Vibration signal and neural network-based TBM disc cutter wear identification system

Abstract

The invention discloses a vibration signal and neural network-based TBM disc cutter wear identification system, which comprises a vibration signal acquisition and processing subsystem and a neural network identification model, and is characterized in that the vibration signal acquisition and processing subsystem comprises a sensor module, a data acquisition module and a data processing output module which are connected in sequence; the sensor module is installed on the hob and used for obtaining hob rock breaking vibration signals and converting the vibration signals into piezoelectric signals. The data acquisition module acquires a piezoelectric signal at a set sampling frequency to obtain a time domain signal, and the data processing output module calculates the time domain signal by adopting a fast Fourier method to obtain a frequency domain signal and outputs frequency domain data; and the neural network identification model identifies the wear state of the single-blade disc cutter according to the frequency domain data. The recognition system has good stability and reliability, has good feature extraction and recognition capability, can comprehensively capture the features of the vibration frequency domain data, and achieves a good accuracy level.

Description

technical field [0001] The invention belongs to the field of identification and diagnosis of wear state of TBM hobs, in particular to a TBM disc hob wear identification system based on vibration signals and neural networks. Background technique [0002] The disc hob is an important core component of the TBM, which undertakes the most important rock breaking function, and its state directly affects whether the TBM can operate normally, and is a major source of risk in tunnel excavation construction. The common method of traditional TBM disc hob wear diagnosis is to stop the machine and open the warehouse for inspection. Operators must frequently stop the machine and enter the warehouse for manual inspection of the cutter head and cutter, so as to judge whether it is necessary to repair the cutter head and replace the cutter. Tool replacement and maintenance due to downtime inspections bring high time costs and economic costs, and the high-temperature and high-pressure warehou...

AI Technical Summary

Problems solved by technology

[0005] In the existing research, the vibration signal is rarely used to detect the wear state of a single disc hob, and some neural network algorithms have also been initially applied in the condition monitoring of the disc hob, but there is no connection between the vibration signal and the neural network. An Example of Combining Network Algorithms Used in Recognition of the Wear State of a Single Disc Hob

Images