Technical Note Leveraging Variable Frequency Drive Data for Nondestructive Testing and Predictive Maintenance in Industrial Systems
Carl Lee Tolbert
Institute for Globally Distributed Open Research and Education (IGDORE), USA; carl.tolbert@igdore.org
Abstract: Nondestructive testing (NDT) has a crucial role in ensuring the reliability and safety of industrial systems. However, traditional methods typically rely on external sensors, which can lead to increased costs and added complexity. The current study examined an alternative approach using variable-frequency drive (VFD) data for real-time fault detection and predictive maintenance. Most VFDs continuously monitor essential parameters such as motor speed, torque, efficiency, and power consumption, facilitating sensorless condition monitoring that helps detect early-stage motor and apparatus faults without additional hardware. To improve diagnostic capabilities, calculated metrics such as apparent power, efficiency, torque, and energy consumption can deliver more profound insights into system performance, assisting in identifying potential failure patterns. A Python-based data acquisition and visualization system was developed and implemented as an example of a potential solution, enabling centralized monitoring, anomaly detection, and historical data analysis. Future advancements in artificial intelligence and machine learning could further refine automated fault detection by utilizing historical VFD data to predict system failures accurately. By integrating VFD-based diagnostics into NDT, industries can develop scalable, cost-effective, intelligent testing and maintenance solutions that improve reliability and asset management in modern systems. Keywords: nondestructive testing; variable frequency drive; predictive maintenance; industrial monitoring; Python; reliability engineering; controls engineering; industrial automation 1. Introduction Nondestructive testing (NDT) includes various techniques to evaluate the properties of materials, components, and systems without causing damage [1,2]. For practical pur- poses, the advantages of NDT involve defect detection, predictive maintenance, quality assurance, safety enhancements, and cost discipline [1]. Traditional NDT methods rely on established techniques such as dye penetrant testing, magnetic particle inspection, eddy current testing, radiography, ultrasonics, and acoustic emission analysis [2]. Addition- ally, many NDT applications utilize external sensors for precision, defect detection, and assessing environmental changes [3]. Nondestructive testing is extensively utilized across various industries where safety during development and mechanical integrity are critical. In aerospace, it identifies material defects and fatigue in aircraft components, ensuring specified reliability [2]. In the oil and gas sector, NDT helps prevent pipeline failures by monitoring corrosion and material degradation [4]. The manufacturing industry relies on NDT for weld inspections and defect detection in castings, enhancing product quality and compliance [1]. In power generation,
Academic Editor: Fabio Tosti
Received: 28 February 2025 Revised: 18 March 2025 Accepted: 18 March 2025 Published: 24 March 2025
Citation: Tolbert, C.L. Leveraging Variable Frequency Drive Data for Nondestructive Testing and Predictive Maintenance in Industrial Systems. NDT 2025 , 3 , 7. https://doi.org/ 10.3390/ndt3020007 Copyright: © 2025 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).
NDT 2025 , 3 , 7
https://doi.org/10.3390/ndt3020007
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