Synthesizing high-fidelity signals with spikes for prognostic-surveillance applications

A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for performing prognostic-surveillance operations on a monitored system, the method comprising:

• receiving original time-series signals from sensors in the monitored system;
• detecting and removing spikes from the original time-series signals to produce despiked original time-series signals, wherein detecting the spikes involves,
• using the original time-series data to optimize a damping factor, which is applied to a threshold for a spike-detection technique, and
• using the spike-detection technique with the optimized damping factor to detect the spikes;
• generating despiked synthetic time-series signals, which are statistically indistinguishable from the despiked original time-series signals;
• including synthetic spikes, which have the same temporal distribution, amplitude distribution and width distribution as the spikes in the original time-series signals, in the despiked synthetic time-series signals to produce synthetic time-series signals with spikes;
• using the synthetic time-series signals with spikes to train an inferential model;
• and
• using the inferential model to perform prognostic-surveillance operations on subsequently-received time-series signals from the monitored system.

A system that performs prognostic-surveillance operations on a monitored system, comprising:

• at least one processor and at least one associated memory;
• and
• a prognostic-surveillance mechanism that executes on the at least one processor, wherein during operation, the prognostic-surveillance mechanism:
• receives original time-series signals from sensors in the monitored system;
• detects and removes spikes from the original time-series signals to produce despiked original time-series signals, wherein while detecting the spikes, the prognostic-surveillance mechanism,
• uses the original time-series data to optimize a damping factor, which is applied to a threshold for a spike-detection technique, and
• uses the spike-detection technique with the optimized damping factor to detect the spikes;
• generates despiked synthetic time-series signals, which are statistically indistinguishable from the despiked original time-series signals;
• includes synthetic spikes, which have the same temporal distribution, amplitude distribution and width distribution as the spikes in the original time-series signals, in the despiked synthetic time-series signals to produce synthetic time-series signals with spikes;
• uses the synthetic time-series signals with spikes to train an inferential model;
• and
• uses the inferential model to perform prognostic-surveillance operations on subsequently-received time-series signals from the monitored system.