Preventive Work and Health Monitoring for Technology by Cracks of Concrete Surface Using Coating Type Resin Sensor
Nobuhiro Shimoi,
Yu Yamauch,
Kazuhisa Nakasho
Issue:
Volume 11, Issue 1, June 2023
Pages:
1-10
Received:
7 April 2023
Accepted:
8 May 2023
Published:
18 May 2023
Abstract: Infrastructure safety inspections rely on visual inspections and hammering inspections by inspectors. However, an important difficulty is that inspection results vary because of differences in the technical expertise of inspectors. An inspection method and preventive work using a coating type resin sensor and an infrared camera are proposed to overcome that difficulty. A nondestructive evaluation technique using thermography is used increasingly as a tool to maintain concrete structures. Most inspections only evaluate the defect locations and shapes on planes. No method has been developed for evaluating defect depths. After applying infrared reactive resin, thermographic images of a target area are taken sequentially. Then, temperature curves obtained at each pixel during cooling defect states in different parts of the temperature distribution are analyzed using Fourier transform. The temperature change is related to the defect size. Approximately 10% of aluminum powder mixed into the applied gel resin, because of its specific gravity, has the property of concentrating in areas damaged by compression failure or floating. This report describes technologies related to defect identification and size measurements in infrared reactive resin, and describes effects of preventive work to avoid the scattering and collapse of defects caused by structural degradation.
Abstract: Infrastructure safety inspections rely on visual inspections and hammering inspections by inspectors. However, an important difficulty is that inspection results vary because of differences in the technical expertise of inspectors. An inspection method and preventive work using a coating type resin sensor and an infrared camera are proposed to over...
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Virtual Reality as Assessment Tool of the Risk of Falls in the Elderly
Fabien Clanché,
Gabin Personeni,
Alexandre Renaux,
Frédéric Muhla,
Thierry Bastogne,
Gérome Gauchard
Issue:
Volume 11, Issue 1, June 2023
Pages:
11-17
Received:
30 May 2022
Accepted:
1 March 2023
Published:
27 June 2023
Abstract: We present an assessment tool, based on virtual reality technology, for predicting motor control, attentional or cognitive factors of risk of falls in the elderly. Falls are the leading cause of accidents among the elderly. Each year, it affects 1 in 4 people over the age of 65. In order to better understand and predict this risk of falling, we developed an immersion solution that can collect and identify various indicators of the risk of falling. This easy-to-use solution automates the experimental protocol and the data collection of indicators, and immerses the patient in realistic everyday situations. Our virtual reality device, uses a total of 6 sensors worn by the patient to capture a kinematic of the complete body and generate a virtual avatar in real time to the patient. These kinematic data, replayable for the health practitioner, train a digital process. The scientific experiment, patient-centered, is based on 6 tests of motor or attentional disturbances, requiring global functional abilities. The results obtained showed that for high-risk fall patients, the longer completion times and the number of steps for the different tests compared to low-risk fall patients. Specifically, the introduction of manual and cognitive tasks affects high-risk fall patients more significantly.
Abstract: We present an assessment tool, based on virtual reality technology, for predicting motor control, attentional or cognitive factors of risk of falls in the elderly. Falls are the leading cause of accidents among the elderly. Each year, it affects 1 in 4 people over the age of 65. In order to better understand and predict this risk of falling, we dev...
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Calibration of 3-Axis Low-Cost Magnetometer Using the Least Square Ellipsoid Fitting Algorithm
Ali Shakerian,
Saoussen Bilel,
René Jr. Landry
Issue:
Volume 11, Issue 1, June 2023
Pages:
18-24
Received:
6 July 2023
Accepted:
20 July 2023
Published:
9 August 2023
Abstract: This paper presents a calibration method for low-cost 3-axis magnetometers using the least square ellipsoid fitting algorithm. The aim of the calibration process is to reduce noise and mitigate the effects of magnetic interferences and instrumentation errors, thereby enhancing the accuracy and reliability of magnetometer measurements. By collecting data while moving the sensor in arbitrary directions, the calibration parameters are estimated, including magnetic disturbances (soft iron and hard iron effects) and instrumental errors (scale factor, nonorthogonality, and bias). The measured data are modeled as a combination of these errors, and the calibration parameters are obtained by solving a quadratic form equation using the least square ellipsoid fitting algorithm. The results demonstrate that the proposed calibration method using the least square ellipsoid fitting algorithm provides a valuable contribution to the field of magnetometer calibration, with the calibrated data exhibiting a better fit to the surface of an ellipsoid compared to the original magnetometer data, indicating its effectiveness, achieving 90% accuracy in magnetometer calibration of module MPU-9250. The proposed calibration method offers several advantages, including its simplicity and cost-effectiveness. Furthermore, the real-time capability of the algorithm makes it suitable for applications that require continuous calibration, ensuring accurate and reliable measurements over time. The integration of the calibration method into the intelligent IMU Sensor (IIS) further enhances its practicality and applicability in real-world scenarios.
Abstract: This paper presents a calibration method for low-cost 3-axis magnetometers using the least square ellipsoid fitting algorithm. The aim of the calibration process is to reduce noise and mitigate the effects of magnetic interferences and instrumentation errors, thereby enhancing the accuracy and reliability of magnetometer measurements. By collecting...
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