Study on Self-Localization with Ultrasonic Sensor Array in Consideration of Environment Resistance

Tohoku University田所諭課

Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

High precision hybrid RF and ultrasonic chirp-based ranging for low-power IoT nodes

Hybrid acoustic-RF systems offer excellent ranging accuracy, yet they typically come at a power consumption that is too high to meet the energy constraints of mobile IoT nodes. We combine pulse compression and synchronized wake-ups to achieve a ranging solution that limits the active time of the nodes to 1 ms. Hence, an ultra low-power consumption of 9.015 µW for a single measurement is achieved. The operation time is estimated on 8.5 years on a CR2032 coin cell battery at a 1 Hz update rate, which is over 250 times larger than state-of-the-art RF-based positioning systems. Measurements based on a proof-of-concept hardware platform show median distance error values below 10 cm. Both simulations and measurements demonstrate that the accuracy is reduced at low signal-to-noise ratios and when reflections occur. We introduce three methods that enhance the distance measurements at a low extra processing power cost. Hence, we validate in realistic environments that the centimeter accuracy can be obtained within the energy budget of mobile devices and IoT nodes. The proposed hybrid signal ranging system can be extended to perform accurate, low-power indoor positioning

Collaborative signal and information processing for target detection with heterogeneous sensor networks

In this paper, an approach for target detection and acquisition with heterogeneous sensor networks through strategic resource allocation and coordination is presented. Based on sensor management and collaborative signal and information processing, low-capacity low-cost sensors are strategically deployed to guide and cue scarce high performance sensors in the network to improve the data quality, with which the mission is eventually completed more efficiently with lower cost. We focus on the problem of designing such a network system in which issues of resource selection and allocation, system behaviour and capacity, target behaviour and patterns, the environment, and multiple constraints such as the cost must be addressed simultaneously. Simulation results offer significant insight into sensor selection and network operation, and demonstrate the great benefits introduced by guided search in an application of hunting down and capturing hostile vehicles on the battlefield

Structural Health Monitoring of Large Structures Using Acoustic Emission-Case Histories

Acoustic emission (AE) techniques have successfully been used for assuring the structural integrity of large rocket motorcases since 1963 [...

A phased array-based method for damage detection and localization in thin plates

A method for damage localization based on the phased array idea has been developed. Four arrays oftransducers are used to perform a beam-forming procedure. Each array consists of nine transducersplaced along a line, which are able to excite and register elastic waves. The A0 Lamb wave mode hasbeen chosen for the localization method. The arrays are placed in such a way that the angulardifference between them is 458 and the rotation point is the middle transducer, which is common for allthe arrays. The idea has been tested on a square aluminium plate modeled by the Spectral Element Method. Two types of damage were considered, namely distributed damage, which was modeled asstiffness reduction, and cracks, modeled as separation of nodes between selected spectral elements.The plate is excited by a wave packet. The whole array system is placed in the middle of the plate.Each linear phased array in the system acts independently and produces maps of a scanned fieldbased on the beam-forming procedure. These maps are made of time signals (transferred to spacedomain) that represent the difference between the damaged plate signals and those from the intactplate. An algorithm was developed to join all four maps. The final map is modified by proposed signal processing algorithm to indicate the damaged area of the plate more precisely. The problem fordamage localization was investigated and exemplary maps confirming the effectiveness of theproposed system were obtained. It was also shown that the response of the introduced configurationremoves the ambiguity of damage localization normally present when a linear phased array is utilized.The investigation is based exclusively on numerical data

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

A noncontact ultrasonic platform for structural inspection

Miniature robotic vehicles are receiving increasing attention for use in nondestructive testing (NDE) due to their attractiveness in terms of cost, safety, and their accessibility to areas where manual inspection is not practical. Conventional ultrasonic inspection requires the provision of a suitable coupling liquid between the probe and the structure under test. This necessitates either an on board reservoir or umbilical providing a constant flow of coupling fluid, neither of which are practical for a fleet of miniature robotic inspection vehicles. Air-coupled ultrasound offers the possibility of couplant-free ultrasonic inspection. This paper describes the sensing methodology, hardware platform and algorithms used to integrate an air-coupled ultrasonic inspection payload into a miniature robotic vehicle platform. The work takes account of the robot's inherent positional uncertainty when constructing an image of the test specimen from aggregated sensor measurements. This paper concludes with the results of an automatic inspection of a aluminium sample