Thermally Stimulated Depolarization Current Evaluation of Molding Compounds

TSDC (thermally stimulated depolarization current) is one of the most important and popular technique for investigating electret materials. TSDC technique can indicate the magnitude of polarization and depolarization, relaxation time, charge-storage, glass transition, and activation energy. To fully investigate polarization and relaxation for pure epoxy and filled epoxy materials, a TSDC system was built and verified by the research. The article describes the building processes and verification of the TSDC system. TSDC, TSPC, and TWC tests data for epoxy and filled epoxy samples are presented in the article. To compare TSDC technique with other related techniques, DEA (dielectric analysis), DMA (dynamic mechanical analysis), and DSC (differential scanning calorimetry) tests are introduced

Fault detection and diagnosis in HVAC systems using analytical models

Faults that develop in the heat exchanger subsystems in air-conditioning installations can lead to increased energy costs and jeopardise thermal comfort. The sensor and control signals associated with these systems contain potentially valuable information about the condition of the system, and energy management and control systems are able to monitor and store these signals. In practice, the only checks made are to verify set-points are being maintained and that certain critical variables remain within predetermined limits. This approach may allow the detection of certain abrupt or catastrophic faults, but degradation faults often remain undetected until their effects become quite severe. This thesis investigates the appropriateness of using mathematical models to track the development of degradation faults. An approach is developed, which is based on the use of analytical models in conjunction with a recursive parameter estimation algorithm. A subset of the parameters of the models, which are closely related to faults, is estimated recursively. Significant deviations in the values of the estimated parameters from nominal values, which represent `correct operation', are used as an indication that the system has developed a fault. The extent of the deviation from the nominal values is used as an estimate of the degree of fault. This thesis develops the theory and examines the robustness of the parameter estimator using simulation-based testing. Results are also presented from testing the fault detection and diagnosis scheme with data obtained from a simulated air-conditioning system and from a full size test installation

Supervisory Adaptive Control Revisited: Linear-like Convolution Bounds

Classical feedback control for LTI systems enjoys many desirable properties including exponential stability, a bounded noise-gain, and tolerance to a degree of unmodeled dynamics. However, an accurate model for the system must be known. The field of adaptive control aims to allow one to control a system with a great deal of parametric uncertainty, but most such controllers do not exhibit those nice properties of an LTI system, and may not tolerate a time-varying plant. In this thesis, it is shown that an adaptive controller constructed via the machinery of Supervisory Control yields a closed-loop system which is exponentially stable, and where the effects of the exogenous inputs are bounded above by a linear convolution - this is a new result in the Supervisory Control literature. The consequences of this are that the system enjoys linear-like properties: it has a bounded noise-gain, is robust to a degree of unmodeled dynamics, and is tolerant of a degree of time-varying plant parameters. This is demonstrated in two cases: the first is the typical application of Supervisory Control - an integral control law is used to achieve step tracking in the presence of a constant disturbance. It is shown that the tracking error exponentially goes to zero when the disturbance is constant, and is bounded above by a linear convolution when it is not. The second case is a new application of Supervisory Control: it is shown that for a minimum phase plant, the d-step-ahead control law may be used to achieve asymptotic tracking of an arbitrary bounded reference signal. In addition to the convolution bound, a crisp bound is found on the 1-norm of the tracking error when a disturbance is absent