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The processing characteristics and the induced compressive damage in filament-wound carbon/carbon composites were examined. Tubular carbon/phenolic composites were made by the filament winding method. The inside diameter was 25.4 mm and the nominal thickness was 2.5 mm. The cured composites were then carbonized. Three more cycles of matrix densification were repeated. After densification, the composites were graphitized at 26008C. Compressive tests were then carried out for the cured, carbonized, and graphitized composites. The load was applied directly on the end of the tube. The loading response and the induced damage were studied. Their microscopic fracture behaviors were examined by optical and scanning electron microscopes. With the heating temperature increased, the damage modes shifted from a ductile fracture in the cured composites to a more brittle fracture in the graphitized composites. The resulting strength and stiffness were also decreased significantly with the temperature. Kinking of fibers was the major mode in the cured specimens, while separation of bundles became more prominent in the graphitized specimens. FIG. 14. SEM image of the graphitized specimen (G45) showing layered patterns in the fractured matrix. FIG. 13. SEM image of the fractured carbonized specimen (C55) showing fiber bending fracture.

The collision fault detection of a XXY stage is proposed for the first time in this paper. The stage characteristic signals are extracted and imported into the master and slave chaos error systems by signal filtering from the vibratory magnitude of the stage. The trajectory diagram is made from the chaos synchronization dynamic error signals E1 and E2. The distance between characteristic positive and negative centers of gravity, as well as the maximum and minimum distances of trajectory diagram, are captured as the characteristics of fault recognition by observing the variation in various signal trajectory diagrams. The matter-element model of normal status and collision status is built by an extension neural network. The correlation grade of various fault statuses of the XXY stage was calculated for diagnosis. The dSPACE is used for real-time analysis of stage fault status with an accelerometer sensor. Three stage fault statuses are detected in this study, including normal status, Y collision fault and X collision fault. It is shown that the scheme can have at least 75% diagnosis rate for collision faults of the XXY stage. As a result, the fault diagnosis system can be implemented using just one sensor, and consequently the hardware cost is significantly reduced.