Chen-Long Li, Chang-Shun Yuan, Xiao-Shuang Ma, Wen-Liang Chen and Jun Wang
This paper aims to provide a novel integrated fault detection method for industrial process monitoring.
Abstract
Purpose
This paper aims to provide a novel integrated fault detection method for industrial process monitoring.
Design/methodology/approach
A novel integrated fault detection method based on the combination of Mallat (MA) algorithm, weight-elimination (WE) algorithm, conjugate gradient (CG) algorithm and multi-dimensional Taylor network (MTN) dynamic model, namely, MA-WE-CG-MTN, is proposed in this paper. First, MA algorithm is taken as data pre-processing. Second, in virtue of approximation ability and low computation complexity owing to the simple structure of MTN, MTN dynamic models are constructed for each frequency band. Furthermore, the CG algorithm is used to discipline the model parameters and the outputs of MTN model of each frequency band are gained. Third, the authors introduce the WE algorithm to cut down the number of middle layer nodes of MTN, reducing the complexity of the network. Finally, the outputs of MTN model for each frequency band are superimposed to achieve outputs of MTN model, and fault detection is proceeded by the residual error generator based on the difference between the output of MTN model and the actual output.
Findings
The novel proposed method is used to perform fault detection for industrial process monitoring effectively, such as the Benchmark Simulation Model 1 wastewater treatment process.
Originality/value
The novel proposed method has generality and provides considerably improved performance and effectiveness, which is used to perform fault detection for industrial process monitoring. The proposed method has good robustness, low complexity and easy implementation.
Details
Keywords
Jiawei Sun, Peng Yi, Hong-Yu Jia, Xiao-Shuang Yang, Yong-Jun Shi, Yancong Liu and Muming Hao
This paper aims to investigate the influence of sinusoidal texture (ST) with different morphology parameters on the corresponding tribological effects.
Abstract
Purpose
This paper aims to investigate the influence of sinusoidal texture (ST) with different morphology parameters on the corresponding tribological effects.
Design/methodology/approach
The STs with different amplitudes, ranging from 0.05 to 0.3 mm, and frequencies, ranging from 5 to 17.5, are fabricated using nanosecond pulsed laser equipment. The friction experiments and the finite element analysis method are combined to investigate the tribological properties, under dry friction conditions.
Findings
Test results show that when the amplitude is 0.15 mm and frequency is 10, ST surface has the lowest friction coefficient of 0.373, and exhibits great anti-friction effect. It also possesses a complete texture edge after friction. The friction reduction effect of ST with larger or smaller amplitude and frequency is worse.
Originality/value
The results of this study can provide a guidance for the design optimization of ST of reciprocating sliding contact surfaces, under dry friction conditions.