Research on fault diagnosis method of piston rod based on harmonic wavelet and manifold learning

As the core part of reciprocating compressor,piston rod is easy to cause a serious accident when abrasion and breakage fault occur to it. Therefore,it is very important to monitor its running state. At present,a small number of reciprocating compressors have been installed on-line monitoring and diagnosis system,most of which can only monitor a single vertical subsidence of piston rod and it can't fully represent the running state of piston rod. Therefore,a method of monitoring the vertical and horizontal displacement of piston rod axis orbit is simultaneously used. In view of the characteristics that the piston rod axis orbit is disordered and difficult to extract features,purification of the axis orbit is carried out based on harmonic wavelet and then features are extracted such as vibration energy,natural frequency and the axis orbit envelope area. After that,a nonlinear local tangent space manifold learning algorithm is used to reduce the dimension of the features and obtain sensitive features. By analyzing the practical cases,the effectiveness of the method for fault monitoring and diagnosis of reciprocating compressor piston rod assembly has been verified. Finally,as BP neural network has the characteristics of solving complex nonlinear problems,the validity of the fault diagnosis method of reciprocating compressor piston rod based on harmonic wavelet and manifold learning is proved by actual case data analysis based on BP neural network.

Investigations of high-frequency induction hardening process for piston rod of shock absorber

The microhardness of piston rods treated with different induction hardening processes was tested. The experimental results reveal that the depth of the hardened zone is proportional to the ratio of the moving speed of the piston rod to the output power of the induction generator. This result is proved correct through the Finite Element Method (FEM) simulation of the thermal field of induction heating. From tensile and impact tests, an optimized high frequency induction hardening process for piston rods has been obtained, where the output power was 82%×80 kW and the moving speed of workpiece was 5364 mm/min. The piston rods, treated by the optimized high frequency induction hardening process, show the best comprehensive mechanical performance.

Design of Piston Rod Inspection Robot for Hydraulic Hoist based on Vision

In order to automatically detect the corrosion on the piston rod of hydraulic hoist of hydropower station and find the location of corrosion conveniently and accurately,a piston rod defect detection robot based on machine vision was developed.Firstly,the structure of the robot is presented,the detection system introduces the data collection process in the process of image processing,using a laser camera to capture image information.After the image preprocessing,cascade filter and morphological images after operation,the image information of gradient data,the depth of the defect data is extracted.To acquire the information of image defects in concave and convex,after using the RGB color image information acquisition defects the camera,HSV space separation and median filter and morphological processing are used to extracti defects in the image color information.Finally for defect information coding for quad,through comprehensive information for defect recognition and using QT development the human-computer interaction interface is developed,which can realize the reality and statistics of the robot′s motion control and defect information.Through the experimental verification of the robot′s performance,it is proved that the reliability of the robot′s motion and the accuracy of defect identification meet the design goal.

Microstructure characteristics of segregation zone in 17-4PH stainless steel piston rod

The segregation of Cu and Ni in a 17-4PH stainless steel piston rod has been confirmed to be responsible for the cracking after heat treatment.Further investigation showed that the segregation zone was composed of three layers,namely the fine grain martensitic layer,the coarse grain martensitic layer and the coarse grain austenitic layer from the matrix to the crack surface.Three button ingots with the same chemical compositions as those three layers have been prepared to evaluate the grain size distribution,microstructure and mechanical properties.The effects of Cu and Ni segregation on the microstructures of those three layers have been explored by thermodynamic calculation.Based on the microstructure and mechanical properties results,an intensive understanding of the cracking in the segregation zone was therefore reached.