easily damaged by the parasitic capacitance changes between the coils and mechanical vibration,this type of system also has problems such as low detection sensitivity,oil bubbles are easy to false detection,and weak anti-vibration interference capabilities.Therefore,this paper proposes a three-coil type chip detector scheme based on wavelet transform and curve fitting algorithm,focuses on the construction of metal debris sensor model,optimizes sensor coil parameters,and conducts research on key technologies such as chip metal signal detection algorithm.The main work is as follows:1.In view of the need for the detection of lubricating oil metal chips to distinguish the ferromagnetism of the chips from the statistics of the size distribution of the chips,as well as the difficulty of easy detection of air bubbles,analyzed the characteristics of three types of electric inductance sensors,namely single-coil,double-coil and threecoil,a realization scheme of lubricating oil metal chips detection based on three-coil sensor is designed.2.Based on Biot Savart’s law and Faraday’s law of electromagnetic induction,a three-coil time-harmonic magnetic field metal chip sensor model was constructed,combined with finite element simulation,and the influence of excitation frequency and coil structure parameters on the induced voltage was analyzed.The orthogonal test method obtains the coil structure parameter combination that maximizes the sensor’s induced voltage output,which effectively improves the sensor’s detection sensitivity.3.Analyzed the influence of environmental noise,mechanical vibration and oil bubbles on the sensing signal and the characteristics of the interference signal,and proposed a fusion of adaptive spectral line enhancement,wavelet transform and Gaussian differential curve fitting on-line metal chip parameters detection algorithm.Using the short-term and stable time-frequency characteristics of vibration interference,the sensor signal is delayed by 0.05 s as the reference signal,and the autocorrelation filtering algorithm is used to achieve vibration interference suppression;the original signal is decomposed into multiple wavelet subbands using variable quality factor wavelet transform,on each wavelet subband,the adjacent coefficient threshold method is used to process the wavelet coefficients,and the processed wavelet coefficients are reconstructed to obtain the denoising signal;the high similarity of the first-order differential of the signal waveform of the metal shavings and the Gaussian function is used,Continuous wavelet transform and curve fitting algorithm are used to realize the detection and detection of metal chips and the suppression of bubble interference.4.Developed a prototype of a three-coil type chip sensor,built a lubricating oil metal chip detection system and an experimental platform;the system performance test and reliability test experiment were carried out,and the detection thresholds of the system for spherical iron and spherical copper chips were determined to be 150μm and250μm,respectively.And verified the anti-interference ability and reliability of the system. |
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