Papers by Author: Chao Deng

Abstract: Since numerous parts and various faults of CNC machine tool, the mapping model is proposed to represent the complex relationship between faults. Then some matrices are used to process the mappings model. Finally, the priority of the fault sources is sorted by the fault localization algorithm based on the matrix above. Besides, the case of ram feed system of CNC boring machine tools FB260 illustrates the performance of mapping model based on fault diagnosis.

Abstract: The modern high-end CNC equipment with high reliability and long life expectancy makes traditional methods of equipment reliability assessment difficult due to the multiple performance parameters as well as less failures and degradation data. This paper proposes a performance reliability assessment based on multiple parameter degradation data, which deals with reliability evaluation with small numbers of samples. With the analysis of performance degradation processes and rules, the framework of the performance reliability assessment for multiple parameters is proposed. Using the degradation data of multiple performance parameters of CNC equipment, a covariance matrix is built to determine the correlation between the performance parameters. The degradation trajectories of the performance parameter(s) are curve fitted by Support vector machines (SVM). The reliability when the degradation curve reaches its specified threshold is calculated. According to both the reliabilities of non-relevant performance parameters and relevant performance parameters, the joint reliability of the system is calculated. Finally, using a specific type of CNC machine tool as an example, the performance reliability assessment method is verified.

Abstract: The trend of modern high-end CNC equipment with high reliability and long life expectancy makes traditional methods of equipment reliability assessment difficult due to the multiple performance parameters as well as less failures and degradation data. This paper proposes a performance reliability assessment based on parameter degradation data, which deals with reliability evaluation with small numbers of samples. With the analysis of performance degradation processes and rules, the framework of the performance reliability assessment for parameters is proposed. According to the degradation data of a single performance parameter, the degradation trajectory of the performance parameters is curve fitted by Support vector machines (SVM). The reliability when the degradation curve reaches its specified threshold is calculated. The probability density function at time is also built, which describes the shape of the failure distribution of each performance parameter at each stage in time. Finally, using a specific type of CNC machine tool as an example, the performance reliability assessment method is verified.

Abstract: Machining process parameters directly affect the machining quality and efficiency of heavy-duty CNC machine tools, selecting correctly machining process parameters can improve the machine’s machining performance effectively. This paper presents a machining process parameters optimization method based on grid optimization algorithm for heavy-duty CNC machine tools. In this method, a multi-objective optimization model will be established, which considers not only the linear constrains of machining process parameters, such as machining time and machining cost, but also the non-linear constrain, such as chatter in machining process. Grid optimization algorithm will be adapted to search the optimal combination of machining process parameters from the multi-objective optimization model. In the end, this paper will present an example to verify superiority of the multi-objective optimization method by comparing with single-objective optimization method.

Abstract: This paper analyzes the machining process of CNC machine tools, and builds an optimization model of the machining process parameters based on the mechanical vibration and the operational research. The model mixed genetic algorithm and particle swarm optimization (PSO) is built. It proposes an optimization algorithm that has higher convergence precision and execute ability to solve engineering problem with nonlinear and multi-extremum. According to case study, it proves the correctness of the model and the efficiency and high-performance nature of the designed optimization algorithm. It also appears the efficiency to solve the common engineering problems by the intelligent optimization algorithms.

Abstract: NC machines are more and more widely used in manufacturing industry. As the key equipments in the factory, NC machines should be closely monitored to avoid faults. Therefore, the research on multi-function diagnosis based on BP-SOM is discussed for NC machine in the paper. Taking the precision data as the basic data for diagnosis, the research used BP and SOM algorithms to build up diagnosis models. As a result, the research has accomplished the diagnosing process and acquires good simulation output, which resembles with the real fact.

Abstract: Performance degradation; Time series; Reliability prediction; Non-stationary data. Abstract. Performance degradation model has become a critical issue for lifetime reliability research. A novel n-ARIMA-based equipment performance degradation model method was proposed in this paper. First of all, a general performance degradation process was analyzed in detail. Then a non-stationary Auto-Regression Integrated Moving Average model was adopted to set up the equipment performance degradation model, and an equation to calculate the performance degradation level was also built. Finally, a validation experiment was implemented on OTM650 milling machine. It has been indicated from the experiment that the performance degradation model built in this paper may accurately describe the characteristics of the equipment performance degradation against time.