Designing a 2-DOF passive mechanism for dynamical calibration of MEMS-based motion sensors

Asadi, A.; Homaeinezhad, Mohammad Reza; Arefnezhad, Sadegh; Safaeifar, A.; Zoghi, Milad

doi:10.1109/icrom.2014.6990910

Cited by 3 publications

(4 citation statements)

References 11 publications

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“…Although the tests carried out with synthetic data give a valid indication of the potential accuracy of this method, the suitability of the proposed model for the calibration of a real accelerometer can be only verified by performing real experiments on that sensor. The most popular calibration methods in literature assess their accuracy by comparing the fitness of the sensor output to a known model, like the closeness of the absolute value to g in static conditions, as in [4], [5], [10]- [12], or the fitness to other known model constraints, as in [2], [3], [13], before and after the calibration. This approach only proves that the calibrated acceleration signal is more accurate than the uncalibrated output, but no information is provided about the actual precision of the estimated calibration parameters.…”

Section: B Performance Evaluation On a Real Sensormentioning

confidence: 99%

“…Many different approaches have been proposed in literature for the calibration of triaxial accelerometer [2], [4]- [13], featuring a large variety of calibration setups and sensor models. In general, more sophisticated calibration approaches are able to estimate more complex accelerometer models.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, these procedures need to carry out many data acquisitions, one for each time the sensor is positioned and held fixed on a new orientation. Conversely, in dynamic calibrations, the acceleration samples are acquired continuously, while the sensor is undergoing a controlled motion [2], [6], [9], [13], [14]. Consequently, dynamic calibrations typically need a single data sequence, which makes the acquisition process simpler, compared to static procedures.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Calibration of Triaxial Accelerometers With Simple Setup

Pedersini

2022

IEEE Sensors J.

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In the dynamic techniques for calibration of triaxial accelerometers, the sensor is held in motion during data acquisition; the acquired time-varying acceleration is in general more informative than the constant acceleration acquired in static calibration approaches. Dynamic methods, however, typically require complex and expensive calibration setups based on high-precision moving benches, to guarantee accurate a-priori knowledge of the acceleration applied to the sensors under test. This article presents a dynamic calibration procedure working with a very simple and inexpensive setup: a tilted, freelyrotating bench, made of a simple wheel mounted on a static support. The accelerometer is fastened to the bench, which is then manually set into rotation; the acceleration signal is then acquired while the bench is freely rotating. No a-priori knowledge is required about the bench rotation: the proposed calibration procedure estimates both the calibration parameters and the bench motion. To keep the setup as simple as possible, an effort has been made to minimize also the necessity of prior knowledge of the bench geometry: only the distance of the sensor from the rotation axis needs to be known, which can be easily obtained through direct measurement on the bench. The proposed calibration has been tested both on synthetic data, to prove the absence of estimation biases and to evaluate the potential accuracy of the estimated parameters, and on real data from a MEMS triaxial accelerometer, to assess the practical usability and measure the actual precision of the procedure.

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Section: B Performance Evaluation On a Real Sensormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic Calibration of Triaxial Accelerometers With Simple Setup

Pedersini

2022

IEEE Sensors J.

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“…In [ 27 ], a two-degree-of-freedom (DOF) mechatronic structure is proposed to generate controlled linear and angular accelerations in the sensor. The structure includes shaft encoders and a microcontroller unit to obtain its position when in motion.…”

Section: Related Workmentioning

confidence: 99%

A Low-Cost Calibration Method for Low-Cost MEMS Accelerometers Based on 3D Printing

García

Lara

Aguilar

2020

Sensors

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A ubiquitous sensor in embedded systems is the accelerometer, as it enables a range of applications. However, accelerometers experience nonlinearities in their outputs caused by error terms and axes misalignment. These errors are a major concern because, in applications such as navigations systems, they accumulate over time, degrading the position accuracy. Through a calibration procedure, the errors can be modeled and compensated. Many methods have been proposed; however, they require sophisticated equipment available only in laboratories, which makes them complex and expensive. In this article, a simple, practical, and low-cost calibration method is proposed. It uses a 3D printed polyhedron, benefiting from the popularisation and low-cost of 3D printing in the present day. Additionally, each polyhedron could hold as much as 14 sensors, which can be calibrated simultaneously. The method was performed with a low-cost sensor and it significantly reduced the root-mean-square error (RMSE) of the sensor output. The RMSE was compared with the reported in similar proposals, and our method resulted in higher performance. The proposal enables accelerometer calibration at low-cost, and anywhere and anytime, not only by experts in laboratories. Compensating the sensor’s inherent errors thus increases the accuracy of its output.

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Calibration of a micro-electro mechanical system-based accelerometer for vehicle navigation

Ghaffari

Khodayari

Nosoudi³

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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Micro-electro mechanical system-based inertial sensors have broad applications in moving objects including in vehicles for navigation purposes. The low-cost micro-electro mechanical system sensors are normally subject to high dynamic errors such as linear or nonlinear bias, misalignment errors and random noises. In the class of low cost sensors, keeping the accuracy at a reasonable range has always been challenging for engineers. In this paper, a novel method for calibrating low-cost micro-electro mechanical system accelerometers is presented based on soft computing approaches. The method consists of two steps. In the first step, a preliminary model for error sources is presented based on fuzzy subtractive clustering algorithm. This model is then improved using adaptive neuro-fuzzy systems. A Kalman filter is also used to calculate the vehicle velocity and its position based on calibrated measured acceleration. The performance of the presented approach has been validated in the simulated and real experimental driving scenarios. The results show that this method can improve the accuracy of the accelerometer output, measured velocity and position of the vehicle by 79.11%, 97.63% and 99.28%, in the experimental test, respectively. The presented procedure can be used in collision avoidance and emergency brake assist systems.

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Designing a 2-DOF passive mechanism for dynamical calibration of MEMS-based motion sensors

Cited by 3 publications

References 11 publications

Dynamic Calibration of Triaxial Accelerometers With Simple Setup

Dynamic Calibration of Triaxial Accelerometers With Simple Setup

A Low-Cost Calibration Method for Low-Cost MEMS Accelerometers Based on 3D Printing

Calibration of a micro-electro mechanical system-based accelerometer for vehicle navigation

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