论文信息 - Multiple fault diagnosis for a machine tool's flood coolant system using a neural network

Multiple fault diagnosis for a machine tool's flood coolant system using a neural network

Abstract This paper presents a method for diagnosing “multiple faults” and the levels of severity of the individual faults in the flood coolant system of a CNC vertical milling machine tool. The method employs a neural network to perform pattern recognition with “features” extracted from the transient response of the coolant pressure on shut-down.

Paul R. Drake | Difu Pant

[1] Roger Ivor Grosvenor,et al. A Data Acquisition System for Machine Tool Condition Monitoring , 1995 .

[2] P. R. Drake,et al. Fault curves—A novel drift-fault diagnosing method for condition monitoring , 1991 .

[3] D.R. Hush,et al. Progress in supervised neural networks , 1993, IEEE Signal Processing Magazine.

[4] Robert A. Jacobs,et al. Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.

[5] Duc Truong Pham,et al. Neural networks for classifying surface defects on automotive valve stem seals , 1995 .

[6] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .

[7] Richard P. Lippmann,et al. An introduction to computing with neural nets , 1987 .

[8] Duc Truong Pham,et al. Neural Networks for Identification, Prediction and Control , 1995 .