Multi-frequency electromagnetic feature fusion abrasive particle identification method

By combining multi-frequency series sensors and the Levenberg-Marquardt optimization algorithm, the problems of hardware parasitic parameter coupling, multi-frequency detection interference, and difficulty in solving nonlinear models are solved, achieving high accuracy and fast response in abrasive particle identification, which is suitable for online oil monitoring of large mechanical equipment.

CN122330253AActive Publication Date: 2026-07-03HARBIN ENG UNIV
5 Cites 0 Cited by

Patent Information

Application Number
CN202610813327.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-06-08
Publication Date
2026-07-03
Estimated Expiration
2046-06-08

AI Technical Summary

Technical Problem

Existing technologies for online monitoring of oil in large mechanical equipment suffer from problems such as measurement distortion caused by deep coupling between hardware parasitic parameters and physical response, intermodulation interference during multi-frequency detection, difficulty in analytically solving the nonlinearity of the forward analytical model, and poor convergence of conventional optimization algorithms, which affect the accuracy and real-time performance of abrasive particle identification.

Method used

A multi-frequency complex observation matrix is ​​acquired using a multi-frequency series sensor. Parasitic parameter interference is removed by complex domain calibration of the hardware system. A multi-dimensional joint inversion objective function of the time harmonic field is constructed. The Levenberg-Marquardt optimization algorithm is used for iterative optimization to extract the equivalent diameter, conductivity and relative permeability of the abrasive particles.

Benefits of technology

It achieves a robust environment against hardware influences, high-precision decoupling of multiple physical properties of abrasive particles, and global convergence and extreme speed of the solution process, thereby improving the accuracy and real-time performance of abrasive particle identification and meeting the requirements of industrial online monitoring.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention provides a multi-frequency electromagnetic feature fusion abrasive particle identification method, and relates to the field of signal processing, sensor information fusion and mechanical state intelligent monitoring. The problems that measurement distortion is caused by hardware parasitic parameter coupling in existing abrasive particle recognition, a time-harmonic field model cannot be directly analyzed and solved due to high nonlinearity, and abrasive particle parameter misjudgment is easily caused due to poor convergence of a conventional optimization algorithm are solved. According to the method, a time-harmonic field forward analytic model and a nonlinear objective function are constructed, and a Levenberg-Marquardt (LM) optimization algorithm is utilized to extract the equivalent diameter, the conductivity and the relative permeability of unknown metal abrasive particles in a multi-dimensional parameter space through joint inversion. According to the method, the equivalent diameter, the conductivity and the magnetic conductivity of the abrasive particles can be accurately decoupled, materials can be accurately distinguished, the LM algorithm is fast in convergence and free of divergence, millisecond-level inversion is achieved, and the requirements for high precision and real-time performance of industrial oil online monitoring are met.
Need to check novelty before this filing date? Find Prior Art