Based on the laboring structure and working elements of the ammunition handling of the self-propelled artillery, the dynamic mathematical model of the hydraulic system for self-propelled artillery was established by means of power bond graph. The model deduced the system, then set the restriction conditions and simulated the system dynamic characteristics based on Matlab-Simulink. The simulation results matched the face. The results could provide a foundation for the detection and diagnosis of the hydraulic system.

Dynamic Simulation of Hydraulic System for Self-Propelled Artillery Based on Power Bond Graph

In this study, a new adaptive morphological filter is developed based on the mathematical morphology algorithm and characteristics of the subtle differences in the waveform morphology in seismic data. The algorithm improves the traditional morphological dilation and corrosion operations. In this study, we propose a multiscale adaptive operator based on the principle of morphological structural “probes” and present the corresponding mathematical proof. Simulation experiments and actual seismic data processing results show that compared with traditional morphological filters, the constructed OCCO-based multistructure adaptive morphological filter can suppress noise to the greatest extent. Moreover, it can effectively improve the SNR of the images, and offers great application prospects.

Study and application analysis of random noise adaptive morphological filter algorithm reconstruction for seismic signals

Image segmentation plays an important role in wear particles analysis. A new segmentation method based on multiscale mathematical morphology is proposed for wear particles image segmentation. The newly introduced method employs different scale structuring elements to detect the image edge, the final edge is calculated by the weighted average method. Edge details can be remained by small scale structuring element (SE) and noise can be depressed effectively by large scale SE, therefore, the new method has great effect in edge accuracy, strong and weak edge extraction and noise suppression. The efficiency of the method is evaluated by a set of wear particles images. The comparison with the single scale SE and other traditional methods demonstrates the improvement of the new algorithm.

Wear Particles Image Segmentation Method Based on Multiscale Mathematical Morphology

Feature selection is a key step in hydraulic system fault diagnosis. Some of the collected features are unrelated to classification model, and some are high correlated to other features. These features are harmful for establishing classification model. In order to solve this problem, genetic algorithm-partial least squares (GA-PLS) is proposed for selecting the representative and optimal features. K nearest neighbor algorithm (KNN) is used for diagnosing and classifying hydraulic system faults. For expressing better performance of GA-PLS, the original data of a model engineering hydraulic system is used, and the results of GA-PLS are compared with all feature used and GA. The experimental results show that, the proposed feature method can diagnose and classify hydraulic system faults more efficiently with using fewer features.

Bing Li

Papers

Wear Particles Image Segmentation Method Based on Multiscale Mathematical Morphology

Feature Selection Method for Hydraulic System Faults Diagnosis Based on GA-PLS