A winding can fail from dielectric aging and internal partial-discharge activity long before it ever produces a vibration signature -- exactly the blind spot in most maintenance references built around a mechanically-oriented equipment model.
Most predictive maintenance literature still treats electrical equipment as one more entry on a general machine-train, diagnosed with the same short list of techniques used on any rotating asset. Electrical equipment does not fail that way. A stator winding degrades through dielectric aging and internal discharge activity long before it shows up in a vibration reading. A switchgear connection degrades thermally and electrically at the same time. A rotor bar fault shows up in the current spectrum before it shows up anywhere else. Engineers responsible for motors, transformers, switchgear, and protective relays are often left piecing together this knowledge from scattered standards documents, vendor manuals, and conference papers, without a single reference that ties each diagnostic method back to the electrical failure physics driving it.
This handbook is built specifically around the failure physics of electrical equipment rather than a borrowed mechanical-reliability framework. It works from the underlying degradation mechanism to the diagnostic technique to the interpretation criteria, and every worked example carries the complete calculation, not a quoted result, so the reasoning behind a pass/fail threshold is never a black box.
Inside, you will:
- Build the reliability mathematics an electrical program runs on: P-F curves, failure rate, MTBF, MTTR, availability, and Weibull-based reliability analysis, plus the cost-benefit case for the investment.
- Recognize the specific failure modes of motors, transformers, switchgear, protective relays, cables, and capacitor and reactor banks.
- Apply and interpret vibration monitoring, motor current signature analysis, infrared thermography, ultrasonic and acoustic-emission testing, partial discharge and insulation diagnostics, power quality monitoring, and transformer dissolved-gas analysis.
- Evaluate switchgear and protective-relay health through contact resistance testing, relay self-testing data, and cable condition monitoring.
- Build the digital layer a modern program depends on: wireless and IoT sensor networks, AI and machine-learning based failure prediction, digital twins, and the cybersecurity practices a networked monitoring system now requires.
- Close the loop from detection to work order through CMMS and cloud data integration.
- Establish, staff, pilot, and scale a predictive maintenance program from an asset-management foundation.
The book is organized around reliability foundations and failure-mode physics, the physical diagnostic techniques themselves equipment class by equipment class, the digital infrastructure that separates a modern program from an older one, and the organizational work of building and sustaining the program. Practice problems, worked answer keys, a glossary, and formula and standards quick-reference appendices support every chapter.
Written for practicing maintenance, reliability, and electrical engineers responsible for rotating machinery, transformers, switchgear, and protective relays, as well as plant engineers building a condition-monitoring program from the ground up. A working knowledge of electrical fundamentals and basic statistics is assumed; no prior condition-monitoring experience is required. Both North American and international engineering-practice traditions are presented side by side throughout.
Add this reference to your library and start tracing every diagnostic technique in your program back to the electrical failure physics it was built to detect.
