Study On The Mapping Relationship Between Vibration Of Cutting Head Of Rock Roadheader And Rock Hardness

The subject is an important part of national science fund projects “Research on Intelligent Recognition Method of Cutting Dynamic Load of the Super-heavy Rock Roadheader Based on Multi Parameters”(NO: U1510112),which is mainly aimed at solving the problem of difficulty in recognizing the hardness of cutting rock wall because of the poor underground environment and the hidden danger to the personal safety of operators.During actual coal and rock mining,the operating workers cannot accurately judge the condition of the rock wall contacted by the cutting head of the roadheader and adjust the parameters of the roadheader in time,which may cause damage to the roadheader parts and shorten it's life.Therefore,a method for identifying the dynamic load of the cutting head of the super-heavy rock roadheader suitable for actual coal and rock mining is proposed,which provides a basis for the intelligent development of the roadheader and this research has extremely important significance.In this paper,through consulting a large number of domestic and foreign literatures,on the basis of in-depth understanding of the development process of the roadheader and the dynamic load identification method,it is found that the existing roadheader has a low level of intelligence,and the dynamic load identification technology is rarely applied in the field of coal and rock cutting of roadheader.Therefore,taking super-heavy rock roadheader as the research object,a dynamic parameter recognition method for the cutting head of the roadheader based on multi-parameters is proposed to analyze the mapping relationship between the vibration signal of the head of roadheader and the hardness of the rock.The specific research contents are as follows:Through the deep understanding of the structure and working principle of the roadheader,the dynamic analysis of the cutting mechanism is carried out.According to the load calculation formula of the cutting head of the roadheader,the main parameters affecting the cutting head of the roadheader including the cutting rock hardness,the cutting head depth,the swing speed,the rotation speed,etc.According to the design parameters of the cutting head of the roadheader,the cutting head load simulation program is written in MATLAB software,the stress curve of the cutting head of roadheader under different parameter variables is gotten,and the influence of each parameter on the cutting head load is analyzed in depth,which provides the reference basis for the identification of the driving load of the cutting head load of the roadheader.According to the example of a super-heavy rock roadheader,a threedimensional virtual prototype model was built.The three-dimensional models of the roadheader's cutting part,body part,walking part and other components are built and assembled in Pro / E software to establish the three-dimensional model of the roadheader.In the ADAMS software,the three-dimensional model is flexibly processed,and various constraints and driving conditions are added to form a virtual prototype model of the roadheader.The force curve of the cutting head of the roadheader under different parameters is imported into the ADAMS software and applied to the center of mass of the cutting head.In the ADAMS,the coal and rock cutting of the roadheader is simulated to obtain the vibration signal of the cutting head under different parameters,which provides a basis for the extraction of the cutting head load feature quantity.According to the requirements of roadheader maneuver load identification,a method of roadheader maneuver load recognition based on multi-source data fusion is proposed.First,a feature extraction method combining correlation threshold denoising method and empirical wavelet transform is proposed.According to the maximum value point of the time-frequency map of the roadheader signal,an adaptive filter bank is constructed,the empirical wavelet transform is used to decompose the signal,and the correlation threshold denoising method is used to denoise each signal component,and the standard deviation of the correlation coefficient between each component after denoising and the initial signal is used as a threshold to perform signal deletion to constitute a feature quantity.Finally,the feature quantity is used as the input signal of the convolutional neural network to perform pattern recognition of the cutting head signal of the roadheader.The process flow of the dynamic load identification scheme for the cutting head of the roadheader is designed.The empirical wavelet transform and correlation threshold denoising method are used to extract the feature quantity of the cutting head signal of the roadheader under different parameters,then the neural network model is constructed by setting appropriate neural network parameters,and then the one-dimensional convolution neural network is used to perform patten recognition on the input signal,experiments show that this scheme has a high recognition accuracy.