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This paper provides several examples of silicon “micromachined” semiconductor sensors with which the authors are involved for aerospace condition monitoring. This and related work in MEMS (Micro Electro Mechanical Systems) has the potential to revolutionize condition monitoring in aerospace condition and “health monitoring” by (1) moving “smart” electronics out to the sensor chip itself and (2) combining a vast quantity and types of, not only electronic, but micromechanical sensing schemes into the silicon chip . Precisely formed cantilevers, gears, valves, microplumbing and even micro motors of the cross-section of a human hair can be fabricated on a single silicon microchip. Silicon is an excellent mechanical material with a yield strength several times that of stainless steel. Also silicon has excellent thermal properties , whereas compatible silicon dioxide (which we typically use in connection with silicon microelectronics patterning) is virtually a thermal insulator.

High voltage Schottky diodes have been fabricated on 3C-SiC films grown on Si substrates. A Ni metallization process has been developed to fabricate both rectifying and ohmic contacts to SiC by controlling the post-annealing temperature. A high voltage (>150V) breakdown has been obtained at room temperature from the SiC Schottky diode. The Ni-SiC Schottky junction shows a thermal resistance for temperatures as high as 600°C. This technology has good potential for monolithic integration of SiC high power devices and Si integrated circuits.

The High Pressure Oxidizer Turbine (HPOT) discharge temperature of the Space Shuttle Main Engine (SSME) was estimated using Radial Basis Function Neural Networks (RBFNN) during the startup transient. Estimation was performed for both nominal engine operation and during simulated input sensor failures. The K-means clustering algorithm was used on the data to determine the location of the basis function centers. The performance of the RBFNN is compared with that of a feedforward neural network trained with the Quickprop learning algorithm.

Electrically passive optical sensors have been formed using optical waveguides and micromachined-micromechanical structures on silicon substrates. We present recent results on an interferometric pressure sensor where pressure-induced strain in a micromachined diaphragm alters the path length of an optical channel waveguide ring resonator. Pressure is detected as a change in the resonant condition of the ring and found to vary linearly over a range of -100 to 400 kPa with a sensitivity of 0.0094 rad/kPa. Problems with attaching this sensor for testing will be discussed. Our second device is an intensity-type accelerometer utilizing a micromachined cantilever beam. Light transmission across a gap between two channel waveguides, one located on a beam bent by acceleration and another which remains fixed, is measured optically. We show preliminary measurements of the coupling between two closely spaced waveguide sections which agree with overlap integral calculations.

In this work, the goal of enhanced reliability through redundancy is explored. Two levels of fusion have been defined: the first is a fusion of sensors, redundant in both number and type, and the second is a statistical fusion of the resulting data at a software level. An intermediate preprocessing level is required to connect both fusions. The various types of sensors which are included are bulk micromachined flow, pressure and hydrogen sensors and a thin film poly-crystalline silicon temperature sensor. Individual sensors have been fabricated and packaged in arrays. Associated preprocessing has been designed to be able to handle all of the signals coming from each sensor and prepare them for statistical analysis. Data fusion algorithms have been written and tested.

Joining of a PdCr Strain Gage with a Hastelloy X carrier shim to Inconel by a rapid infrared processing technique has been investigated at 1150 °C using a nickel based brazing alloy AMS 4777, Ni-7Cr-3Fe-3.2B-4.5Si-.06C in wt%. The effects of the infrared joining parameters on the joint and base material microstructure, joint shear strength, and delamination tendency of the PdCr gage was investigated. Results show that the joint shear strength is as high as 503 MPa when processed at approximately 1150 °C for 120 seconds. Microstructural examinations of the joint with both an optical microscope and a scanning electron microscope indicate that good wetting exists between the brazing alloy with both the Hastelloy X and Inconel 718. And, the Hastelloy X and Inconel 718 exhibits no noticeable change in microstructure due to the rapid processing cycle of the infrared heating process while the stabilized PdCr wire gage shows little change in resistance.

This paper argues in favor of a human-centered (anthropocentric) approach to modern manufacturing. The bases for these arguments are: (a) worker deskilling and creativity issues, (b) economics, and (c) unresolved problems in automation, such as software reliance and costs. Detailed arguments are avoided owing to space limitations. Finally, some issues confronting human-centered manufacturing are raised.

Efforts have been made to utilize Al constructs to identify flaws in the Space Shuttle Main Engine (SSME) faceplate regions. In order to expand the applicability of these algorithms to a larger problem domain, the automatic visual inspection system(AVIS) has been modified to enable a user with little or no image processing background to define a system capable of identifying flaws on a given set of imagery. This system requires the user to simply identify flawed regions and the selection of processing and feature descriptors is performed automatically. This paper explicates the motivations, definitions, and performance issues associated with the AVIS paradigm.

Building and operating dependable systems is fundamental to many critical applications, such as designing integrated hardware and software systems for vehicles or satellites. Dependable systems techniques, methods, and tools are developed and used by researchers and practitioners working in widely varying disciplines. In order to provide a unifying framework for the successful dissemination and sharing of dependability results, the development of a dependable systems knowledge base is underway.1 Two database support subsystems are under development: one that manages the storage and retrieval of document information, as well as communicating between the user interface layer and the physical database layer, and another that manages the lexicon of dependability terminology for the user interface layer. The system will provide access to information in a sophisticated, intelligent manner that enables a human user to function more effectively in learning and decision-making capacities.