MEMS Inertial Sensor for Strata Stability Monitoring in Underground Mining: An Experimental Study

To investigate the fracture and deformation characteristics of the strata in underground mining as well as the effectiveness and sensitivity of the MEMS inertial sensor for strata stability monitoring, a low cost, small size, and easy implementation inertial MEMS sensor module was redeveloped. Sensor modules were installed on roof strata in an underground mining equivalent material simulation experiment. Then, monitoring signal of two modules near the middle and end section of caving strata was processed. The processed signal presents stepped change, and each step consists a vibration stage and a stable stage. Further analysis of each stage, a strategy to estimate the deformation and stability of strata, can be reached: the duration of each vibration stage and complete stage with rising trend indicates that the deformation of strata is growing to the ultimate state. In this study, this method could recognize the destructive deformation of strata at least 1 hour before the strata caving.

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A Universal Approach for Processing any MEMS Inertial Sensor Configuration for Land-Vehicle Navigation

Journal of Navigation ◽

10.1017/s0373463307004213 ◽

2007 ◽

Vol 60 (2) ◽

pp. 233-245 ◽

Cited By ~ 24

Author(s):

Xiaoji Niu ◽

Sameh Nasser ◽

Chris Goodall ◽

Naser El-Sheimy

Keyword(s):

Inertial Sensor ◽

Low Cost ◽

Navigation Systems ◽

Micro Electro Mechanical Systems ◽

Land Vehicle ◽

Mems Sensor ◽

Navigation Algorithm ◽

Main Challenge ◽

Universal Approach ◽

Sensor Configuration

Recent navigation systems integrating GPS with Micro-Electro-Mechanical Systems (MEMS) Inertial Measuring Units (IMUs) have shown promising results for several applications based on low-cost devices such as vehicular and personal navigation. However, as a trend in the navigation market, some applications require further reductions in size and cost. To meet such requirements, a MEMS full IMU configuration (three gyros and three accelerometers) may be simplified. In this context, different partial IMU configurations such as one gyro plus three accelerometers or one gyro plus two accelerometers could be investigated. The main challenge in this case is to develop a specific navigation algorithm for each configuration since this is a time-consuming and costly task. In this paper, a universal approach for processing any MEMS sensor configuration for land vehicular navigation is introduced. The proposed method is based on the assumption that the omitted sensors provide relatively less navigation information and hence, their output can be replaced by pseudo constant signals plus noise. Using standard IMU/GPS navigation algorithms, signals from existing sensors and pseudo signals for the omitted sensors are processed as a full IMU. The proposed approach is tested using land-vehicle MEMS/GPS data and implemented with different sensor configurations. Compared to the full IMU case, the results indicate the differences are within the expected levels and that the accuracy obtained meets the requirements of several land-vehicle applications.

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A NEW CALIBRATION METHOD FOR LOW COST MEMS INERTIAL SENSOR MODULE

Journal of Marine Science and Technology ◽

10.51400/2709-6998.1939 ◽

2010 ◽

Vol 18 (6) ◽

Author(s):

Sheng-Chih Shen ◽

Chia-Jung Chen ◽

Hsin-Jung Huang

Keyword(s):

Inertial Sensor ◽

Low Cost ◽

Calibration Method ◽

Sensor Module

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Comparison of a Low-Cost Miniature Inertial Sensor Module and a Fiber-Optic Gyroscope for Clinical Balance and Gait Assessments

Journal of Healthcare Engineering ◽

10.1155/2019/9816961 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Daniel Roetenberg ◽

Claudia Höller ◽

Kevin Mattmüller ◽

Markus Degen ◽

John H. Allum

Keyword(s):

Angular Velocity ◽

Fiber Optic ◽

Balance Control ◽

Inertial Sensor ◽

Low Cost ◽

Reference Database ◽

Motion Sensors ◽

Fiber Optic Gyroscope ◽

Perfect Agreement ◽

Sensor Module

Objective. To investigate whether a microelectromechanical system (MEMS) inertial sensor module is as accurate as fiber-optic gyroscopes when classifying subjects as normal for clinical stance and gait balance tasks. Methods. Data of ten healthy subjects were recorded simultaneously with a fiber-optic gyroscope (FOG) system of SwayStar™ and a MEMS sensor system incorporated in the Valedo® system. Data from a sequence of clinical balance tasks with different angle and angular velocity ranges were assessed. Paired t-tests were performed to determine significant differences between measurement systems. Cohen’s kappa test was used to determine the classification of normal balance control between the two sensor systems when comparing the results to a reference database recorded with the FOG system. Potential cross-talk errors in roll and pitch angles when neglecting yaw axis rotations were evaluated by comparing 2D FOG and 3D MEMS recordings. Results. Statistically significant (α=0.05) differences were found in some balance tasks, for example, “walking eight tandem steps” and various angular measures (p<0.03). However, these differences were within a few percent (<2.7%) of the reference values. Tasks with high dynamic velocity ranges showed significant differences (p=0.002) between 2D FOG and 3D MEMS roll angles but no difference between 2D FOG and 2D MEMS roll angles. An almost perfect agreement could be obtained for both 2D FOG and 2D MEMS (κ=0.97) and 2D FOG and 3D MEMS measures (κ=0.87) when comparing measurements of all subjects and tasks. Conclusion. MEMS motion sensors can be used for assessing balance during clinical stance and gait tasks. MEMS provides measurements comparable to values obtained with a highly accurate FOG. When assessing pitch and roll trunk sway measures without accounting for the effect of yaw, it is recommended to use angle and angular velocity measures for stance, and only angular velocity measures for gait because roll and pitch velocity measurements are not influenced by yaw rotations, and angle errors are low for stance.

