scholarly journals Temperature Sensor Denoising Algorithm Based on Curve Fitting and Compound Kalman Filtering

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1959
Author(s):  
Yang Zhang ◽  
Rong Wang ◽  
Shouzhe Li ◽  
Shengbo Qi
Keyword(s):  
Wavelet Transform ◽  
Kalman Filtering ◽  
Curve Fitting ◽  
Temperature Sensor ◽  
World Ocean ◽  
Theoretical Data ◽  
Least Square ◽  
Statistical Characteristics ◽  
Transform Method ◽  
Kalman Smoothing

One of the most important ocean water parameters in world ocean observations is temperature. In the application of high-precision ocean sensors, there are often various interferences and random noises. These noises will cause the linearity of the sensor to change, and it is difficult to estimate the statistical characteristics, and the results will deviate from the real temperature. Aiming at the problems in the application, this paper proposes a compound Kalman smoothing filter (CKSF) algorithm based on least square curve fitting. This algorithm first analyzes the system model of the sensor, uses the least square method to fit the theoretical data and eliminate the non-linear factors caused by system itself, then estimates the statistical characteristics of the noise required by modeling, using the wavelet transform method to track the change of noise in real time and to accurately estimate the noise variance. Finally, a compound filtering method including wavelet transform and Kalman smoothing filtering is used as the main denoising algorithm, which is more accurate than a single Kalman filtering result. The algorithm is applied to the temperature measurement process of the ocean temperature sensor. The results show that the accuracy and stability of the sensor are improved.

Demodulation of single interferograms using a sliding 2-D continuous wavelet transform method

2015 ◽  
Vol 62 (8) ◽  
pp. 633-637 ◽  
Author(s):  
Jésus Villa ◽  
Ismael de la Rosa ◽  
Rumen Ivanov ◽  
Daniel Alaniz ◽  
Efrén González
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Continuous Wavelet ◽  
Transform Method

Study of Segmentation Threshold Based on Wavelet Transform

2013 ◽  
Vol 756-759 ◽  
pp. 3855-3859
Author(s):  
Jian Yi Li ◽  
Hui Juan Wang
Keyword(s):  
Wavelet Transform ◽  
Digital Image ◽  
Region Growing ◽  
Detection Methods ◽  
Mathematical Tool ◽  
Matlab Simulation ◽  
Segmentation Method ◽  
Transform Method ◽  
Threshold Segmentation ◽  
Digital Image Enhancement

Based on the research of the four kinds of algorithms of digital image segmentation, based on edge detection methods, based on region growing method, threshold segmentation method and digital image threshold segmentation method based on wavelet transform, using MATLAB simulation of all digital image enhancement and segmentation process, the obtained results are analyzed, proving the threshold segmentation wavelet transform method has unparalleled advantages in information extraction in medical image. Wavelet transform is a mathematical tool widely used in recent years, compared with the Fu Liye transform, the window of Fu Liye transform, wavelet transform is the local transform of space and frequency, it can be very effective in extracting information from the signal [[1.

A wavelet transform method to merge Landsat TM and SPOT panchromatic data

1998 ◽  
Vol 19 (4) ◽  
pp. 743-757 ◽  
Author(s):  
J. Zhou ◽  
D. L. Civco ◽  
J. A. Silander
Keyword(s):  
Wavelet Transform ◽  
Landsat Tm ◽  
Transform Method

Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method

2015 ◽  
Vol 81 ◽  
pp. 56-64 ◽  
Author(s):  
U. Rajendra Acharya ◽  
K. Sudarshan Vidya ◽  
Dhanjoo N. Ghista ◽  
Wei Jie Eugene Lim ◽  
Filippo Molinari ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Computer Aided Diagnosis ◽  
Discrete Wavelet ◽  
Transform Method ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals Leakage Detection in Pipeline using Wavelet Transform Method

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mohd Fairusham Ghazali ◽  
Abdul Kadir Samta
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Correlation Analysis ◽  
Pipeline System ◽  
Leakage Detection ◽  
Transient Method ◽  
Research Project ◽  
Transform Method ◽  
Cepstrum Analysis ◽  
Transient Methods

This research project is focusing on the leakage detection in the pipelines using wavelet and cepstrum analysis. To fully complete this research project, experimental and analysis by using signal processing are required. This research project proposed a technique which is a transient method. The basic principle is the fact that water spouting out of a leak in a pressurized pipe generates a signal, and this signal contains information to whether a leak exists and where it is located. The present transient methods for finding leaks are mainly based upon correlation analysis, where one sensing device is installed at each side of a leak. This method is hard to operate because it needs many operators to operate it due to equipment in different place. This research project proposed a wavelet transform method to detect leakage in the pipeline system. The experimental results show appears  to improve the ability of the method to identify features in the signal.

scholarly journals State of Charge Estimation of Composite Energy Storage Systems with Supercapacitors and Lithium Batteries

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kai Wang ◽  
Chunli Liu ◽  
Jianrui Sun ◽  
Kun Zhao ◽  
Licheng Wang ◽  
...  
Keyword(s):  
Energy Storage ◽  
Kalman Filtering ◽  
Lithium Batteries ◽  
Estimation Error ◽  
Storage System ◽  
Energy Storage System ◽  
Least Square ◽  
Recursive Least Square ◽  
Soc Estimation ◽  
Composite Energy

This paper studies the state of charge (SOC) estimation of supercapacitors and lithium batteries in the hybrid energy storage system of electric vehicles. According to the energy storage principle of the electric vehicle composite energy storage system, the circuit models of supercapacitors and lithium batteries were established, respectively, and the model parameters were identified online using the recursive least square (RLS) method and Kalman filtering (KF) algorithm. Then, the online estimation of SOC was completed based on the Kalman filtering algorithm and unscented Kalman filtering algorithm. Finally, the experimental platform for SOC estimation was built and Matlab was used for calculation and analysis. The experimental results showed that the SOC estimation results reached a high accuracy, and the variation range of estimation error was [−0.94%, 0.34%]. For lithium batteries, the recursive least square method is combined with the 2RC model to obtain the optimal result, and the estimation error is within the range of [−1.16%, 0.85%] in the case of comprehensive weighing accuracy and calculation amount. Moreover, the system has excellent robustness and high reliability.

Sign in / Sign up

Export Citation Format

Share Document