Papers by Author: P. Wang

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Authors: Chun Ya Wu, Xian Li Liu, Yi Wen Wang, P. Wang, Yu Wang
Abstract: This study takes virtual instrument technology as the development platform to complete data acquisition, pre-processing, analysis and database storage for three orthogonal components of a cutting force and the corresponding cutting temperature. Simultaneously, single-factor experimentation is adopted to establish empirical formulas of these cutting state parameters for further check analysis. Hence real-time monitoring of cutting process can be implemented to represent cutting-tool wear, failure and rationality of parameter selection in cutting state.
Authors: Chun Ya Wu, Xian Li Liu, Y.J. Wang, P. Wang, Yi Zhi Liu
Abstract: Aiming at different ground surfaces of hardened bearing steel GCr15, this paper made experimental research on assessment method of surface roughness based on computer vision technology. Firstly, some pre-processing of the ground images should be carried out to eliminate noise and get more detail information, including image enhancement and median filtering. Then the method of power spectrum analysis transformed representation of processed image from spatial domain to frequency domain by adopting two-dimensional Discrete Fourier Transform. Gaining the mean power spectrum named E and its corresponding radius r, we made efforts to seek the direction in which the arithmetic average surface roughness Ra varied according to E and r. After that the variation rule can be regarded as an assessment basis of ground surface roughness.
Authors: Yu Wang, Fu Gang Yan, P. Wang, Cai Xu Yue, Xian Li Liu
Abstract: Machining hardened steels has become an important manufacturing process, particularly in the automotive and bearing industries. Hardened steel GCr15 with its harness between HRC50 and HRC65 is one kind of more difficult machining material. Abrasive processes such as grinding have typically been required to machine hardened steels, but advances in machine tools and a new cutting material of polycrystalline cubic boron nitride (PCBN) have allowed hard turning on modern lathes to seems to gain an ever increasing industrial acceptance as an economically and environmentally friendly alternative to many grinding applications. In this paper, based on large deformation theory and updated Lagrangian procedure, a coupled thermo-mechanical plane strain orthogonal precision cutting model with general finite element analysis software is developed to the influence of cutting edge preparation on the cutting of GCr15 with PCBN tool, such as cutting forces, shear angle, and cutting temperature. The three major designs of cutting edge preparation are used on most commercial cutting inserts: a) sharp edge, b) honed edge, and c) chamfer edge. The friction between the tool and the chip is assumed to follow a shear model and the local adaptive remeshing technique is used for the formation of chip. The calculated principle cutting forces are compared with published data and found to be in good agreement. The simulation results can be used as a practical tool both by researchers and toolmakers to design new tools with rational tool edge and to optimize the cutting process.
Authors: P. Wang, D.L. Liu, Yi Zhi Liu, Xian Li Liu, Chun Ya Wu
Abstract: The Polycrystalline Cubic Boron Nitride (PCBN) cutting tools has have been developed for high speed machining in modern automation manufacture. The machining surface roughness is regarded as an important criterion to assess PCBN cutting tools performance. There are too many problems in conventional detection method. In order to solve that problem, we present a new way that is based on image analysis of machining surface texture to assess surface roughness. The new method is consisted of three steps. It captures surface texture image when machining is finished or pauses. Firstly, RGB histogram is adopted to analyze image pixel information. This means takes advantage of histogram technique and provides more pixel distribution information than gray histogram. Secondly, unsupervised texture segmentation is used based on resonance algorithm. Thirdly, a new estimation parameter E that is the density of surface contour peak is put forward to estimate machining surface roughness.
Authors: Yi Zhi Liu, Xian Li Liu, P. Wang, Yi Wen Wang, Liang Zhu, Lan Wang
Abstract: This paper used digital image technology to detect surface defects of steel ball, and designed mechanism body and the corresponding control system. In order to improve the poor control effect of basic PID, we put forward modified PID control strategy, combining speed-variable integral, differential, and anti-saturation integral, then realized optimum design for PID parameters. The experimental results indicated that PID control strategy in the paper based on optimizing parameters had a maximum output at the initial time interval, so that the response speed of system would be much higher, and the adjusting time would also be shorter.
Authors: P. Wang, Yi Zhi Liu, D.L. Liu, Chun Ya Wu, Xian Li Liu
Abstract: The detecting instrument for surface quality of steel ball bases on embedded control system and image detection technique, and is applied to detect surface defect region of steel ball in bearing. Its control system requires excellent real-time character and control accuracy. This paper puts forward a new design for controller of detecting instrument. We adopted TMS320LF2407A which produced by company TI as main processor, and integrated CPLD to develop an embedded controller. We used the Ziegler–Nichols tuning methods to get PID control and designed hardware circuit. We realized the function of correlative logic elements through programming, and constructed an embedded multitask operating system based on the transplant of μC/OS-II on TMS320LF2407A. It solved problems about intricate structure and bad real-time character existed in traditional control module. The result of simulation and experiment indicates that this control system satisfied excellently the requirement of high speed and real-time image detection.
Authors: P. Wang, Y.L. Zhao, Xian Li Liu, Yi Wen Wang
Abstract: It has been necessary to adopting automatic detection of steel ball based on machine vision in industrial processing. The detecting instrument for surface quality of steel ball based on machine vision and embedded control technique and is applied to detecting external bug region of steel ball in bearing. Its image detection and control system require excellent real-time character and high control accuracy. This paper put forward a new design for image processing and control system of detecting instrument. Firstly, we adopted OTSU segmentation arithmetic based on image enhancement and median filtering. As a result, steel ball was detected by area character parameter. Secondly, we adopted TMS320LF2407A as main processor and integrated CPLD to develop an embedded controller. It presents a novel optimal design method for PID controller based on the ant colony optimization (ACO) algorithm to optimize traditional PID control algorithm. At last, a performance study of experimental system is conducted and it shows that the proposed method can be used in online steel ball detection applications.
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