Accurate vehicle classification including motorcycles using piezoelectric sensors

Thesis (M.S. ECE)--University of Oklahoma, 2012.Includes bibliographical references (leaves 88-90).State and federal departments of transportation are charged with classifying vehicles and monitoring mileage traveled. Accurate data reporting enables suitable roadway design for safety and capacity. Vehicle classifier devices currently employ inductive loops, piezoelectric sensors, or some combination of both, to aid in the identification of 13 Federal Highway Administration (FHWA) classifications. However, systems using inductive loops have proven unable to accurately classify motorcycles and record pertinent data. Previous investigations undertaken to overcome this problem have focused on classification techniques utilizing inductive loops signal output, magnetic sensor output with neural networks, or the fusion of several sensor outputs. Most were off-line classification studies with results not directly intended for product development. Vision, infrared, and acoustic classification systems among others have also been explored as possible solutions. This thesis presents a novel vehicle classification setup that uses a single piezoelectric sensor placed diagonally on the roadway to accurately identify motorcycles from among other vehicles, as well as identify vehicles in the remaining 12 FHWA classifications. An algorithm was formulated and deployed in an embedded system for field testing. Both single element and multi-element piezoelectric sensors were investigated for use as part of the vehicle classification system. The piezoelectric sensors and vehicle classification system reported in this thesis were subsequently tested at the University of Oklahoma-Tulsa campus. Various vehicle types traveling at limited vehicle speeds were investigated. The newly developed vehicle classification system demonstrated results that met expectation for accurately identifying motorcycles

Fiber-optic interferometric sensor for monitoring automobile and rail traffic

This article describes a fiber-optic interferometric sensor and measuring scheme including input-output components for traffic density monitoring. The proposed measuring system is based on the interference in optical fibers. The sensor, based on the Mach-Zehnder interferometer, is constructed to detect vibration and acoustic responses caused by vehicles moving around the sensor. The presented solution is based on the use of single-mode optical fibers (G.652.D and G.653) with wavelength of 1550 nm and laser source with output power of 1 mW. The benefit of this solution lies in electromagnetic interference immunity and simple implementation because the sensor does not need to be installed destructively into the roadway and railroad tracks. The measuring system was tested in real traffic and is characterized by detection success of 99.27% in the case of automotive traffic and 100% in the case of rail traffic.Web of Science2662995298

Novel Approaches for Structural Health Monitoring

The thirty-plus years of progress in the field of structural health monitoring (SHM) have left a paramount impact on our everyday lives. Be it for the monitoring of fixed- and rotary-wing aircrafts, for the preservation of the cultural and architectural heritage, or for the predictive maintenance of long-span bridges or wind farms, SHM has shaped the framework of many engineering fields. Given the current state of quantitative and principled methodologies, it is nowadays possible to rapidly and consistently evaluate the structural safety of industrial machines, modern concrete buildings, historical masonry complexes, etc., to test their capability and to serve their intended purpose. However, old unsolved problematics as well as new challenges exist. Furthermore, unprecedented conditions, such as stricter safety requirements and ageing civil infrastructure, pose new challenges for confrontation. Therefore, this Special Issue gathers the main contributions of academics and practitioners in civil, aerospace, and mechanical engineering to provide a common ground for structural health monitoring in dealing with old and new aspects of this ever-growing research field

MULTI‐PHYSICAL MODELLING AND PROTOTYPING OF AN ENERGY HARVESTING SYSTEM INTEGRATED IN A RAILWAY PNEUMATIC SUSPENSION

The aim of this PhD thesis is the investigation of an energy harvesting system to be integrated in a railway pneumatic spring to recovery otherwise wasted energy source from suspension vibration. Exploiting the piezoelectric effect to convert the mechanical energy into an electrical one, the final scope consists on the use of this system to power supply one or more sensors that can give useful information for the monitoring and the diagnostics of vehicle or its subsystems. Starting from the analysis of the energy sources, a multi‐physical approach to the study of an energy harvesting system is proposed to take into account all physics involved in the phenomenon, to make the most of the otherwise wasted energy and to develop a suitable and affordable tool for the design. The project of the energy harvesting device embedded in a railway pneumatic spring has been carried out by means of using a finite element technique and multi‐physics modelling activity. The possibility to combine two energy extraction processes was investigated with the purpose of making the most of the characteristics of the system and maximize the energy recovering. Exploiting commercial piezoelectric transducers, an experimental activity was conducted in two steps. A first mock‐up was built and tested on a shaker to develop the device and to tune the numerical model against experimental evidence. In the second step a fullscale prototype of an air spring for metro application with the EH system was realized. In order to test the full‐scale component, the design of a new test bench was carried out. Finally, the Air spring integrated with the EH device was tested and models validated

SMARTI - Sustainable Multi-functional Automated Resilient Transport Infrastructure

