Enhancing and Validating Simulator Data Generation Integrity Through Frequency-Based Analysis

Data seamlessly becomes a critical component for the state estimation and performance optimization of Cyber-Physical Systems (CPSs). Ensuring timely access to CPS data could be challenging due to operation costs, limited accessibility, security and connectivity, etc. CPS simulators have been thoroughly used in industry to synthesize CPS data. However, a common drawback for CPS simulators is the low integrity and fidelity of the synthesized data to the actual system. In this paper, we propose an extension, calibration, and validation to enhance the data synthesis integrity of an industrial CPS simulator. Behavior patterns are inferred from actual data, using frequency analysis, and applied to the simulation data synthesis, where a calibration using cross-correlation is utilized to fine-tune the data synthesis. According to the analysis results, our enhanced simulation data synthesis demonstrates a correlation of 93.7% to the actual CPS data.