Optimization of calculations for wireless condition monitoring systems

Abstract

Health Indicator for machine health monitoring are generally well-established. Regardless of the type of the Condition Monitoring System (stationary, remote, wireless) and the system’s manufacturer, the most commonly applied Health Indicators include wideband estimators (peak-to-peak, Root Mean Square, kurtosis, crest factor, velocity Root Mean Square), narrowband estimators (speed harmonics, gear meshing frequencies, rolling-element bearing characteristic frequen-cies), and simple spectral bands corresponding to a group of machine elements, e.g. 100–2000 Hz for gearboxes. In order to improve the reliability of Health Indicators, stationary Condition Monitoring System implement averaging and advanced data acquisition logic. In order to detect faults in very early stage, Condition Monitoring System implement resampling, order analysis, Deterministic Random Separation, and for instance auxiliary visualization. However, in case of wireless Condition Monitoring System without a speed sensor, improvement might concern only three aspect, namely hardware realization, data transmission, and power savings, where the latter one might be decomposed into data transfer power consumption, data acquisition power consumption, and data analysis power consumption. The current paper illustrates few recent ideas on how to minimize the power consumptions for data analysis. As it will be shown, it is possible to reduce the computational cycles by more than 60% comparing to stationary Condition Monitoring System while losing acceptable level of the quality of calculated Health Indicators.