Fiber Optic Microbend Sensor Thesis


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Analysis of Fiber Optic Microbend Sensors for Use in Vehicle Classification and Weigh-in-Motion Systems.

This thesis was a continuation of the weigh-in-motion and vehicle classification projects that have taken place at Florida Institute of Technology. The need to weigh and classify vehicles was based on the damage that large trucks have on road surfaces. The project used a system with two fiber optic microbend sensors that were embedded in the pavement or placed on top of the road. When vehicles passed over a sensor, a loss of light occurred that corresponded to the weight of the vehicle and the length of time the vehicle’s tire made contact with the sensor. This loss was converted to a voltage and sampled by a computer. The voltage drop could then be analyzed to determine key characteristics of the vehicle.

The construction and installation of the fiber optic microbend sensors were presented. This included new methods for building better sensors and new installation techniques for more consistent light loss and extended sensor life. A road top sensor was also being developed that would be relocatable require minimal installation.

A software application was written specifically for this project. It used a National Instruments DAQCard 700 for A/D conversions. The application captured and analyzed analog data produced by vehicles passing over the sensors. The application determined a vehicle’s velocity, classification, and weight. The Basic Method for weight calculation was presented. This method used the width of the pulses produced by a vehicle passing over the sensors to determine the tire contact patch length. The tire contact patch width and air pressure were estimated for the vehicle and multiplied by contact patch length and a calibration coefficient to produce the weight estimate. The results for this method were presented for light vehicles (Class 2) and large trucks (Class 6). These results had error ranges of approximately ±10% when a vehicle’s correct tire width was used for the weight calculation.

The Area Method for weight calculation was presented. For this method, the trapezoidal approximation of the area between the trigger level and the pulse curve was calculated. The area was then normalized for the sample rate and vehicle velocity, and multiplied by an area to weight conversion coefficient to produce the weight estimate. The results for this method were presented for light vehicles (Class 2) and large trucks (Class 6). These results had an error range of approximately ±10% for the large trucks.

The vehicle classification was determined from the number of axles and the axle separation lengths. The classification method used was the same method used by TrafiCOMP ® , and is based on the Maine Highway Department’s Scheme F (Braley , 1984) which was based on the FHWA’s Vehicle Classification guidelines (FHWA-PL- 95-031).

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