The paper considers certain impedimental issues related to the use of magnetic gearbox and magnetic coupling technologies in high performance servo control systems. A prototype magnetic coupling is used as a basis for...The paper considers certain impedimental issues related to the use of magnetic gearbox and magnetic coupling technologies in high performance servo control systems. A prototype magnetic coupling is used as a basis for demonstrating that the underlying torque transfer characteristic is significantly nonlinear when transmitted torque approaches the maximum designed pull-out torque of the device. It is shown that linear controllers for speed control proportional plus integral （PI） and position control proportional plus derivative （PD） result in acceptable performance provided the magnetic coupling operates below 80 % of designed pull-out torque. To fully compensate for the inherent nonlinearity of the torque transfer characteristic, feedback linearizing control laws and state transformations are derived resulting in exactly linear input-output characteristic for position and speed control of magnetically-geared drive-trains. With the addition of state feedback, the closed-loop dynamics for both position and speed control of a magnetically-geared drive-train can be designed to satisfy the integral of time multiplied by absolute error （ITAE） optimized linear response for a step input. Outstanding results are demonstrated through simulation and experimental real-time implementation on a demonstrator magnetically-geared drive-train.展开更多
The paper presents readily implementable approaches for fault detection and diagnosis （FDD） based on measurements from multiple sensor groups, for industrial systems. Specifically, the use of hierarchical clustering...The paper presents readily implementable approaches for fault detection and diagnosis （FDD） based on measurements from multiple sensor groups, for industrial systems. Specifically, the use of hierarchical clustering （HC） and self-organizing map neural networks （SOMNNs） are shown to provide robust and user-friendly tools for application to industrial gas turbine （IGT） systems. HC fingerprints are found for normal operation, and FDD is achieved by monitoring cluster changes occurring in the resulting dendrograms. Similarly, fingerprints of operational behaviour are also obtained using SOMNN based classification maps （CMs） that are initially determined during normal operation, and FDD is performed by detecting changes in their CMs. The proposed methods are shown to be capable of FDD from a large group of sensors that measure a variety of physical quantities. A key feature of the paper is the development of techniques to accommodate transient system operation, which can often lead to false-alarms being triggered when using traditional techniques if the monitoring algorithms are not first desensitized. Case studies showing the efficacy of the techniques for detecting sensor faults, bearing tilt pad wear and early stage pre-chamber burnout, are included. The presented techniques are now being applied operationally and monitoring IGTs in various regions of the world.展开更多
文摘The paper considers certain impedimental issues related to the use of magnetic gearbox and magnetic coupling technologies in high performance servo control systems. A prototype magnetic coupling is used as a basis for demonstrating that the underlying torque transfer characteristic is significantly nonlinear when transmitted torque approaches the maximum designed pull-out torque of the device. It is shown that linear controllers for speed control proportional plus integral （PI） and position control proportional plus derivative （PD） result in acceptable performance provided the magnetic coupling operates below 80 % of designed pull-out torque. To fully compensate for the inherent nonlinearity of the torque transfer characteristic, feedback linearizing control laws and state transformations are derived resulting in exactly linear input-output characteristic for position and speed control of magnetically-geared drive-trains. With the addition of state feedback, the closed-loop dynamics for both position and speed control of a magnetically-geared drive-train can be designed to satisfy the integral of time multiplied by absolute error （ITAE） optimized linear response for a step input. Outstanding results are demonstrated through simulation and experimental real-time implementation on a demonstrator magnetically-geared drive-train.
文摘The paper presents readily implementable approaches for fault detection and diagnosis （FDD） based on measurements from multiple sensor groups, for industrial systems. Specifically, the use of hierarchical clustering （HC） and self-organizing map neural networks （SOMNNs） are shown to provide robust and user-friendly tools for application to industrial gas turbine （IGT） systems. HC fingerprints are found for normal operation, and FDD is achieved by monitoring cluster changes occurring in the resulting dendrograms. Similarly, fingerprints of operational behaviour are also obtained using SOMNN based classification maps （CMs） that are initially determined during normal operation, and FDD is performed by detecting changes in their CMs. The proposed methods are shown to be capable of FDD from a large group of sensors that measure a variety of physical quantities. A key feature of the paper is the development of techniques to accommodate transient system operation, which can often lead to false-alarms being triggered when using traditional techniques if the monitoring algorithms are not first desensitized. Case studies showing the efficacy of the techniques for detecting sensor faults, bearing tilt pad wear and early stage pre-chamber burnout, are included. The presented techniques are now being applied operationally and monitoring IGTs in various regions of the world.