The world’s transport network has developed over thousands of years; emerging from the need of allowing more comfortable trips to roman soldiers to the modern smooth roads enabling modern vehicles to travel at high speed and to allow heavy airplanes to take off and land safely. However, in the last two decades the world is changing very fast in terms of population growth, mobility and business trades creating greater traffic volumes and demand for minimal disruption to users, but also challenges, such as climate change and more extreme weather events. At the same time, technology development to allow a more sustainable transport sector continue apace. It is within this environment and in close consultation with key stakeholders, that this consortium developed the vision to achieve the paradigm shift to Sustainable Multifunctional Automated and Resilient Transport Infrastructures. SMARTI ETN is a training-through-research programme that empowered Europe by forming a new generation of multi-disciplinary professionals able to conceive the future of transport infrastructures and this Special Issue is a collection of some of the scientific work carried out within this context. Enjoy the read

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

The Utah Pilot Bridge, Live Load and Dynamic Testing, Modeling and Monitoring for the Long-Term Bridge Performance Program

As part of the Federal Highway Administration\u27s Long-Term Bridge Performance Program, Live Load and Dynamic tests were conducted. A long-term monitoring plan was developed and presented for the Utah Pilot Bridge based on Live Load and Dynamic tests. As one of seven pilot bridges, the Utah Pilot Bridge is one of the first bridges used to initiate the LTBP Program. A formal permit approval process, with the Utah Department of Transportation, was followed to gain permission to conduct the tests and install long-term instrumentation. Analysis provided good results for each test completed, with a summary of test results presented. A Finite Element Model was created and refined based off test data. Instrumentation was installed and checked to ensure quality data was streaming to the collection site

Investigation of Environmental Impacts on Piezoelectric Weigh-In-Motion Sensing System

Transportation by trucks plays a major role in North America’s economy. The growth of this industry will increase the loads on existing roads and highways and raises the possibility of overloaded vehicles, which causes significant damage to the pavement and consequently will reduce the lifespan of the roads. Weigh-in-motion (WIM) systems technology helps to address the challenge of overloaded vehicles. This technology provides traffic monitoring, collects data for pavement research and design, and improves the capacity of static weigh station operations. However, there is still a lack of knowledge about the behaviour of WIM sensors installed in different environments, which affects reliable and precise data gathering. More knowledge is required on proper installation procedures, pavement design for WIM systems, choice of sensor type for location, and calibration processes. This research is intended to explore the behaviour of WIM piezoelectric sensors under different loads and environmental conditions. Specifically, the effects of air and pavement temperature, and weight and speed of trucks are examined with respect to the estimation accuracy of WIM sensors. To accomplish this, three WIM systems composed of different piezoelectric transducers were installed at the CPATT test site at the Waste Management facility of the Region of Waterloo in 2007, and two WIM systems were installed between exits 238 and 250 on Highway 401 eastbound near Woodstock, Ontario. It was concluded that the output of the polymer piezoelectric sensor is influenced by temperature and weight factors but not by normally observed vehicle speed differences. While temperature can be compensated for, not enough information has been gathered yet does the same for weight factor. It should be noted that very low speeds (e.g. < 50 km/hr) result in significant errors for all the sensors, so that in congested sections WIM results should be interpreted accordingly. These results will be useful for investigating the effects of environmental conditions on other WIM systems and for predicting the responses of sensors in actual installation environments. This will assist in the recommendation of: (1) alternative and transparent calibration procedures for the WIM sensor systems, (2) and improved benefits of least expensive technology

Ultrasonic sensor platforms for non-destructive evaluation

Robotic vehicles are receiving increasing attention for use in Non-Destructive Evaluation (NDE), due to their attractiveness in terms of cost, safety and their accessibility to areas where manual inspection is not practical. A reconfigurable Lamb wave scanner, using autonomous robotic platforms is presented. The scanner is built from a fleet of wireless miniature robotic vehicles, each with a non-contact ultrasonic payload capable of generating the A0 Lamb wave mode in plate specimens. An embedded Kalman filter gives the robots a positional accuracy of 10mm. A computer simulator, to facilitate the design and assessment of the reconfigurable scanner, is also presented. Transducer behaviour has been simulated using a Linear Systems approximation (LS), with wave propagation in the structure modelled using the Local Interaction Simulation Approach (LISA). Integration of the LS and LISA approaches were validated for use in Lamb wave scanning by comparison with both analytical techniques and more computationally intensive commercial finite element/diference codes. Starting with fundamental dispersion data, the work goes on to describe the simulation of wave propagation and the subsequent interaction with artificial defects and plate boundaries. The computer simulator was used to evaluate several imaging techniques, including local inspection of the area under the robot and an extended method that emits an ultrasonic wave and listens for echos (B-Scan). These algorithms were implemented in the robotic platform and experimental results are presented. The Synthetic Aperture Focusing Technique (SAFT) was evaluated as a means of improving the fidelity of B-Scan data. It was found that a SAFT is only effective for transducers with reasonably wide beam divergence, necessitating small transducers with a width of approximately 5mm. Finally, an algorithm for robot localisation relative to plate sections was proposed and experimentally validated

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective