Rudolph Alfred Albert Koegl

A new approach to on-line turn fault detection in AC motors

Turn fault detection is based on the principal that symmetrical (unfaulted) motors powered by symmetrical multiphase voltage sources will have no negative sequence currents flowing in the leads. A turn-to-turn fault will break that symmetry and give rise to a negative sequence current which may then be used as a measure of fault severity or to initiate protective action such as a circuit breaker trip. A new way of looking at the effects of turn faults has been developed that improves sensitivity and speed while reducing the probability of misdetection, taking into account voltage balance, load or voltage variation and instrument errors. The method has been implemented on a PC and tested, in real time, on a specially prepared small motor. Reliable detection of one shorted turn out of 648 turns per phase (in a Y connected motor) was demonstrated with the fault indicator becoming fully developed in two cycles of line frequency after initiation of the fault.

Sensorless, online motor diagnostics

Early detection of abnormalities in electric motors helps to avoid expensive failures. Motor current signature analysis (MCSA) implemented in a computer-based motor monitor can contribute to such condition-based maintenance functions. Such a system may also detect an abnormality in the process as well as the motor. Extensive online monitoring of the motors can lead to greater plant availability, extended plant life, higher quality product, and smoother plant operation. With advances in digital technology over the last several years, adequate data processing capability is now available on cost-effective, microprocessor-based, protective-relay platforms to monitor motors for a variety of abnormalities in addition to the normal protection functions. Such multifunction monitors, are displacing the multiplicity of electromechanical devices commonly applied for many years. Following some background information on motor monitoring, this article features recent developments in providing tools for the diagnosis of faults or incipient faults in electric motor drives, including: sensorless torque measurement; direct detection of turn-to-turn short circuits; detection of cracked or broken rotor bars; and detection of bearing deterioration.

An adaptive, on-line, statistical method for bearing fault detection using stator current

It is well-known that motor current is a nonstationary signal whose properties vary with respect to the time varying operating conditions of the motor. As a result Fourier analysis makes it difficult to recognize fault conditions from the normal operating conditions of the motor. Time-frequency analysis, on the other hand, unambiguously represents the motor current which makes signal properties related to fault detection more evident in the transform domain. In this paper, we present an adaptive, statistical, time-frequency method for the detection of bearing faults. Due to the time varying normal operating conditions of the motor and the effect of motor geometry on the current, we employ a training base approach in which the algorithm is trained to recognize the normal operating conditions of the motor before the actual testing starts. The experimental results from our study suggests that the proposed method provides a powerful, and a general approach to the motor current based fault detection.

XIM: X-Ray Inspection Module for Automatic High Speed Inspection of Turbine Blades and Automated Flaw Detection and Classification

Under military manufacturing technology funding, a production prototype X-ray Inspection Module (XIM) has been established at General Electric Corporate Research and Development (GE-CRD) and delivered to Quality Technology (QT), General Electric Aircraft Engine Business Group (GE-AEBG). A company funded production unit has been built by GE-AEBG and delivered to the GE-AEBG manufacturing facility in Madisonville, Kentucky where it is in use in production. Computerized tomography (CT) and digital fluoroscopy (DF) images are produced with the system. The CT images provide an image cross-section, and the DF images are much like chest X-rays.The system was designed to automatically inspect and analyze flaws present in turbine blades. It was applied to two flaw types; each type in a different turbine blade. The image processing is performed on complex gray scale images with varying background. The XIM system may be used either automatically or in a manual mode with a trained operator to interpret the images and make quality decisions.

In Process Characterization of Gallium Arsenide Crystals by X-Ray Digital Radiography and Computed Tomography

Gallium arsenide has promised to revolutionize the semiconductor industry for many years. However, numerous practical difficulties have prevented this potential from becoming reality. As part of a DARPA funded effort to enhance the manufacturability of gallium arsenide crystals, we have designed and implemented an x-ray inspection system for imaging these crystals during growth. The objective of the work is to measure melt height, crystal diameter, meniscus shape, and liquid-solid interface shape of a 3 in. diameter crystal grown using the liquid encapsulated Czochralski process. The shape of these structures is a critical factor in determining whether the growth process results in a single crystal with good electrical properties, or whether twinning or polycrystalline growth is present.