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Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance

Sensors ◽

10.3390/s21072480 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2480

Author(s):

Isidoro Ruiz-García ◽

Ismael Navarro-Marchal ◽

Javier Ocaña-Wilhelmi ◽

Alberto J. Palma ◽

Pablo J. Gómez-López ◽

...

Keyword(s):

Data Fusion ◽

Reference System ◽

Inertial Sensor ◽

Low Cost ◽

Sampling Rate ◽

Sensor Data ◽

Fusion Algorithm ◽

Improve Technique ◽

Worst Case ◽

Sensor Data Fusion

In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from −1.13° (roll) to 0.44° (yaw) and 95% limits of agreements from 2.87° (yaw) to 6.27° (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.

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Design, manufacture and testing of a prototype obstacle-detection device at blind corners: an automated highway system technology

Transportation Safety and Environment ◽

10.1093/tse/tdaa029 ◽

2020 ◽

Author(s):

Charles Atombo ◽

Emmanuel Gbey ◽

Apevienyeku Kwami Holali

Keyword(s):

Traffic Accidents ◽

Low Cost ◽

Effective Area ◽

Obstacle Detection ◽

The Road ◽

Vibration Sensors ◽

Road Signs ◽

Sensor Module ◽

Vehicle Path ◽

Automated Highway

Abstract Traffic accidents on highways are attributed mostly to the "invisibility" of oncoming traffic and road signs. "Speeding" also causes drivers to reduce the effective radius of the vehicle path in the curve, thus trespassing into the lane of the oncoming traffic. The main aim of this paper was to develop a multisensory obstacle-detection device that is affordable, easy to implement and easy to maintain to reduce the risk of road accidents at blind corners. An ultrasonic sensor module with a maximum measuring angle of 15° was used to ensure that a significant portion of the lane was detected at the blind corner. The sensor covered a minimum effective area of 0.5 m2 of the road for obstacle detection. Yellow light was employed to signify caution while negotiating the blind corner. Two photoresistors (PRs) were used as sensors because of the limited number of pins on the microcontroller (Arduino Uno). However, the device developed for this project achieved obstacle detection at blind corners at relatively low cost and can be accessed by all road users. In real-world applications, the use of piezoelectric accelerometers (vibration sensors) instead of PR sensors would be more desirable in order to detect not only cars but also two-wheelers.

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A Low-Cost Inertial Sensor Based on Shaped Magnetic Fluids

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2011.2174902 ◽

2012 ◽

Vol 61 (5) ◽

pp. 1231-1236 ◽

Cited By ~ 9

Author(s):

Bruno Ando ◽

Salvatore Baglio ◽

Angela Beninato

Keyword(s):

Inertial Sensor ◽

Low Cost ◽

Magnetic Fluids

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Visual Measurement System for Wheel–Rail Lateral Position Evaluation

Sensors ◽

10.3390/s21041297 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1297

Author(s):

Viktor Skrickij ◽

Eldar Šabanovič ◽

Dachuan Shi ◽

Stefano Ricci ◽

Luca Rizzetto ◽

...

Keyword(s):

Measurement System ◽

Inertial Sensor ◽

Low Cost ◽

Image Point ◽

Low Velocity ◽

Point Selection ◽

Lateral Direction ◽

Initial Field ◽

Visual Measurement ◽

Track Geometry

Railway infrastructure must meet safety requirements concerning its construction and operation. Track geometry monitoring is one of the most important activities in maintaining the steady technical conditions of rail infrastructure. Commonly, it is performed using complex measurement equipment installed on track-recording coaches. Existing low-cost inertial sensor-based measurement systems provide reliable measurements of track geometry in vertical directions. However, solutions are needed for track geometry parameter measurement in the lateral direction. In this research, the authors developed a visual measurement system for track gauge evaluation. It involves the detection of measurement points and the visual measurement of the distance between them. The accuracy of the visual measurement system was evaluated in the laboratory and showed promising results. The initial field test was performed in the Vilnius railway station yard, driving at low velocity on the straight track section. The results show that the image point selection method developed for selecting the wheel and rail points to measure distance is stable enough for TG measurement. Recommendations for the further improvement of the developed system are presented.

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Thermal Modulation of a High-Bandwidth Gas Sensor Array in Real-Time for Application on a Mobile Robot

Proceedings ◽

10.3390/proceedings2130858 ◽

2018 ◽

Vol 2 (13) ◽

pp. 858 ◽

Cited By ~ 1

Author(s):

Timothy A. Vincent ◽

Yuxin Xing ◽

Marina Cole ◽

Julian W. Gardner

Keyword(s):

Signal Processing ◽

Mobile Robot ◽

Real Time ◽

Low Cost ◽

Processing Technique ◽

Signal Processing Technique ◽

Baseline Drift ◽

Gas Sensor Array ◽

Sensor Module ◽

High Bandwidth

A new signal processing technique has been developed for resistive metal oxide (MOX) gas sensors to enable high-bandwidth measurements and enhanced selectivity at PPM levels (<50 PPM VOCs). An embedded micro-heater is thermally pulsed from 225 to 350 °C, which enables the chemical reactions in the sensor film (e.g., SnO2, WO3, NiO) to be extracted using a fast Fourier transform. Signal processing is performed in real-time using a low-cost microcontroller integrated into a sensor module. The approach enables the remove of baseline drift and is resilient to environmental temperature changes. Bench-top experimental results are presented for 50 to 200 ppm of ethanol and CO, which demonstrate our sensor system can be used within a mobile robot.

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