Browsing by Subject "interferometry"
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Item Feasibility of the Interferometric Neighboring Fracture Method and Improved Relative Travel Time Measurement(2014-12-16) Shtaygrud, IlaanThe recently proposed Interferometric Neighboring Fracture (INF) localization method places unique and demanding constraints on relative travel time measurement accuracy and precision, while sampling a function of relative travel times between pairs of microseismic events as measured along a linear array. Conducting two synthetic trials, I analyze the relationship between event-receiver geometry and relative travel time measurement error and its effect on the feasibility of INF localization. The results indicate that even for typical hydraulic fracturing monitoring geometries, measurement error can exceed the feasible error limits of INF localization. In order to mitigate this error, I propose a new relative travel time measurement technique, Modified Adaptive Steering (MAS), along with a unique preprocessing methodology, Progressive Template Extraction (PTE). Analyzing synthetic data sets with varying SNR ratios, and a field recorded microseismic data set, I compare the performance of PTE-preprocessed MAS to conventional cross-correlation (CXC). Results of both synthetic and field recorded data analysis indicate that PTE enhanced MAS outperforms CXC as a general lag measurement technique, reducing average lag error by as much as 1.25 ms at SNRs below 10. With respect to the unique constraints of the INF method, PTE-MAS produces as many as 4.2 times as many usable samplings of the relative travel time function, while reducing error in stationary position and lag by up to 15 m and 2.5 ms, respectively.Item Two applications of the Fabry-Perot interferometric sensor(2009-05-15) Xie, ZhaoxiaTwo important applications of the fiber Fabry-Perot Interferometer (FFPI) sensor are investigated: (1) an optical binary switch for aerospace application, and (2) an FFPI weigh-in-motion sensor for measuring the weight of trucks traveling down a highway. In the fiber optical switch, the FFPI sensor is bonded to a copper cantilever to sense the elongation of cavity length induced by force applied to the end of the cantilever via a pushed button. Light from a superluminescent diode light source passes through a scanned Michelson interferometer and is reflected from a sensing FFPI and a reference FFPI to produce a fringe pattern. A secondary interferometer uses a distributed feedback laser light source to compensate for irregularities in the mechanical scanning rate of the moving stage to achieve precision measurement of the optical path difference. The system is calibrated by applying known weights to the cantilever. The elongation measured by the FFPI sensor shows excellent linearity as a function of the force applied, and little hysteresis was observed. By comparing the measured force to a threshold, the system produces a binary signal that indicates the state of the pilotactuated system; i. e., whether or not the button has been pushed. In FFPI weigh-in-motion sensors system, the FFPI sensors are installed in metal bars so that they will experience the strain induced by applied loads and are connected to the Signal Conditioning Unit (SCU). The SCU determines the induced phase shift in the FFPI and produces voltage outputs proportional to the phase shifts. Laboratory Material Testing System tests show that the fiber optic sensor response is a fairly linear function of the axial displacement. In highway tests the FFPI sensors showed strong responses and consistently reproduced the expected characteristics of truck wheel crossings. A falling weight deflectometer was used to calibrate the sensor response and predict unknown loads. All sensors in steel bars and aluminum bars showed excellent repeatability and accurate predictions, with an average relative percentage error within 2%. The study on sensor response variation with applied load positions shows a bell shaped distribution. Truck tests on the road sensors indicate that the repeatability of wheel crossings at similar position is good. The sensor can accurately measure axle spacing, speed, and truck class.