scholarly journals Online Monitoring of Torpedo Car Shells Based on Equal Angle Scanning

2021 ◽  
Author(s):  
Yumei Tang ◽  
Kefu Liu
Keyword(s):  
Design Principle ◽  
Online Monitoring ◽  
Calibration Method ◽  
Measurement Unit ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Infrared Sensors ◽  
Monitoring Test ◽  
On Line ◽  
Application Requirements

Infrared sensors are applied more and more widely in industrial production applications. Based on the theory of thermal radiation, this paper discusses the system design principle, temperature calibration method and thermal image analysis method in detail. The system has passed the measurement unit certification, showing that the field of view is 180°, the number of scanning points is 2048, the linear velocity is 10-100Hz, the spatial resolution is 2.5mrad, and the precision is ±1℃. On-line monitoring test has been done in the steelmaking plant of Bao Steel. The results show that the system has strong anti-interference ability, stability and reliability, and meets the application requirements of online monitoring.

scholarly journals Online Monitoring of Torpedo Car Shells Based on Equal Angle Scanning

2021 ◽  
Vol 11 (17) ◽  
pp. 8053
Author(s):  
Yumei Tang ◽  
Kefu Liu
Keyword(s):  
Design Principle ◽  
Online Monitoring ◽  
Calibration Method ◽  
Field Of View ◽  
Measurement Unit ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Infrared Sensors ◽  
Monitoring Test ◽  
Application Requirements

Infrared sensors are being applied more and more widely in industrial production applications. Based on the theory of thermal radiation, this paper discusses the system design principle, temperature calibration method, and thermal image analysis method in detail. The system passed the measurement unit certification, showing that the field of view is 180°, the number of scanning points is 2048, the linear velocity is 10–100 Hz, the spatial resolution is 2.5 mrad, and the precision is ±1°C. An online monitoring test of torpedo car was carried out in the steelmaking plant of Bao Steel. The results show that the system has strong anti-interference ability, stability, and reliability, and meets the application requirements of online monitoring.

scholarly journals On-line data splicing power flow analysis method based on sensitivity

2021 ◽  
Vol 7 ◽  
pp. 326-333
Author(s):  
Jun Lu ◽  
Lu Lu Zhang ◽  
Dong Yu Shi ◽  
Tie Li ◽  
Jun Ci Tang ◽  
...  
Keyword(s):  
Power Flow ◽  
Flow Analysis ◽  
Analysis Method ◽  
Power Flow Analysis ◽  
On Line

scholarly journals Automated image analysis method for oil-release test of lipid-based materials

MethodsX ◽  
2021 ◽  
pp. 101447
Author(s):  
Fabio Valoppi ◽  
Petri Lassila ◽  
Ari Salmi ◽  
Edward Haeggström
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Release Test

scholarly journals Optimization-Based Online Initialization and Calibration of Monocular Visual-Inertial Odometry Considering Spatial-Temporal Constraints

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2673
Author(s):  
Weibo Huang ◽  
Weiwei Wan ◽  
Hong Liu
Keyword(s):  
Measurement Data ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Measurement Unit ◽  
Temporal Parameters ◽  
Work Routine ◽  
Initial States ◽  
Time Offset ◽  
Public Datasets ◽  
Metric Scale

The online system state initialization and simultaneous spatial-temporal calibration are critical for monocular Visual-Inertial Odometry (VIO) since these parameters are either not well provided or even unknown. Although impressive performance has been achieved, most of the existing methods are designed for filter-based VIOs. For the optimization-based VIOs, there is not much online spatial-temporal calibration method in the literature. In this paper, we propose an optimization-based online initialization and spatial-temporal calibration method for VIO. The method does not need any prior knowledge about spatial and temporal configurations. It estimates the initial states of metric-scale, velocity, gravity, Inertial Measurement Unit (IMU) biases, and calibrates the coordinate transformation and time offsets between the camera and IMU sensors. The work routine of the method is as follows. First, it uses a time offset model and two short-term motion interpolation algorithms to align and interpolate the camera and IMU measurement data. Then, the aligned and interpolated results are sent to an incremental estimator to estimate the initial states and the spatial–temporal parameters. After that, a bundle adjustment is additionally included to improve the accuracy of the estimated results. Experiments using both synthetic and public datasets are performed to examine the performance of the proposed method. The results show that both the initial states and the spatial-temporal parameters can be well estimated. The method outperforms other contemporary methods used for comparison.

Systematic Calibration Method for FOG Inertial Measurement Units

2013 ◽  
Vol 662 ◽  
pp. 717-720 ◽  
Author(s):  
Zhen Yu Zheng ◽  
Yan Bin Gao ◽  
Kun Peng He
Keyword(s):  
Inertial Measurement Unit ◽  
Inertial Sensors ◽  
Calibration Method ◽  
State Equation ◽  
Measurement Unit ◽  
Observation System ◽  
Body Frame ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Error Coefficients

As an inertial sensors assembly, the FOG inertial measurement unit (FIMU) must be calibrated before being used. The paper presents a one-time systematic IMU calibration method only using two-axis low precision turntable. First, the detail error model of inertial sensors using defined body frame is established. Then, only velocity taken as observation, system 33 state equation is established including the lever arm effects and nonlinear terms of scale factor error. The turntable experiments verify that the method can identify all the error coefficients of FIMU on low-precision two-axis turntable, after calibration the accuracy of navigation is improved.

A Computerized Image Analysis Method for Measuring Elastic Tissue.

1989 ◽  
Vol 93 (3) ◽  
pp. 358-362 ◽  
Author(s):  
Thomas J. Flotte ◽  
Johanna M. Seddon ◽  
Yuqing Zhang ◽  
Robert J. Glynn ◽  
Kathleen M. Egan ◽  
...  
Keyword(s):  
Image Analysis ◽  
Elastic Tissue ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Computerized Image Analysis
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