A Field Calibration Method for Low-Cost MEMS Accelerometer Based on the Generalized Nonlinear Least Square Method

2020 ◽  
Vol 2 (2-3) ◽  
pp. 135-142
Author(s):  
Mahmood ul Hassan ◽  
Qilian Bao
Keyword(s):  
Low Cost ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Mems Accelerometer ◽  
Field Calibration

scholarly journals Self-Calibration of an Industrial Robot Using a Novel Affordable 3D Measuring Device

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3380 ◽  
Author(s):  
Martin Gaudreault ◽  
Ahmed Joubair ◽  
Ilian Bonev
Keyword(s):  
Industrial Robot ◽  
Low Cost ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Geometrical Parameters ◽  
Robot Arm ◽  
Measuring Device ◽  
Self Calibration ◽  
Position Errors

This work shows the feasibility of calibrating an industrial robot arm through an automated procedure using a new, low-cost, wireless measuring device mounted on the robot’s flange. The device consists of three digital indicators that are fixed orthogonally to each other on an aluminum support. Each indicator has a measuring accuracy of 3 µm. The measuring instrument uses a kinematic coupling platform which allows for the definition of an accurate and repeatable tool center point (TCP). The idea behind the calibration method is for the robot to bring automatically this TCP to three precisely-known positions (the centers of three precision balls fixed with respect to the robot’s base) and with different orientations of the robot’s end-effector. The self-calibration method was tested on a small six-axis industrial robot, the ABB IRB 120 (Vasteras, Sweden). The robot was modeled by including all its geometrical parameters and the compliance of its joints. The parameters of the model were identified using linear regression with the least-square method. Finally, the performance of the calibration was validated with a laser tracker. This validation showed that the mean and the maximum absolute position errors were reduced from 2.628 mm and 6.282 mm to 0.208 mm and 0.482 mm, respectively.

A Rapid Field Calibrating Method for MIMU

2011 ◽  
Vol 80-81 ◽  
pp. 1140-1144
Author(s):  
Yu Bao Fan ◽  
Jie Li ◽  
Bo Wang ◽  
Xiao Chun Tian ◽  
Jun Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Operation Time ◽  
Calibration Method ◽  
Least Square ◽  
Measurement Unit ◽  
Calibration Model ◽  
Time Saving ◽  
Inertial Measurement ◽  
Field Calibration ◽  
Calibration Program

When the Micro Inertial Measurement Unit is been placed randomly in the case of stationary, the sum vectors that measured by the inertial devices configured orthogonally along three axis, are constant vectors. In view of the above objective facts, a field calibration method of micro inertial measurement unit was proposed. On the base of the establishment and optimization of calibration model, all parameters to be calibrated can be obtained through the least square by the ellipsoid fitting, with the result of high-precision field calibration for micro inertial measurement unit. Finally, a filed calibration program for micro inertial measurement unit is scheduled reasonably. The experiment results show that the method has such characteristics such as easily-operation, time-saving, higher calibration accuracy, and not depending on the baseline direction and datum offered by precision instruments. Especially, it fits for inertial measurement systems which work short time and ask for high accuracy. In addition, it can also significantly increase the measurement accuracy of micro inertial measurement system in practical application.

Research on Zero Bias Characteristic of MEMS Accelerometer in FBW

2014 ◽  
Vol 609-610 ◽  
pp. 1046-1052
Author(s):  
Lun Chao Zhong ◽  
Jian Zhong Wang ◽  
Jia Dong Shi
Keyword(s):  
Random Error ◽  
Temperature Scale ◽  
Least Square Method ◽  
Temperature Characteristic ◽  
Least Square ◽  
Measuring Error ◽  
Zero Bias ◽  
Mems Accelerometer ◽  
Temperature Bias ◽  
Bias Stability

Zero bias is an important performance index of MEMS accelerometerscope. Based on the large amount of given accelerometer experiments, we study zero bias of random error properties, temperature characteristic, large overload environment variation, and then calculate MEMS accelerometer bias, bias stability, zero bias repeatability. Through least-square method,we fit temperature scale factor and temperature bias of MEMS accelerometer. The experimental results show that the compensation method has the advantages of simple operation, effectively compensation for measuring error of MEMS accelerometer which is induced by temperature, and has strong engineering using value.

scholarly journals How To Build Customer Loyalty: Through Customer Experience, Perceived Price, And Customer Satisfaction

2021 ◽  
Vol 12 (4) ◽  
pp. 1546-1554
Author(s):  
Edhie Budi Setiawan, Et. al.
Keyword(s):  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Structural Equation ◽  
Low Cost ◽  
Least Square Method ◽  
Customer Experience ◽  
Partial Least Square ◽  
Least Square ◽  
Perceived Price ◽  
The Impact

The competition to get the highest Market Share among Low-Cost Carrier airlines in Indonesia is getting fierce. Airlines are competing to offer prices that are appropriate for passengers to perceive them in this era of tariff wars. The degree of satisfaction that is felt is needed to get loyal customers. The purpose of this research is to analyze the impact of customer experience and perceived price on customer loyalty through customer satisfaction. The method of analysis in this study uses the SEM-PLS (Structural Equation Model - Partial Least Square) method with 250 respondents taken by purposive sampling. The result of this research is there is effect positive and significant between customer experience on customer satisfaction and customer loyalty, also there is effect of perceived price on customer satisfaction and customer loyalty. Airlines must pay attention to the services provided to create a memorable experience for passengers and adjust prices to be accepted by passengers.

