Kwok Tom

A Wireless Sensor System for Prognostics and Health Management

This paper introduces a novel radio-frequency-based wireless sensor system and describes its prognostics and health management functions. The wireless sensor system includes a radio frequency identification sensor tag, a wireless reader, and diagnostic-prognostic software. The software uses the sequential probability ratio test with a cross-validation procedure to detect anomalies, assess degradation, and predict failures. The prognostic performance of the sensor system is demonstrated by a field application.

Fault diagnosis and failure prognosis for engineering systems: A global perspective

Engineering systems, such as aircraft, industrial processes, manufacturing systems, transportation systems, electrical and electronic systems, etc., are becoming more complex and are subjected to failure modes that impact adversely their reliability, availability, safety and maintainability. Such critical assets are required to be available when needed, and maintained on the basis of their current condition rather than on the basis of scheduled or breakdown maintenance practices. Moreover, on-line, real-time fault diagnosis and prognosis can assist the operator to avoid catastrophic events. Recent advances in Condition-Based Maintenance and Prognostics and Health Management (CBM/PHM) have prompted the development of new and innovative algorithms for fault, or incipient failure, diagnosis and failure prognosis aimed at improving the performance of critical systems. This paper introduces an integrated systemsbased framework (architecture) for diagnosis and prognosis that is generic and applicable to a variety of engineering systems. The enabling technologies are based on suitable health monitoring hardware and software, data processing methods that focus on extracting features or condition indicators from raw data via data mining and sensor fusion tools, accurate diagnostic and prognostic algorithms that borrow from Bayesian estimation theory, and specifically particle filtering, fatigue or degradation modeling, and real-time measurements to declare a fault with prescribed confidence and given false alarm rate while predicting accurately and precisely the remaining useful life of the failing component/system. Potential benefits to industry include reduced maintenance costs, improved equipment uptime and safety. The approach is illustrated with examples from the aircraft and industrial domains.

Failure Precursors for Polymer Resettable Fuses

Resettable fuses have been widely used in overcurrent or overtemperature circuit protection designs in computers, automotive circuits, telecommunications equipment, and medical devices. Abnormal behavior of a resettable fuse can damage a circuit. This paper identifies and experimentally assesses the failure precursor parameters of a polymer positive temperature coefficient resettable fuse. It is shown that the degradation of the resettable fuse can be monitored, detected, and predicted based on the monitoring of these precursor parameters.

Detection of surface and buried mines with an UHF airborne SAR

A small minefield was deployed in the desert near Yuma, Arizona in June of 1993. Radar data of this minefield was collected by ground-based and airborne radar sensors. The minefield consists of M-20 metal and M-80 plastic anti-armor mines and Valmara-69 antipersonnel mines. The mines were deployed on the surface and buried at three different depths. Images and analysis of the minefield, which are derived from data collected by the SRI FOLPEN II synthetic aperture radar, are presented here. The minefield was imaged over three bands from 100 to 500 MHz and at various depression angles with this radar sensor. The image analysis is compared to the modeling results of surface and buried mine-like objects. We also show the results of a new radio frequency interference (RFI) rejection algorithm and the image quality improvement we achieved.

Anomaly Detection of Polymer Resettable Circuit Protection Devices

As circuit protection devices, failure or abnormal behavior of polymer positive-temperature-coefficient resettable devices can cause damage to circuits. It is necessary to detect anomalies in the resettable circuit protection devices to provide early warning of failure and avoid damage to a circuit. In this paper, a novel anomaly detection method, the cross-validation-based sequential probability ratio test, is developed and applied to the failure precursor parameters of the resettable circuit protection devices to conduct anomaly detection. The cross-validation-based sequential probability ratio test integrates the advantages of both the sequential probability ratio test for in situ anomaly detection and the cross-validation technique for model parameter selection to reduce the probability of false and missed alarms in anomaly detection. The cross-validation-based sequential probability ratio test solves the model parameter selection difficulty of the traditional sequential probability ratio test and improves its performance in anomaly detection.

New features for diagnosis and prognosis of systems based on empirical mode decomposition

We present a new procedure to generate additional features for system diagnosis. The procedure is based on empirical mode decomposition of measured signals obtained by monitoring the relevant state of a system. This procedure is different from the conventional procedures for defining features, which are generally obtained using the statistics of the measured signal, the matched filter outputs, and the wavelet decomposition of measured signals. Features derived by this new procedure complement the existing features for diagnosis, and therefore they should improve performance of the classifier used to diagnose systems. We illustrate the procedure by generating new features for diagnosis of the AH64A helicopter transmission assembly.

Failure Causes of a Polymer Resettable CircuitProtection Device

As a circuit protection device, failure or abnormal behavior of polymer positive-temperature-coefficient resettable devices can cause damage to circuits. Identification of failure modes and determination of failure causes are necessary to improve the reliability of resettable circuit protection devices and understand their limitations. In this study, a series of experiments was conducted to identify the failure modes of polymer positive-temperature- coefficient resettable circuit protection devices. The causes of failures of a polymer positive-temperature-coefficient resettable circuit protection device were determined by failure analyses, including analysis of the increase in surface temperature using an infrared camera, interconnection analysis using cross-sectioning and environmental scanning electron microscopy, analysis of the microstructures of carbon-black-filled polymer composite, thermal property analysis of the polymer composite, and coefficient of thermal expansion analysis of different parts of the resettable circuit protection device.