Minping Jia

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Abstract—This brief presents a scheme of model reference adaptive control with perturbation estimation (MRACPE) for precise motion control of a piezoelectric actuation micropositioning system. One advantage of the proposed scheme lies in the fact that the size of tracking error can be predesigned, which is desirable in practice. A second-order nominal(More)
This study proposes a hybrid model for evaluating surface roughness in hard turning using a Bayesian inference-based hidden Markov model and least squares support vector machine (HMM-SVM). The model inputs are multidirectional fusion features that are extracted from the acquired monitoring signals through independent component analysis and singular spectrum(More)
Manifold learning is one of the efficient nonlinear dimensionality reduction techniques, which can be used to fault feature extraction. But they are not taking the class information of the data into account. In this paper, a new supervised Laplacian Eigenmaps algorithm (S-LapEig) for classification is proposed first. Via utilizing class information to guide(More)
This paper reports on a new back propagation (BP) neural network based on an improved shuffled frog leaping algorithm (ISFLA) and its application in bearing fault diagnosis. The ISFLA is developed on the basis of a chaotic operator and the convergence factor of particle swarm optimization to overcome the shortcomings of conventional shuffled frog leaping(More)
A method of measuring the fill level based on the vibration signal of the mill shell is researched in this paper. An accelerometer that has a large measurement range is mounted directly to the mill shell, and the vibration signals are collected off the mill shell by a data acquisition system in experiment. According to the characteristic of vibration signal(More)
This paper proposes a new sensor deployment strategy based on quantitative cause-effect graph (QCEG) to handle the heterogeneity among the properties of sensors and faults. A QCEG is developed to model the cause-effect relationship between the system faults and sensor readings. A multi-objective optimization is performed to facilitate the monitoring of(More)
This paper reports a new improved discrete shuffled frog leaping algorithm (ID-SFLA) and its application in multi-type sensor network optimization for the condition monitoring of a gearbox. A mathematical model is established to illustrate the sensor network optimization based on fault-sensor dependence matrix. The crossover and mutation operators of(More)
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