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Wu G.,Chongqing University | Wu G.,Chongqing Communication Institute | Wu P.,Chongqing University | Wu P.,Chongqing Chuanyi Automation Co | And 2 more authors.
Proceedings of the World Congress on Intelligent Control and Automation (WCICA) | Year: 2015

Industrial Ethernet is the movement of industrial control network systems. In order to have an overall understanding of industrial Ethernet for the readers, the paper introduces the development of industrial Ethernet. Then further state the mainstream technology of industrial Ethernet in detail. And finally, discuss the development trend of industrial Ethernet and summarize all the paper. © 2014 IEEE. Source

Lin T.,Chongqing University | Wu P.,Chongqing University | Wu P.,Chongqing Chuanyi Automation Co | Gao F.,Xinxiang Medical University | Yu Y.,Xinxiang Medical University
International Journal of Heat and Technology | Year: 2015

When the quality of liquid ammonia is measured by volumetric flowmeter, the traditional quadratic expression method can't meet the accuracy of temperature compensation in modern coal chemical industry. So the temperature compensation method by support vector machine (SVM) regression is presented, and kernel function parametersof SVM isoptimizedby variable weight particle swarm optimization (PSO). After the performance analysisandcomparisonin PSO, the suitable linear inertia weight method is selected. Experimental results show that the temperature compensation accuracy ofthe SVM method based on the variable weight PSO is significantly higher than that of the traditional quadratic expression method. Source

Xia Y.,Chongqing University | Wu P.,Chongqing University | Wu P.,Chongqing Chuanyi Automation Co
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | Year: 2016

In order to improve the production efficiency and reduce the production cost, in this paper, taking instrument and meter manufacturing industry as the background, aiming at the characteristics of a certain flow meter production workshop, we establish the optimization objective function, propose a multi-processing path FJSP (MPFJSP) model. In order to avoid the interference of the non-feasible solutions in the model, we adopt a new sequential encoding mode and a new method that searches the feasible solution nearby the non-feasible solution and then replaces the non-feasible solution. In order to improve the convergence speed, the particles are divided into a number of small segments, which are updated and disturbed respectively, and the excellent gene is reserved; thus, the PMOPSO algorithm is formed. Compared with other algorithms, the proposed algorithm could find the optimum machining path in every machining path of the workpiece, which verifies the superior performance of the algorithm; it is also verifies that the MPFJSP is more flexible than traditional FJSP, and the obtained solution is better. In the experimental production of the flow meter production workshop, the default cost is decreased by about 12%, and the production efficiency is improved by about 10%. © 2016, Science Press. All right reserved. Source

Hu J.-J.,Chongqing University | Zhang Y.,Chongqing Chuanyi Automation Co | Zhou T.,Chongqing Institute of Engineering
ICIC Express Letters | Year: 2015

Based on the pioneer work of Konishi et al., with consideration of the influence of the steady desired speed effect of the two vehicles in front on the traffic flow, a new feedback control car-following model is presented to suppress the traffic jam under open boundary condition. According to the control theory, the condition under which traffic jam can be suppressed is analyzed. Compared with the previous control models, the simulation results show that the stability performance of our model is better than those of the previous models, and it confirms the correctness of the theoretical analysis © 2015 ICIC International. Source

Wu P.,Chongqing University | Wu P.,Chongqing Chuanyi Automation Co | Lin T.,Chongqing University
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | Year: 2014

Aiming at the high accuracy requirement of identification modeling in sheathed thermocouple sensor accuracy compensation, an approach for the parameter optimization of support vector machine (SVM) kernel function is proposed, which adopts SVM identification modeling combined with quantum genetic algorithm (QGA) that has powerful global searching ability to minimize modeling error. The generalization performance of SVM identification model output response and checking error was tested, and the SVM identification modeling error was compared with that of recursive least square estimation method. The results show that the SVM identification modeling method based on QGA has better generalization performance and modeling precision for sheathed thermocouple sensor identification modeling. The related error compensation experiment proves that the proposed method can meet the requirement of sheathed thermocouple sensor error compensation in modeling precision. Source

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