scholarly journals The Application of Multiple Wireless Sensor Data Fusion Algorithm in Temperature Monitoring System

2018 ◽  
Keyword(s):  
Data Fusion ◽  
Monitoring System ◽  
Temperature Monitoring ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Fusion Algorithm ◽  
Sensor Data Fusion

Heterogeneous Sensor Data Fusion Method for Temperature Monitoring in Carbon Fiber Carbonization Process

2013 ◽  
Vol 711 ◽  
pp. 403-407
Author(s):  
Hai Nan Li ◽  
Li Hong Ren ◽  
Yong Sheng Ding
Keyword(s):  
Carbon Fiber ◽  
Data Fusion ◽  
Temperature Monitoring ◽  
Sensor Data ◽  
Iteration Algorithm ◽  
Fusion Algorithm ◽  
External Interference ◽  
Carbonization Process ◽  
Sensor Data Fusion ◽  
Average Value

Certain error exists in the data collected from multi-sensor network, which is caused by the external interference and defect of sensors. Thus, data fusion algorithm is applied in such monitoring to improve the reliability. In this paper, we propose a heterogeneous sensor data fusion algorithm for temperature monitoring in carbon fiber carbonization process. Through an improved adaptive weighting algorithm and iteration algorithm based on the average value, data from heterogeneous sensors are merged to obtain data closer to the real values. The feasibility of the method is verified in experiment.

scholarly journals Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2480
Author(s):  
Isidoro Ruiz-García ◽  
Ismael Navarro-Marchal ◽  
Javier Ocaña-Wilhelmi ◽  
Alberto J. Palma ◽  
Pablo J. Gómez-López ◽  
...  
Keyword(s):  
Data Fusion ◽  
Reference System ◽  
Inertial Sensor ◽  
Low Cost ◽  
Sampling Rate ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Improve Technique ◽  
Worst Case ◽  
Sensor Data Fusion

In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from −1.13° (roll) to 0.44° (yaw) and 95% limits of agreements from 2.87° (yaw) to 6.27° (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.

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