Bispectral analysis for on-line monitoring of stamping operation
Owing to the ever-increased demand for product quality improvement and production cost reduction, on-line monitoring of stamping operations has become a common practice in shop floors around the world today. Based on a market survey, for most stamping processes, monitoring systems use tonnage signals and/or strain signals. Recently, a few attempts have been reported using acceleration signals as they contain rich information and are relatively inexpensive. However, it is known that acceleration signals are vulnerable to the noise disturbances, and hence are less robust. This paper presents a study that uses bispectrum to analyze the acceleration signals. It is shown that the bispectrum can suppress Gaussian color noise to boost the signal-to-noise ratio. It also extracts the features of the signal that are related to the defective parts (such as material too thick or slug). The experimental results demonstrate that the method presented is effective and has a good potential for applications in shop floor. We also present new method for reducing the computation load in the process.
bispectral analysis stamping process condition monitoring higher order statistics