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Article

SCADA-Based Stator-Winding Prognostics: A Temperature-Weighted Work Index for Industrial Motor Health Monitoring

1
Mechanical & Aerospace Engineering Department, University of Houston, Houston, TX 77204, USA
2
SLB, Houston, TX 77042, USA
*
Author to whom correspondence should be addressed.
Machines 2026, 14(4), 425; https://doi.org/10.3390/machines14040425
Submission received: 14 February 2026 / Revised: 28 March 2026 / Accepted: 8 April 2026 / Published: 11 April 2026

Abstract

Industrial predictive maintenance programs often rely on SCADA historian signals characterized by low-frequency sampling and asynchronous reporting intervals. These data constraints, specifically non-uniform scan rates and inter-tag time misalignment, limit the applicability of high-resolution or sensor-intensive prognostic models. This study proposes a lightweight, physics-informed health proxy, the temperature-weighted work (TWW) index, designed to monitor motor stator-winding degradation within these industrial limitations. The TWW index accumulates mechanical work derived from torque and speed measurements, weighted by an adaptive exponential temperature-emphasis function that penalizes operation at elevated temperatures. The formulation is inspired by practical thermal-aging heuristics such as Montsinger’s rule in the qualitative sense that higher temperatures are treated as disproportionately more damaging, but it is not intended as a direct implementation of a fixed absolute-temperature life law. Instead, it is designed as a lightweight adaptive index suitable for online SCADA-based implementation. To address SCADA-specific irregularities, the framework incorporates data synchronization and resampling techniques to align heterogeneous tags, alongside power-thresholding to isolate degradation-relevant load periods. The resulting cumulative index is mapped to a normalized health/RUL proxy using failure-referenced thresholds identified from historical events. Validation using field data from industrial three-phase motors demonstrates that the TWW index provides a monotonic degradation profile that is consistent with documented winding-related failures and proactive removals. Case studies confirm that the model enabled proactive maintenance interventions by signaling the terminal phase of insulation life before catastrophic breakdown, offering a hardware-free and scalable solution for real-time asset management.
Keywords: SCADA data; stator-winding degradation; temperature-weighted work (TWW); remaining useful life (RUL); physics-informed prognostics SCADA data; stator-winding degradation; temperature-weighted work (TWW); remaining useful life (RUL); physics-informed prognostics

Share and Cite

MDPI and ACS Style

Khaled, O.; Rekik, M.; Tang, Y.; Franchek, M.A. SCADA-Based Stator-Winding Prognostics: A Temperature-Weighted Work Index for Industrial Motor Health Monitoring. Machines 2026, 14, 425. https://doi.org/10.3390/machines14040425

AMA Style

Khaled O, Rekik M, Tang Y, Franchek MA. SCADA-Based Stator-Winding Prognostics: A Temperature-Weighted Work Index for Industrial Motor Health Monitoring. Machines. 2026; 14(4):425. https://doi.org/10.3390/machines14040425

Chicago/Turabian Style

Khaled, Omar, Malek Rekik, Yingjie Tang, and Matthew Albert Franchek. 2026. "SCADA-Based Stator-Winding Prognostics: A Temperature-Weighted Work Index for Industrial Motor Health Monitoring" Machines 14, no. 4: 425. https://doi.org/10.3390/machines14040425

APA Style

Khaled, O., Rekik, M., Tang, Y., & Franchek, M. A. (2026). SCADA-Based Stator-Winding Prognostics: A Temperature-Weighted Work Index for Industrial Motor Health Monitoring. Machines, 14(4), 425. https://doi.org/10.3390/machines14040425

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