Lixiu Zhang

Fault diagnosis of nonlinear and large-scale processes using novel modified kernel Fisher discriminant analysis approach

It is pretty significant for fault diagnosis timely and accurately to improve the dependability of industrial processes. In this study, fault diagnosis of nonlinear and large-scale processes by variable-weighted kernel Fisher discriminant analysis (KFDA) based on improved biogeography-based optimisation (IBBO) is proposed, referred to as IBBO-KFDA, where IBBO is used to determine the parameters of variable-weighted KFDA, and variable-weighted KFDA is used to solve the multi-classification overlapping problem. The main contributions of this work are four-fold to further improve the performance of KFDA for fault diagnosis. First, a nonlinear fault diagnosis approach with variable-weighted KFDA is developed for maximising separation between the overlapping fault samples. Second, kernel parameters and features selection of variable-weighted KFDA are simultaneously optimised using IBBO. Finally, a single fitness function that combines erroneous diagnosis rate with feature cost is created, a novel mixed kernel function is introduced to improve the classification capability in the feature space and diagnosis accuracy of the IBBO-KFDA, and serves as the target function in the optimisation problem. Moreover, an IBBO approach is developed to obtain the better quality of solution and faster convergence speed. On the one hand, the proposed IBBO-KFDA method is first used on Tennessee Eastman process benchmark data sets to validate the feasibility and efficiency. On the other hand, IBBO-KFDA is applied to diagnose faults of automation gauge control system. Simulation results demonstrate that IBBO-KFDA can obtain better kernel parameters and feature vectors with a lower computing cost, higher diagnosis accuracy and a better real-time capacity.

Operating state evaluation model of motorized spindle based on composite index

The operating state of motorized spindle directly affects the machine tool performance, and the evaluation model of operating state was proposed in this paper to improve the stability and reliability of the motorized spindle. The composite index was introduced based on multi-characteristic parameter evaluation model to quantitatively characterize the operating state. The statistical analysis method was used to classify the operating state data that matching the evaluation grade of the motorized spindle. The experimental results proved that the evaluation model can be used to classify the running status of the motorized spindle based on the composite index, and the index could provide references for tracing back the deterioration factor. The proposed operating state evaluation model could provide theoretical support for rational arrangement of maintenance and shorten maintenance time.

Simulation and experimental research on Si3N4 ceramic grinding based on different diamond grains

The removal mechanism of silicon nitride ceramic under high-speed grinding is studied in this article, and grinding parameters are optimized. The efficiency of grinding is improved. The diamond grains of grinding wheel are simplified into the truncated octahedron and cone to simulate the grinding process. When the ceramic workpiece is grinded by single-diamond grain and continuously grinded by multi-diamond grains, the effects of grinding depth and grinding speed on grinding force and surface morphology are analyzed. Through the grinding experiment of the inner surface of silicon nitride ceramic, the grinding force data and surface morphology images were obtained. It proves that at the process of studying the effect of grinding speed on the grinding force and machining surface quality, the results of simulation using multi-diamond grains are closer to the experimental results. The results prove that by increasing wheel speed or lowering grinding depth, the grinding force would be reduced and the quality of grinding surface would be improved. Between grinding depth and grinding speed, the latter factor has a greater impact on grinding force and the quality of grinding surface.

Based on u-n under the Flux Observer Spindle Motor Direct Torque Control System Simulation

Purpose: to study the performance of DTC system (direct torque control) within the Motorized Spindle full-speed range, and to improve the observation precision of Motorized Spindle stator flux by adopting the Full-order stator flux observer. Method: construct a Motorized Spindle DTC system based on the mathematical model of Motorized Spindle under a static stator reference frame; revise the deviation between status value and measured value of the Motorized Spindle, then build a Full-order magnetic flux observer with error-compensator based on close-loop state estimation by combining the feedback correction term and the mathematical model of Motorized Spindle with flux estimation; build a Full-order flux observer and simulate the Motorized Spindle DTC system by Matlab/Simulink so that the simulative waveform of stator flux would be obtained. Result: the correctness of Full-order stator flux observer at various speed ranges is verified. Conclusion: Full-order u-n stator flux observer shows satisfactory dynamic performance in Motorized Spindle DTC system; the u-n stator flux observer model that is constructed by choosing the proper way to set the pole of observer reduces the interference of temperature, frequency, magnetic path etc.