Development of a Wireless Displacement Measurement System Using Acceleration Responses

Skin temperature measurement has always been an important method for evaluating the warm-keeping clothing in winter. In order to realize synchronous real-time and accurate measurement of skin temperature, multi-person and multi-node wireless skin temperature measurement system is designed. Based on LoRa wireless transmission network, this research designed communication protocol and low power consumption circuit and developed a multi-person and multi-node wireless skin temperature measurement system. Twenty-four subjects were selected by this system in alpine regions for field tests on two kinds of warm-keeping clothing. The test results show that the skin temperature measurement system has the characteristics of long transmission distance, high measurement accuracy and simple operation and can meet the requirements of warm-keeping clothing test under extreme conditions.

Design of A Framework for Wireless Body Area Network Health Measurement Systems - written by Daniel Salcedo Pena , Fatima Moumtadi published on 2019/05/29 download full article with reference data and citations

In this paper we propose a compatible design using a smartphone, Bluetooth technology and the Internet to build a wireless physiological measurement system which works in cooperation with a health management function. The advantages in our design include easy portability, high compatibility, small size, wireless connection, low cost and service efficiency. The physiological measurements module provides the necessary measurements such as blood pressure, heart rate, body temperature and electrocardiogram (ECG) results. That information is important for the doctor when diagnosing a patient's health status. The user can easily install the application software on one of three major smartphone platforms. The smartphone, which has been successfully used for physiological measurement (PM) concurrently with Bluetooth technology, receives the measurement through the Internet and sends the result to the remote data center storage.

Putting stroke accounts for 40∼50% of total strokes during a golf rounding. Grasping force of putter griping and motion of wrists during a putting stroke are the most important factors for evaluation of the putting event. In this paper, we developed a wireless grip and acceleration measurement system using force sensors and accelerometers for detection and analysis of the golf putting.

In this paper, an Arduino-based real time wireless temperature measurement and logger system is presented. Wireless transmission of the temperature data occurs via a Bluetooth link. An experimental setup to achieve reliable output was prepared using LM35 temperature sensor. The real time temperature information obtained was observed at MATLAB® Graphical User Interface and at mobile phones via a basic hybrid mobile application (Android, Windows, ios) designed by us. Experimental result and percentage error curve endorse the reliability and feasibility of the proposed system. Moreover, a Global System of Mobile (GSM) module is also used for sending alert messages to a pre-assigned mobile number when an alarm condition is achieved.

Loads at which diagnostic research should be carried out were selected of operational investigation and preliminary diagnostic tests. It is difficult to keep the load constant during operational tests, so there is a need to apply the theory of the experiment. Operational investigation determined, the average and representative loads of tested engines driving generators. In preliminary diagnostic tests, the effects of loading on values of diagnostic parameters in various domains of signals analysis were checked and used to reduce the range the diagnostic research. Besides, the most useful symptoms were selected based on the correlation with the load. The diagnostic of pressure in the injection subsystem and in-cylinder pressure signals were subjected to time frequency analysis. In the principal studies, attempts were made to investigate the value of diagnostic symptoms while maintaining a constant load. For operating marine combustion engines, it is difficult to obtain repeatable test conditions because it is dependent on the principles of engine control and consumption of electricity by shipboard receivers. In operational tests on sea-going vessels, a wireless load measurement system and a system for processing and analyzing the parameters of working and residual processes were used. The wireless simultaneous load measurement system was effective in cases where load indicators and meters were away from the diagnosed objects. A wireless load and selected signals transmission system was used in tests on the ship. The aim of the article is to develop diagnostic models for bringing different test conditions to the common representative and reliable diagnostic decision. The article presents how to adjust diagnostic parameters of the working process, recorded at slightly different loads, to the value of common and equal load. This was done based on the best-fitted approximation model.

Wireless Smart Sensor Networks (WSSN) facilitates a new paradigm to structural health monitoring (SHM) for civil infrastructure. Conventionally, SHM systems employing wired sensors and central data acquisition have been used to characterize the state of a structure; however, wide-spread implementation has been limited due to difficulties in cabling, high equipment cost, and long setup time. WSSNs offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. Wireless smart sensors have shown their tremendous potential for SHM in recent full-scale bridge monitoring examples. However, structural damage identification in WSSNs, a primary objective of SHM, has yet to reach its full potential. This paper presents an implementation of the stochastic dynamic damage locating vector (SDDLV) method on the Imote2 sensor platform and experimental validation in a laboratory environment. The WSSN application is developed based on the Illinois SHM Project (ISHMP) Services Toolsuite (http://shm.cs.uiuc.edu), combining decentralized data aggregation, system identification, receptance-based damage detection, and global damage assessment. The laboratory experiment uses a three-dimensional truss structure with a network of Imote2 sensors for decentralized damage identification. Future efforts to deploy a long-term structural health monitoring system for a fullscale steel truss bridge are also described.

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.

The structural health monitoring has been gaining more importance in civil engineering areas such as earthquake and wind engineering. The use of health monitoring system can also provide tools for the validation of structural analytical model. However, only few structures such as historical buildings and some important long bridges have been instrumented with structural monitoring system due to high cost of installation, long and complicated installation of system wires. In this paper, the structural monitoring system based on cheap and wireless monitoring system is investigated. The use of advanced technology of micro-electro-mechanical system(MEMS) and wireless communication can reduce system cost and simplify the installation. Further the application of wireless MEMS system can provide enhanced system functionality and due to low noise densities. Identification results are compared to ones using data measured from traditional accelerometers and results indicate that the system identification using wireless MEMS system estimates system parameters accurately.

