Inspection of natural gas pipelines is necessary to ensure their integrity. Considerable pipeline mileage exists where the lines, particularly those in the smaller-diameter range, have internal restrictions and/or low pressure/flow rates. Conventional magnetic flux leakage (MFL) inspection pigs cannot be used because the product flow and pressure is not sufficient to propel the pig, and the large MFL magnets cannot readily move through restricted areas. To overcome these problems, an untethered, self-powered tool was developed that can adjust to inspect different pipe sizes and can retract to pass through obstructions such as elbows and tees. Southwest Research Institute developed a remote-field eddy current (RFEC) inspection system for detecting and characterizing pipe wall loss, and this system was integrated with Explorer II, a robotic transport device developed by Carnegie Mellon. The resulting tool has the capability to inspect 6- to 8-inch-diameter pipelines containing tight bends and tees, and can be launched, operated, and retrieved with the pipeline in service. This paper describes the RFEC inspection technology, the RFEC system modules developed for Explorer II, and preliminary test results.
A critical step in mechanism noise reduction for data-processing equipment is identification of sources. Techniques such as disabling mechanisms, microphone probing, and frequency analysis are useful here. We have discussed procedures based on noise-time analysis within machine cycles at past Acoustical Society of America meetings as being particularly useful for this work. For high-speed impacting machinery, normally used analog acoustical instruments are inadequate for noise-time analysis. Procedures have been devised using a high-speed electronic switch attenuator in a “stroboscopic” mode to overcome these limitations. This technique has been useful for source identification and examples are presented. Digital procedures have considerable potential for these applications. Fast Fourier transform digital filtering, and related techniques are useful and we have used these procedures where applicable in noise-time analysis using an IBM 1130 computer system. The practical limit here is in processing time and/or computer size (and cost). Our present direction is combining the best of both digital and analog techniques in a hybrid system. The resulting approaches will be discussed as more nearly optimum than other approaches and most usable for mechanism noise identification.
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