Wire EDM failure prediction and process control based on sensor fusion and pulse train analysis

2021 ◽  
Author(s):  
P M Abhilash ◽  
Dupadu Chakradhar
Keyword(s):  
Process Control ◽  
Sensor Fusion ◽  
Pulse Train ◽  
Failure Prediction ◽  
Wire Edm

scholarly journals Sensor Fusion: Comprehensive Real-Time, On-Line Monitoring for Process Control via Visible, Near-Infrared, and Raman Spectroscopy

ACS Sensors ◽  
2020 ◽  
Vol 5 (8) ◽  
pp. 2467-2475
Author(s):  
Amanda M. Lines ◽  
Gabriel B. Hall ◽  
Susan Asmussen ◽  
Jarrod Allred ◽  
Sergey Sinkov ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Process Control ◽  
Real Time ◽  
Sensor Fusion ◽  
Near Infrared ◽  
Infrared And Raman Spectroscopy ◽  
On Line

scholarly journals Preparation and Cluster Analysis of Data from the Industrial Production Process for Failure Prediction

2016 ◽  
Vol 24 (39) ◽  
pp. 111-116 ◽  
Author(s):  
Martin Németh ◽  
German Michaľčonok
Keyword(s):  
Data Mining ◽  
Cluster Analysis ◽  
Process Control ◽  
Production Process ◽  
Control Systems ◽  
Failure Prediction ◽  
Data Mining Algorithms ◽  
Failure Data ◽  
Process Control Systems ◽  
And Cluster Analysis

Abstract This article is devoted to the initial phase of data analysis of failure data from process control systems. Failure data can be used for example to detect weak spots in a production process, but also for failure prediction. To achieve these goals data mining techniques can be used. In this article, we propose a method to prepare and transform failure data from process control systems for application of data mining algorithms, especially cluster analysis.

Wind Turbine Gearbox Failure Prediction Based on Time Series Analysis and Statistical Process Control

2011 ◽  
Vol 347-353 ◽  
pp. 2236-2240 ◽  
Author(s):  
Fei Fei Wang ◽  
Xiao Qing Xiao ◽  
Hong Shan Zhao
Keyword(s):  
Time Series ◽  
Process Control ◽  
Wind Turbine ◽  
Statistical Process Control ◽  
Arima Model ◽  
Failure Prediction ◽  
Temperature Data ◽  
Operating Conditions ◽  
Statistical Process ◽  
Normal Operating

The Time Series method and Statistical Process Control strategy is applied to predict failures of wind turbine gearboxes. First, based on the real-time temperature data of gearboxes measured by temperature sensors, the temperature prediction model under normal operating conditions is established by ARIMA model. The analysis of the predicted values and the actual values of gearbox temperature is done, and proves that its residuals are normally distributed; then combined with statistical process control (SPC) methods, the big number of temperature data is used to calculate the standard deviation(σ) of residuals, and the gearbox failure threshold will be identified; Finally, the temperature data are analyzed both in normal operating condition and the failure condition to determine the operation status of the gearbox, statistical analysis and residual charts are carried out for gearbox failure prediction, verifying the feasibility and effectiveness of the proposed method.

scholarly journals Sensor fusion for intelligent process control.

2004 ◽  
Author(s):  
John J. Connors ◽  
Kevin Hill ◽  
David Hanekamp ◽  
William F. Haley ◽  
Robert J. Gallagher ◽  
...  
Keyword(s):  
Process Control ◽  
Sensor Fusion ◽  
Intelligent Process ◽  
Intelligent Process Control

Flow and Gauge Sensor Fusion in Vapour Phase Soldering Ovens for Optimized Process Control

2021 ◽  
Author(s):  
Attila Geczy ◽  
Mohamed Amine Alaya ◽  
Egon Rozs ◽  
Daniel Straubinger ◽  
Balazs Illes
Keyword(s):  
Process Control ◽  
Sensor Fusion ◽  
Vapour Phase

INSTRUMENTATION - Mass Spectrometry Process Control

1956 ◽  
Vol 48 (2) ◽  
pp. 81-84
Author(s):  
William Priestley ◽  
B. Dudenbostel, Jr.
Keyword(s):  
Mass Spectrometry ◽  
Process Control
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