[3A10] Intelligent stress and condition indicators for adaptation of control actions
E Juuso
University of Oulu, Finland
Detection of the operating conditions is important for adapting the control actions. Condition monitoring is needed in detecting changes. The vibration level grows considerably when the breakdown point is being approached. A slight linear increase of feature values turns to a steeper and steeper increase when the point of failure is approaching. The time of failure depends strongly on machines and the stress caused by operating conditions. Efficient feature extraction and non-linear scaling methodologies have strong effects on the sensitivity. The scaling functions are updated recursively, which is triggered by a fast increase of the deviation indices. The higher levels, which are rough estimates in the beginning, are gradually refined. The parameters of the scaling functions define suitable control limits for the features and indices. Harmful high levels of stress are efficiently detected with control limits adjusted to the process requirements. Trend indices are calculated from the scaled values by using the means obtained for a short and a long time period. The severity of the situation can be evaluated with a deviation index, which combines the current level, the trend index and the change of the trend index. The solution can be extended to the analysis of fluctuations, recursive tuning and linked with fatigue risk estimation. The generalised statistical process control (GSPC) extends SPC to non-linear and non-Gaussian data: the new approach is suitable for a large set of statistical distributions. It operates without interruptions in short run cases and adapts to the changing process requirements. Control charts based on scaled values and indices are combined by artificial and computational intelligence.
