Vibration signatures of defective roller bearings on railroad freight cars were analyzed in an effort to develop an algorithm for detecting bearing defects. The effort is part of a project to develop an on-board condition monitoring system for freight trains. The Office of Research and Development of the Federal Railroad Administration (FRA) is sponsoring the project. The measurements were made at the Transportation Technology Center (TTC) in Pueblo, CO on July 26 – 29, 1999 during the Phase III Field Test of the Improved Wayside Freight Car Roller Bearing Inspection Research Program sponsored by FRA and the Association of American Railroads (AAR). Wheel sets with specific roller bearing defects were installed on a test train consisting of 8 freight cars designed to simulate revenue service. The consist also contained non-defective roller bearings. Accelerometers were installed on the inboard side of the bearing adapters to measure the vibration signatures during the test. Signatures of both defective and non-defective bearings were recorded. The data were recorded on Sony Digital Audio Tape (DAT) Recorders sampling at a rate of 48 K samples per second. We used both ordinary and envelope spectral analysis to analyze the data in an effort to detect features that could be related to known defects. The spectra of non-defective bearings show no remarkable features at bearing defect frequencies. In general, the ordinary spectra of defective bearings do not exhibit remarkable features at the bearing defect frequencies. In contrast, the envelope spectra of defective bearings contain a number of highly resolved spectral lines at these frequencies. In several cases the spectral lines could be related to specific bearing defects. Based on the analysis performed to date, the envelope spectrum technique provides a promising method for detecting defects in freight car roller bearings using an on-board condition monitoring system.
Matched-field processing is a signal processing technique for arrays in which field vectors for assumed source positions (range and depth) are substituted for plane-wave steering vectors in conventional linear and nonlinear beamformers. The field vectors are computed by standard acoustic field models (FFP, normal mode, etc.) which take into account propagation effects in an oceanic waveguide. The output is an ambiguity surface over possible source positions in which a peak is expected at the true source position. Accuracy of the computed fields is limited in large part by our knowledge of the environment. This environmental mismatch causes degradation in localization performance, sometimes leading to large errors in estimation of source position. In order to assess the significance of this effect, simulations were performed in which a measured field is synthesized using a slightly different environmental model from that used for the steering vectors. The differences were introduced to simulate expected errors in sound-speed profile, sediment thickness, and elastic wave speed. Calculations were made for a cw source operating at 10 Hz and depths of 25 and 250 m in a 500 m-deep ocean. The receiver was a 16-element vertical array at ranges of 25 (shadow zone) and 100 km (second convergence zone). A typical Pacific sound velocity profile was assumed. The bottom was modeled by a thin (50-m) sediment layer overlying an elastic subbottom. Degradation in localization performance due to environmental mismatch will be discussed both quantitatively and qualitatively.
Impulse responses of an abyssal plain ocean bottom were measured at grazing angles from 82° to 5°. When low-pass filtered at 100 Hz, the impulse responses consisted of only two arrivals. First arrivals corresponded to the water-sediment interface reflection, and second arrivals were attributed to sound refracted through the ocean bottom. The Rayleigh reflection equation was fitted to the measured reflection coefficients of first arrivals to determine an effective low-frequency sediment density and interfacial sound velocity. Theoretical arrival times of the refracted signals were computer from the sediment sound velocity model c(z)/c0 = (1 – 2pz/c0)−1/2, where c0 and p are the interfacial velocity and velocity gradient at z=0, and z is the depth in the sediment. Model parameters were determined by fitting theoretical to observed arrival times of the refracted pulse. The interfacial sediment sound velocities determined from the two independent methods agreed within 1%. Based on these results theoretical impulse responses were computed using Airy functions, which were in good agreement with measured impulse responses.
A procedure is presented for estimating the impulse response of a linear system from noise contaminated measurements of random input and output signals. The estimation requires ensemble averaged estimates of input and output noise spectra and a priori assumed spectra of the system function and input signal. A minimum mean-square-error estimator is derived and its theoretical signal-to-noise ratio is shown to be a slowly increasing function of the measured signal-to-noise ratios. The procedure is applied to a set of measured underwater explosive charge acoustic signals. For this application additional techniques are presented for synthesizing source replica signals and for accurately determining bubble pulse periods. The result of the deconvolution is a single sharp spike with at least 20-dB bubble pulse suppression. With approximately 20-dB signal-to-noise ratio in the measured signals the processed signal-to-noise ratios range from 10 to 13 dB and are all within 1 dB of theoretical values. Peak-signal to rms-noise ratios are 41 and 38 dB before and after processing, respectively.
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