The features of the use of the theory of integral series in applied problems of identification of nonlinear dynamic systems in the field of diagnosing the state of cutting tools are considered. The prospects for developing a method for estimating the states of cutting tools based on indirect measurements using integral non-parametric dynamic models based on experimental input-output data using test pulse effects on the cutting system are substantiated. This approach allows increasing the efficiency of diagnosis by reducing the amount of calculations, as well as, the reliability of the diagnosis by simultaneously taking into account the nonlinear and inertial properties of the system in integrated non-parametric dynamic models. In addition, the models in question are capable of describing faults caused by both changes in the system parameters and its structure, as well as can be used in test and functional diagnostics.
A method has been developed for building information models of cutting tool states based on indirect measurements using test pulse effects on a cutting system in the form of loads with impacts and recording system responses, on the basis of which information models are built in the form of multidimensional transition functions.
A block diagram of the organization of the experiment “input-output” in the framework of the problem of diagnosing the state of the tool under the conditions of pulse effects on the cutting system to obtain the primary diagnostic information is proposed. The methods of forming test pulse loads of the cutting system by successive insertion of the cutting tool into the workpiece with different cutting depths, with variable feed and with variable cutting duration are considered.
The computational experiment demonstrates the advantages of information models in the form of multidimensional transition functions for modeling nonlinear dynamic systems in problems of diagnosing the states of cutting tools. It has been established that multidimensional second-order transition functions can be used as an effective source of primary data in the construction of automated technical diagnostics systems.