A MEMS inertial sensor and AMR magnetic sensor calibration method

2011 ◽  
Author(s):  
Wenming Li ◽  
Qingxiu Du ◽  
Peng Mi
Keyword(s):  
Inertial Sensor ◽  
Calibration Method ◽  
Magnetic Sensor ◽  
Sensor Calibration

Partition Beetles Antennae Search Algorithm for Magnetic Sensor Calibration Optimization

2020 ◽  
pp. 1-1
Author(s):  
Xiangang Li ◽  
Shenggang Yan ◽  
Jianguo Liu ◽  
Yang Sun ◽  
Youyu Yan
Keyword(s):  
Search Algorithm ◽  
Magnetic Sensor ◽  
Sensor Calibration

scholarly journals A Normal Sensor Calibration Method Based on an Extended Kalman Filter for Robotic Drilling

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3485 ◽  
Author(s):  
Dongdong Chen ◽  
Peijiang Yuan ◽  
Tianmiao Wang ◽  
Ying Cai ◽  
Haiyang Tang
Keyword(s):  
Kalman Filter ◽  
Laser Beam ◽  
Extended Kalman Filter ◽  
Zero Point ◽  
Calibration Method ◽  
Sensor Calibration ◽  
Beam Direction ◽  
Displacement Sensors ◽  
Robotic Drilling ◽  
Drilling System

To enhance the perpendicularity accuracy in the robotic drilling system, a normal sensor calibration method is proposed to identify the errors of the zero point and laser beam direction of laser displacement sensors simultaneously. The procedure of normal adjustment of the robotic drilling system is introduced firstly. Next the measurement model of the zero point and laser beam direction on a datum plane is constructed based on the principle of the distance measurement for laser displacement sensors. An extended Kalman filter algorithm is used to identify the sensor errors. Then the surface normal measurement and attitude adjustments are presented to ensure that the axis of the drill bit coincides with the normal at drilling point. Finally, simulations are conducted to study the performance of the proposed calibration method and experiments are carried out on a robotic drilling system. The simulation and experimental results show that the perpendicularity of the hole is within 0.2°. They also demonstrate that the proposed calibration method has high accuracy of parameter identification and lays a basis for high-precision perpendicularity accuracy of drilling in the robotic drilling system.

Research on HTc rf SQUID magnetic sensor calibration

ISAPE2012 ◽  
2012 ◽  
Author(s):  
Wei Tao ◽  
Jun Gao ◽  
Yuke Wei ◽  
Zhenghao Liu ◽  
Chen Zhang ◽  
...  
Keyword(s):  
Magnetic Sensor ◽  
Sensor Calibration ◽  
Rf Squid

Discussion on Maximum Likelihood-Based Methods for Inertial Sensor Calibration

2016 ◽  
Vol 16 (14) ◽  
pp. 5522-5523 ◽  
Author(s):  
Stephane Guerrier ◽  
Roberto Molinari ◽  
James Balamuta
Keyword(s):  
Maximum Likelihood ◽  
Inertial Sensor ◽  
Sensor Calibration

scholarly journals Online Calibration Method for Current Sensors Based on GPS

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1923
Author(s):  
Shuang Zhao ◽  
Jun Liu ◽  
Yansong Li
Keyword(s):  
Calibration Method ◽  
National Standard ◽  
Economic Losses ◽  
Current Sensor ◽  
Sensor Calibration ◽  
Gps Receiver ◽  
Angular Difference ◽  
Online Calibration ◽  
Calibration Methods ◽  
Current Sensors

At present, most sensor calibration methods are off-line calibration, which not only makes them time-consuming and laborious, but also causes considerable economic losses. Therefore, in this study, an online calibration method of current sensors is proposed to address the abovementioned issues. The principle and framework of online calibration are introduced. One of the calibration indexes is angular difference. In order to accurately verify it, data acquisition must be precisely synchronized. Therefore, a precise synchronous acquisition system based on GPS timing is proposed. The influence of ionosphere on the accuracy of GPS signal is analyzed and a new method for measuring the inherent delay of GPS receiver is proposed. The synchronous acquisition performance of the system is verified by inter-channel synchronization experiment, and the results show that the synchronization of the system is accurate. Lastly, we apply our online calibration method to the current sensor; the experimental results show that the angular difference and ratio difference meet the requirements of the national standard and the accuracy of the online calibration system can be achieved to 0.2 class, demonstrating the effectiveness of the proposed online calibration method.

The Design of a Multi-Functional Force Loading Device

2014 ◽  
Vol 709 ◽  
pp. 496-499
Author(s):  
Yu Qin Li ◽  
Ying Jun Li ◽  
Huan Yong Cui ◽  
Gui Cong Wang ◽  
Xi Jie Tian
Keyword(s):  
Spatial Information ◽  
Force Sensor ◽  
Calibration Method ◽  
Measurement Range ◽  
Sensor Technology ◽  
Sensor Calibration ◽  
Force Loading ◽  
Technical Performance ◽  
Loading Device ◽  
Simple Measurement

As a mechanical component, sensor can detect spatial information. Sensor technology has been widely used in national defense, aerospace, industrial inspection and automated production areas and so on. However, the sensor calibration device cannot meet the demand of the development of the sensor. In this paper, a multi-functional force loading device, which is of good technical performance, reliable operation, wide measurement range and simple measurement method, and a six-dimensional force sensor calibration method are described.

Kalman filter-based yaw angle estimation by fusing inertial and magnetic sensing: a case study using low cost sensors

Sensor Review ◽  
2015 ◽  
Vol 35 (3) ◽  
pp. 244-250 ◽  
Author(s):  
Pedro Neto ◽  
Nuno Mendes ◽  
A. Paulo Moreira
Keyword(s):  
Kalman Filter ◽  
Inertial Sensor ◽  
Low Cost ◽  
Human Robot Interaction ◽  
Magnetic Sensor ◽  
Robot Interaction ◽  
Magnetic Sensing ◽  
Content Type ◽  
Reliable Estimation ◽  
Yaw Angle

Purpose – The purpose of this paper is to achieve reliable estimation of yaw angles by fusing data from low-cost inertial and magnetic sensing. Design/methodology/approach – In this paper, yaw angle is estimated by fusing inertial and magnetic sensing from a digital compass and a gyroscope, respectively. A Kalman filter estimates the error produced by the gyroscope. Findings – Drift effect produced by the gyroscope is significantly reduced and, at the same time, the system has the ability to react quickly to orientation changes. The system combines the best of each sensor, the stability of the magnetic sensor and the fast response of the inertial sensor. Research limitations/implications – The system does not present a stable behavior in the presence of large vibrations. Considerable calibration efforts are needed. Practical implications – Today, most of human–robot interaction technologies need to have the ability to estimate orientation, especially yaw angle, from small-sized and low-cost sensors. Originality/value – Existing methods for inertial and magnetic sensor fusion are combined to achieve reliable estimation of yaw angle. Experimental tests in a human–robot interaction scenario show the performance of the system.

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