The usual wireless sensor network based on MCU (micro-control unit) is not suitable to test fast changing signals. We designed an intelligent wireless test and measurement system based on wireless sensor network, which can be applied to measure the fast dynamic signals. Changeable sampling rate is designed according to the specific application background in this system. CPLD (complex programmable logic device) is used as the main controller for the high and changeable sampling rate and MCU cooperated with a transceiver for the communication of node. A "first-memory-then-transmission-mechanism" (FMTTM) and a two stages mechanism are proposed, which based on the limited hardware resource. These mechanisms deal well with the relation of the system performance and limited resource. The experiments indicate that the system works well and its design is successful based on ad-hoc network. The complicated system with intelligence can measure a field signal from 1 Msps to 200 Ksps sampling rate reliably and accurately.

Mobile, heterogeneous, and smart sensor networks produce pervasive structural health monitoring (SHM) information. With various embedded sensors, smartphones have emerged to innovate SHM by empowering citizens to serve as sensors. By default, smartphones meet the fundamental smart sensor criteria, thanks to the built-in processor, memory, wireless communication units and mobile operating system. SHM using smartphones, however, faces technical challenges due to citizen-induced uncertainties, undesired sensor-structure integration, and lack of control over the sensing platform. Previously, the authors presented successful applications of smartphone accelerometers for structural vibration measurement and proposed a monitoring framework under citizen-induced spatiotemporal uncertainties. This study aims at extending the capabilities of smartphone-based SHM with a special focus on the lack of control over the sensor (i.e., the phone) positioning by citizens resulting in unknown sensor orientations. Using smartphone gyroscope, accelerometer, and magnetometer; instantaneous sensor orientation can be obtained with respect to gravitational and magnetic north directions. Using these sensor data, mobile operating system frameworks return processed features such as attitude and heading that can be used to correct misaligned sensor signals. For this purpose, a coordinate transformation procedure is proposed and illustrated on a two-story laboratory structural model and real-scale bridges with various sensor positioning examples. The proposed method corrects the sensor signals by tracking their orientations and improves measurement accuracy. Moreover, knowing structure’s coordinate system a priori, even the data from arbitrarily positioned sensors can automatically be transformed to the structural coordinates. In addition, this paper also touches some secondary mobile and heterogeneous data issues including imperfect sampling and geolocation services. The coordinate system transformation methods proposed in this study can be implemented in other non-smartphone-based SHM systems as long as similar instrumentation is available.

As newer and more reliable ways of construction were developed, civilization began to spread out further and retain functional infrastructure for longer periods of time.[...]

In-service condition assessment of large civil infrastructure systems has remained a particularly challenging area of research in the fields of nondestructive evaluation and structural health monitoring (SHM). Extensions of theoretically-based and laboratory verified vibration-based methods for assessing damage have been investigated experimentally on full-scale structures within several studies offering mixed conclusions. This paper introduces a recent experimental test program conducted on a full-scale bridge beam subjected to prescribed damage to the tension reinforcement. Details of the experimental testing program and vibration testing of the full-scale bridge beam both prior to and after damage to tension reinforcement are presented. System identification is applied to compare estimates of the natural frequencies, relative damping factors, and mode shapes obtained in the as-built state against those obtained after cutting over half of the tension reinforcement strands in the beam. A data-driven damage detection algorithm previously applied to detect damage in a full-scale bridge is also explored for application to the current dataset.

The computational and wireless communication capabilities of smart sensors densely distributed over structures can provide rich information for structural monitoring. While smart sensor technology has seen substantial advances during recent years, interdisciplinary efforts to address issues in sensors, networks, and application specific algorithms are needed to realize their potential. This paper first discusses each of these issues, and then reports on research that combines the results to develop a structural health monitoring (SHM) system suitable for implementation on a network of smart sensors. Experimental verification is provided using Intel's Imote2 smart sensors installed on a threedimensional truss structure. The Imote2 is employed herein because it has the high computational and wireless communication performance required for advanced SHM applications. This SHM system is then investigated from sensing, network, and SHM algorithm perspectives.

A displacement measurement provides useful information for structural health monitoring (SHM) as it is directly related to stiffness of the structure. Most existing methods of direct measurement such as the Laser Doppler Vibrometer (LDV) and the Liner Variable Differential Transformer (LVDT) are known to have accurate performance but have difficulties particularly in the use of large-scale civil structures as the methods rely on fixed reference points. Alternatively, indirect methods have been developed and widely used methods are Global Positioning System (GPS), vision-based displacement measurement system and displacement estimation from acceleration record. Among the indirect method, the use of accelerometer provides simple and economical in term of both hardware installation and operation. The major problem using acceleration based displacement estimation is low frequency drift caused by double integration. Recently, dynamic displacement estimation algorithm that addresses low-frequency drift problem has been developed. This study utilizes Wireless Smart Sensor (WSN) for estimating dynamic displacement from acceleration measurement in combination with the recently developed displacement estimation algorithm. Integrated into WSN that are low-cost, wireless, compatible with accelerometers, and capable of onboard computation, the displacement can be measured without limit of location on large-scale civil structures. Thus, this approach has the significant potential to impact many applications that require displacement measurements. With the displacement estimation algorithm embedded, the WSN performs in-network data processing to estimate displacements at each distributed sensor location wirelessly using only measured acceleration data. To experimentally validate the performance of displacement estimation using WSN for the use in structures with multiple-degree of freedom, the random vibration test is conducted on the three-story shear building model. The estimated displacement is compared with the reference displacements measured from the laser displacement sensor and the result shows good agreement.