Henan Diesel Engine Industry Co.

Henan’an, China

Henan Diesel Engine Industry Co.

Henan’an, China

Time filter

Source Type

Ren W.-X.,Henan Diesel Engine Industry Co. | Lei C.-W.,Henan Diesel Engine Industry Co. | Gao Y.-X.,Henan Diesel Engine Industry Co.
Jinshu Rechuli/Heat Treatment of Metals | Year: 2012

The effect of material and process technology on microstructure and fatigue property of piston pin was analyzed. By improving material purity, decreasing banded structure, optimizing carburizing and quenching process, refining microstructure, the strength, wear resistance and dimension stability are greatly improved, fatigue life of piston pin can reach over ten thousand hours.


Niu X.,Harbin Engineering University | Niu X.,Henan Diesel Engine Industry Co. | Yang C.,Harbin Engineering University | Wang H.,Harbin Engineering University | Wang Y.,Harbin Engineering University
Applied Thermal Engineering | Year: 2016

Artificial Neural Network (ANN) and Support Vector Machine (SVM), due to their accuracy and ability to analyze nonlinear problems, have been applied in many research areas. However, their performances vary with the application area. This paper investigates the performances of these two approaches for the responses prediction of a common rail direct injection system (CRDI)-assisted marine diesel engine. Moreover, considering that the experiments of marine diesel engines are always time, money and energy consuming, the main purpose of this study is to determine the better predictive approach based on a small amount of training data. The Taguchi orthogonal array is employed for the operating points determination of training data; then, based on the same training data, which contain only 25 samples, the predictive performances of ANN and SVM are evaluated and compared. The comparison of ANN and SVM indicates that with limited experimental data, SVM can find the optimal global solution and has excellent predictive accuracy and generalization capability, while ANN may converge to local minima and face the overfitting problem. Eventually, this study suggests that SVM is well-suited for application to diesel engine response predictions and will reduce the experimental cost significantly. © 2016 Elsevier Ltd.


Ren W.-X.,HeNan Diesel Engine Industry Co. | Wen J.-B.,Henan University of Science and Technology | Gao Y.-X.,HeNan Diesel Engine Industry Co.
Jinshu Rechuli/Heat Treatment of Metals | Year: 2010

Factors that influenced the distortion of gears and pins during salt bath nitrocarburizing were analysed. Through salt bath nitrocarburizing, it is found that variety of CNO- content in salt bath causes different microstructure in nitrocarburized layer, thus result in obvious change of parts dimension. By controlling the content of CNO- within provided limits, the distortion of gears and pins can be controlled effectively.

Loading Henan Diesel Engine Industry Co. collaborators
Loading Henan Diesel Engine Industry Co. collaborators