2016 IEEE International Conference on Prognostics and Health Management (ICPHM) 2016
DOI: 10.1109/icphm.2016.7542839
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Identification of a roller screw for diagnosis of flight control actuator

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Cited by 5 publications
(1 citation statement)
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“…These studies contribute to a granular understanding of mechanical failures, facilitating targeted interventions and prolonging the service life of critical components. The comprehensive review of condition monitoring for machine tool feed drives by Butler et al [167], coupled with the data-driven methodology for fault detection in EMAs by Chirico et al [155] shown in Figure 12 and the identification strategy for roller screws in flight control actuators by Breuneval et al [154], collectively illustrate the industry's commitment to leveraging advanced diagnostics for enhancing machine reliability and performance. These studies, spanning the spectrum from theoretical models to practical applications, underscore the critical role of diagnostics in the maintenance and operation of modern mechanical systems.…”
Section: Health Condition Monitoring and Fault Diagnosismentioning
confidence: 99%
“…These studies contribute to a granular understanding of mechanical failures, facilitating targeted interventions and prolonging the service life of critical components. The comprehensive review of condition monitoring for machine tool feed drives by Butler et al [167], coupled with the data-driven methodology for fault detection in EMAs by Chirico et al [155] shown in Figure 12 and the identification strategy for roller screws in flight control actuators by Breuneval et al [154], collectively illustrate the industry's commitment to leveraging advanced diagnostics for enhancing machine reliability and performance. These studies, spanning the spectrum from theoretical models to practical applications, underscore the critical role of diagnostics in the maintenance and operation of modern mechanical systems.…”
Section: Health Condition Monitoring and Fault Diagnosismentioning
confidence: 99%