Advanced calibration method for 3-axis MEMS accelerometers

Gheorghe, Marius V.

doi:10.1109/smicnd.2016.7783046

Cited by 15 publications

(10 citation statements)

References 8 publications

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“…The general relation between scaling factor and temperature is described in (3) and offset and temperature is described in (4).…”

Section: Calibration Of High Precision Sensorsmentioning

confidence: 99%

“…Performance of many high-precision sensors is dependent upon environmental factors such as temperature, pressure, and humidity. One way to eliminate the error introduced by the dependency is to model or predict the error with the environmental factors and then compensate it by further processing the output of the sensors [3][4][5]. In most of the cases, the suitable model is a polynomial function in some environmental factors.…”

Section: Introductionmentioning

confidence: 99%

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A Customized Floating-point Processor Design for FPGA and ASIC based Thermal Compensation in High-precision Sensing

Sajjad¹,

Yusoff²,

Ahmed³

2021

AETiC

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There are many types of sensors which require large dynamic range as well as high accuracy at the same time. Barometric altimeter is an example of such sensors. The signal processing techniques in the sensors are normally implemented using Field Programmable Gate Arrays (FPGAs) or Application-Specific Integrated Circuits (ASICs). The sensing variable in such type of the sensors is unwantedly environment dependent. So, for ensuring accuracy of the sensors this environmental dependency is minimized using the modeling and compensation techniques. In this work we have proposed a digital architecture for a programmable high precision computational unit which can be implemented in the FPGA or ASIC running the sensing algorithm of the sensors. This architecture can be used to implement polynomial compensation and it also supports reading and writing of the corresponding calibration coefficients even after the development of the sensors. Moreover, the architecture is platform independent. The architecture have been simulated for different FPGAs and ASIC and it has fulfilled the speed, accuracy and programmability requirements of the type of the sensors. The architecture has also been implemented and verified in a prototype of the barometric pressure sensor on Spartan-6 FPGA.

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“…The general relation between scaling factor and temperature is described in (3) and offset and temperature is described in (4).…”

Section: Calibration Of High Precision Sensorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Customized Floating-point Processor Design for FPGA and ASIC based Thermal Compensation in High-precision Sensing

Sajjad¹,

Yusoff²,

Ahmed³

2021

AETiC

View full text Add to dashboard Cite

show abstract

“…These methods can be divided into the 3-order polynomial fitting method [ 31 ], the linear interpolation method [ 32 ], the AG-based calibration method [ 33 ], the RBF calibration method [ 34 ], and other optimization methods. In this research, we apply the soak method for triaxial accelerometers based on the Levenberg-Marquardt (LM) algorithm and polynomial methods, which can provide more accurate sensor error data at various temperature points.…”

Section: Introductionmentioning

confidence: 99%

Thermal Calibration of Triaxial Accelerometer for Tilt Measurement

Yuan

Tang

Zhang

et al. 2023

Sensors

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The application of MEMS accelerometers used to measure inclination is constrained by their temperature dependence, and each accelerometer needs to be calibrated individually to increase stability and accuracy. This paper presents a calibration and thermal compensation method for triaxial accelerometers that aims to minimize cost and processing time while maintaining high accuracy. First, the number of positions to perform the calibration procedure is optimized based on the Levenberg-Marquardt algorithm, and then, based on this optimized calibration number, thermal compensation is performed based on the least squares method, which is necessary for environments with large temperature variations, since calibration parameters change at different temperatures. The calibration procedures and algorithms were experimentally validated on marketed accelerometers. Based on the optimized calibration method, the calibrated results achieved nearly 100 times improvement. Thermal drift calibration experiments on the triaxial accelerometer show that the thermal compensation scheme in this paper can effectively reduce drift in the temperature range of −40 °C to 60 °C. The temperature drifts of x- and y-axes are reduced from −13.2 and 11.8 mg to −0.9 and −1.1 mg, respectively. The z-axis temperature drift is reduced from −17.9 to 1.8 mg. We have conducted various experiments on the proposed calibration method and demonstrated its capacity to calibrate the sensor frame error model (SFEM) parameters. This research proposes a new low-cost and efficient strategy for increasing the practical applicability of triaxial accelerometers.

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“…In the second step, the dependency of these coefficients is obtained using various methods. For example in Ma et al (2014b) and Ruzza et al (2018) bias, in Encarnacao et al (2017) and Altinöz and Ünsal (2018) bias and scale factor and in Wang et al (2016), Günhan and Ünsal (2014) and Gheorghe, 2016) bias, scale factor and non-orthogonality have been considered as a temperature-dependent polynomial and linear regression methods have been used to obtain coefficients of these polynomials. In addition to linear regression, other methods have also been used to model the dependency of accelerometer coefficients on temperature.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous compensation of systematic errors of a low-cost MEMS triaxial accelerometer and its temperature dependency without accurate laboratory equipment

Khankalantary

Ranjbaran

Mohammadkhani

2021

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Purpose Laboratory calibration methods are time-consuming and require accurate devices to find the error coefficients of the low-cost microelectromechanical system (MEMS) accelerometer. Besides, low-cost MEMS sensors highly depend on temperature because of their silicon property and the effect of temperature on error coefficients should also be considered for compensation. This paper aims to present a field calibration method in which the accelerometer is placed in different positions without any accurate equipment in a few minutes and its temperature is changed by a simple device like a hairdryer. Design/methodology/approach In this paper, a non-linear cost function is defined based on this rule that the magnitude of the acceleration measured by the accelerometer in static mode is equal to the gravity plus error factors. Also, the dependency of error coefficients of the accelerometer is presented as a second-order polynomial in this cost function. By minimizing the cost function, the accelerometer error coefficients include bias, scale factor and non-orthogonality and their temperature dependency are obtained simultaneously. Findings Simulation results in MATLAB and empirical results of a MPU6050 accelerometer verify the good performance of the proposed calibration method. Originality/value Finding a fast and simple field calibration method to calibrate a low-cost MEMS accelerometer and compensate for the temperature dependency without using accurate laboratory equipment can help a wide range of industries that use advanced and expensive sensors or use expensive laboratory equipment to calibrate their sensors, to decrease their costs.

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Advanced calibration method for 3-axis MEMS accelerometers

Cited by 15 publications

References 8 publications

A Customized Floating-point Processor Design for FPGA and ASIC based Thermal Compensation in High-precision Sensing

A Customized Floating-point Processor Design for FPGA and ASIC based Thermal Compensation in High-precision Sensing

Thermal Calibration of Triaxial Accelerometer for Tilt Measurement

Simultaneous compensation of systematic errors of a low-cost MEMS triaxial accelerometer and its temperature dependency without accurate laboratory equipment

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