Research On Real-time Sensing System Of Cutting Force Assembled On Tool Holder

As a basic industry,the machinery manufacturing industry is implementing a transformation and upgrading strategy that towards the direction of intelligent manufacturing with high-efficiency and high-precision to develop.However,the basis for intelligent manufacturing requires that the machine can monitor the status of the process in real time,which depends on the intelligent functional components application.The cutting force is the most stable and easily available signal type in the machining state,and the tool holder is located in the close position of the cutting force transmission chain.Thus,by carrying out the research on real-time sensing system of cutting force which assembled on tool holder,providing accurate data for machining condition monitoring and helping the development of intelligent cutting technology.For the requirement of the tool holder structure that it can assemble sensors to realize measurement in direction of axial force and torque.The characteristics of the resistance sensor are analyzed,and the sensor structure and measurement circuit type used for axial force and torque measurement are determined.Considering the requirements of the base of the tool holder,the strain cell structure is designed to install the sensor.The multi-objective optimization model of the tool holder is established.It is solved by the method of response surface optimization and the optimal size parameters of the tool holder are obtained.The attachment of the tool holder system is developed and the overall design of the tool holder system is determined.Aiming at the problem in traditional signal transmission method which is easy to generate data jam at high frequency sampling frequency,the research on cutting force signal processing method based on compressive sensing is carried out.The sparsity of cutting force signal is analyzed and constructed the sparse representation model of cutting force signal based on discrete fourier transform orthogonal basis.The random Gauss matrix is optimized by using the improved QR decomposition method to construct observation matrix.The compressive sampling matching pursuit method is used to efficiently and accurately reconstruct the low-dimensional observation signals,and the cutting force signal processing based on compressed sensing is realized.In order to obtain the static and dynamic performance of the tool holder system,the static and dynamic calibration experiment platform was built though analyzing the calibration experiment requirements of the system.The static and dynamic characteristics of the system were obtained by step-by-step loading and unloading method and pulse method respectively.The cutting experiment platform was built and analyzed the reason why the measurement error is large between the tool holder system and Kistler plate dynamometer during the milling process.The accuracy of the system in direction of axial force and torque measurement is verified in the drilling experiment.The results show that the tool holder system has a good work performance for real-time measurement of cutting forces.