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Related Experiment Video

Updated: Jan 10, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

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PumpSpectra: An MCSA-Based Platform for Fault Detection in Centrifugal Pump Systems.

Hamza Adaika¹, Zoheir Tir¹, Mohamed Sahraoui²

¹LEVRES Laboratory, University of El Oued, El Oued 39000, Algeria.

Sensors (Basel, Switzerland)

|November 27, 2025

Summary

PumpSpectra, a Motor Current Signature Analysis (MCSA) platform, accurately detects centrifugal pump faults using stator current data. This system accelerates fault diagnosis, reducing analysis time and costs for industrial predictive maintenance.

Keywords:

centrifugal pump fault detection induction motor industrial monitoring misalignment defects motor current signature analysis predictive maintenance spectral analysis

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Area of Science:

Industrial engineering
Mechanical engineering
Data analytics

Background:

Detecting centrifugal pump faults in industrial settings is difficult due to harsh conditions and limited sensor access.
Fast, explainable fault decisions are crucial for industrial operations.

Purpose of the Study:

To develop and validate PumpSpectra, an industrial Motor Current Signature Analysis (MCSA) platform for detecting mechanical faults in centrifugal pumps.
To assess the accuracy, efficiency, and explainability of the PumpSpectra platform in a real-world industrial environment.

Main Methods:

Developed PumpSpectra, an MCSA platform processing stator-current CSV files using Fast Fourier Transform (FFT) and Short-Time Fourier Transform (STFT).
Implemented transparent, rule-based models for identifying mechanical faults like misalignment, bearing defects, and impeller anomalies.
Conducted field validation at a desalination plant, analyzing 40 operating points.

Main Results:

PumpSpectra achieved 91.2% diagnostic accuracy in identifying pump faults.
Analysis time was reduced by 95% compared to manual MCSA post-processing.
A low false-positive rate of 3.8% was recorded at 0.1 Hz resolution, with successful detection of misalignment.

Conclusions:

Current-only, explainable analytics can effectively support predictive maintenance programs.
PumpSpectra accelerates fault triage, enhances decision traceability, and reduces maintenance costs in pump-driven industrial assets.
The platform demonstrates the viability of advanced data analytics for improving the reliability of critical industrial equipment.