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This paper introduces a new technique, Prism signal processing, which may be used for the tracking of one or more noisy sinusoids in a signal. A simulation study is presented demonstrating the potential of Prism signal processing as an alternative to Prony's method for analyzing exponentially decaying sinusoids. One application is to sensor condition monitoring of an industrial pressure sensor, using ultrasonic excitation to evaluate the sensor's structural integrity. Initial experimental results suggest the Prism technique can reveal details in the resulting frequency/amplitude time series of each component, which is not available through Prony's method.

The efficient operation of industrial processes requires the timely and accurate diagnosis of faults in process equipment, particularly sensors, as acting on faulty measurement data can result in inefficient or dangerous operation. A common fault mode in industrial pressure sensors is mechanical damage resulting in the leakage of the internal oil (used to transmit external pressure to the sensing element) and the development of an air pocket within the device. In previous work, we have experimentally determined the faulty measurement characteristics of a commercial pressure sensor, where the sensor manufacturer has provided modified sensors with calibrated degrees of oil loss. The current paper develops a mathematical model of this tensoresistive pressure sensor, which describes and explains the impact that oil loss, and hence the presence of an air pocket, has on the static measurement response.

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