scholarly journals The tides in the south-western Kara sea. Tides calibration method effects

2017 ◽  
pp. 98-115
Author(s):  
G. N. Voinov ◽  
A. K. Naumov
Keyword(s):  
Sea Level ◽  
Least Square Method ◽  
Calibration Method ◽  
Kara Sea ◽  
Least Square ◽  
The South ◽  
Quality Estimation ◽  
Annual Series ◽  
Method Effects ◽  
Statistical Estimations

The estimates of the tides harmonic constants are given over the period from 1962 to 1993. They were received using a least square method according to AARI. Quality estimation of the sea level observations was performed. The annual series with bad observations were transformed by means of tides calibration. The Estimation of the tides fi ne structure – harmonics of the second and third degree of the potential according to analysis over the period from 1962–1985 was received. The statistical estimations of the sea level in the separate typical years were calculated using initial and corrected series.

A machine learning field calibration method for improving the performance of low-cost particle sensors

2020 ◽  
pp. 107457
Author(s):  
Satya S. Patra ◽  
Rishabh Ramsisaria ◽  
Ruihang Du ◽  
Tianren Wu ◽  
Brandon E. Boor
Keyword(s):  
Machine Learning ◽  
Low Cost ◽  
Calibration Method ◽  
Field Calibration

Camera Calibration Based on Snell’s Law

2005 ◽  
Vol 128 (3) ◽  
pp. 548-557 ◽  
Author(s):  
Psang Dain Lin ◽  
Chi-Kuen Sung
Keyword(s):  
Camera Calibration ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Camera System ◽  
Optical Elements ◽  
Snell’S Law ◽  
Snell's Law ◽  
Geometric Relationship ◽  
Pinhole Model

In this paper we present a camera calibration method using Snell’s Law. Traditional camera calibration is based on the pinhole model, which is an approximation algorithm using untrue geometrical assumptions and giving a single lumped result for the various optical elements in the camera system. Using full modeling of lens geometry, the proposed method establishes the geometric relationship between images and objects via Snell’s Law. A matrix equation that relates the intrinsic/extrinsic parameters of image the plane and six pose parameters of each element is determined from sensitivity analysis. These parameters can be identified using the least square method by observing points with known coordinates. An illustrative example using a two-camera stereo coordinate measurement system demonstrates that system performance via the proposed method is better than the pinhole model.

Study on Two-Step Method for Robot Dynamics Parameters Calibration

2012 ◽  
Vol 605-607 ◽  
pp. 1557-1562 ◽  
Author(s):  
Qing Xuan Jia ◽  
Tong Li ◽  
Gang Chen
Keyword(s):  
Inverse Method ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Second Step ◽  
Robot Dynamics ◽  
Joint Movement ◽  
Step Method ◽  
Multidimensional Matrix ◽  
Pseudo Inverse

In order to obtain accurate dynamics parameters, a two-step method for robot dynamics parameters calibration is presented. In the first step a multidimensional matrix is constituted through transforming the configurations of robot manipulators and the product of quality and centroid coordinate about links is solved by using the least square method. In the second step decoupling dynamic equation of robot is deduced based on Newton-Euler algorithm, and through planning specific joint movement, the inertia tensor and centroid coordinate of robot links are calibrated making use of the pseudo inverse method. By the above two steps, the entire calibration of robot dynamic parameters is achieved. The correctness and feasibility of the presented calibration method is manifested by simulations and experiments.

Signal Conditioning of Low-Cost Gyroscope Using Kalman Filter and Nonlinear Least Square Method

2012 ◽  
Vol 622-623 ◽  
pp. 1519-1523
Author(s):  
C. Saraporn ◽  
T. Dolwichai ◽  
J. Srisertpol ◽  
K. Teeka
Keyword(s):  
Kalman Filter ◽  
Motion Control ◽  
Low Cost ◽  
Least Square Method ◽  
Scaling Factor ◽  
Least Square ◽  
Experimental Results ◽  
Signal Conditioning

Gyroscopes are important sensors in motion control in equipment such as airplanes, missiles and Segway. Low-cost gyroscopes have problems in signals such as bias, noise and scaling factor that decrease the efficiency of motion control. Therefore this paper is to present signal conditioning of low-cost gyroscopes using a Kalman filter to remove unwanted noise and nonlinear least square method to estimate parameters for compensation errors to the model by comparison with the encoder. The experimental results is shown that Kalman filter and nonlinear least square method can be used in signal conditioning of low-cost gyroscope for a more accurate signal.

A Camera Calibration Method Based on Free Points

2011 ◽  
Vol 130-134 ◽  
pp. 1885-1888
Author(s):  
Jing Lei Zhang ◽  
Kai Bo Fan ◽  
Yan Jiao Wang
Keyword(s):  
Standard Deviation ◽  
Ccd Camera ◽  
Least Square Method ◽  
Calibration Method ◽  
Initial Guess ◽  
Least Square ◽  
Camera Model ◽  
Extrinsic Parameters ◽  
The Mean ◽  
Constraint Method

A new accurate calibrating technique for intrinsic parameters and extrinsic parameters of CCD camera is described. The camera model is derived by the pinhole projection theory. Then other parameters of the model are resolved under the radial alignment constraints and orthogonal constraints. In order to get a fine initial guess for the nonlinear searching solution, the least square method is introduced, and finally uses radial alignment constraint method to get the results. The experimental results show that the mean absolute differences in x direction and y direction are 0.0070 and 0.1430 separately while the standard deviation are 0.5006 and 1.2046 separately.

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