scholarly journals Intelligent Ball Bearing Fault Diagnosis by using Fractional Lorenz Chaos Extension Detection Method with Acceleration Sensor

2018 ◽  
Author(s):  
An-Hong Tian ◽  
Cheng-Biao Fu ◽  
Yu-Chung Li ◽  
Her-Terng Yau
Keyword(s):  
Ball Bearing ◽  
Detection Method ◽  
Low Cost ◽  
Extension Theory ◽  
Acceleration Sensor ◽  
Diagnostic Ratio ◽  
Bearing Fault Diagnosis ◽  
Dynamic Errors ◽  
Chaos System ◽  
Bearing System

In this study we used a non-autonomous Chua’s Circuit, and the fractional Lorenz chaos system together with a detection method from Extension theory to analyze the voltage signals. The measured bearing signals by acceleration sensor were introduced into the master and slave systems through a Chua’s Circuit. In a chaotic system minor differences can cause significant changes that generate dynamic errors, and extension matter-element models can be used to judge the bearing conditions. Extension theory can be used to establish classical and sectional domains using the dynamic errors of the fault conditions. The results obtained were compared with those from Discrete Fourier Transform analysis, Wavelet analysis and an integer order chaos system. The diagnostic ratio showed the fractional order master and slave chaos system calculations. The results show that the method presented in this paper is very suitable for monitoring the operational state of ball bearing system to be superior to the other methods. The diagnosis ratio was better and there were other significant advantages such as low cost and few.

scholarly journals Intelligent Ball Bearing Fault Diagnosis Using Fractional Lorenz Chaos Extension Detection

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3069 ◽  
Author(s):  
An-Hong Tian ◽  
Cheng-Biao Fu ◽  
Yu-Chung Li ◽  
Her-Terng Yau
Keyword(s):  
Fractional Order ◽  
Chaotic System ◽  
Element Model ◽  
Extension Theory ◽  
Chua’S Circuit ◽  
Chua's Circuit ◽  
Bearing Fault Diagnosis ◽  
Dynamic Errors ◽  
Chaos System ◽  
Matter Element Model

In this study we used a non-autonomous Chua’s circuit, and the fractional Lorenz chaos system. This was combined with the Extension theory detection method to analyze the voltage signals. The bearing vibration signals, measured using an acceleration sensor, were introduced into the master and slave systems through a Chua’s circuit. In a chaotic system, minor differences can cause significant changes that generate dynamic errors. The matter-element model extension can be used to determine the bearing condition. Extension theory can be used to establish classical and sectional domains using the dynamic errors of the fault conditions. The results obtained were compared with those from discrete Fourier transform analysis, wavelet analysis and an integer order chaos system. The diagnostic rate of the fractional-order master and slave chaotic system could reach 100% if the fractional-order parameter adjustment was used. This study presents a very efficient and inexpensive method for monitoring the state of ball bearings.

Parameters research on time-varying stiffness of the ball bearing system without race control hypothesis

2021 ◽  
pp. 095440622110179
Author(s):  
Yongzhen Liu ◽  
Yimin Zhang
Keyword(s):  
Ball Bearing ◽  
Combined Loading ◽  
Time Varying ◽  
Noticeable Effect ◽  
Rotating Speed ◽  
Bearing Stiffness ◽  
Vibration Mechanism ◽  
Control Hypothesis ◽  
Full Consideration ◽  
Bearing System

When the ball bearing serving under the combined loading conditions, the ball will roll in and out of the loaded zone periodically. Therefore the bearing stiffness will vary with the position of the ball, which will cause vibration. In order to reveal the vibration mechanism, the quasi static model without raceway control hypothesis is modeled. A two-layer nested iterative algorithm based on Newton–Raphson (N-R) method with dynamic declined factors is presented. The effect of the dispersion of bearing parameters and the installation errors on the time-varying carrying characteristics of the ball-raceway contact and the bearing stiffness are investigated. Numerical simulation illustrates that besides the load and the rotating speed, the dispersion of bearing parameters and the installation errors have noticeable effect on the ball-raceway contact load, ball-inner raceway contact state and bearing stiffness, which should be given full consideration during the process of design and fault diagnosis for the rotor-bearing system.

scholarly journals A Note on Advantages of the Fuzzy Gabor Filter in Object and Text Detection

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 678
Author(s):  
Vladimir Tadic ◽  
Tatjana Loncar-Turukalo ◽  
Akos Odry ◽  
Zeljen Trpovski ◽  
Attila Toth ◽  
...  
Keyword(s):  
Object Detection ◽  
Detection Method ◽  
Gabor Filter ◽  
Low Cost ◽  
Fuzzy Optimization ◽  
Detection Performance ◽  
Text Detection ◽  
License Plate ◽  
2D Gabor Filter ◽  
Fine Tune

This note presents a fuzzy optimization of Gabor filter-based object and text detection. The derivation of a 2D Gabor filter and the guidelines for the fuzzification of the filter parameters are described. The fuzzy Gabor filter proved to be a robust text an object detection method in low-quality input images as extensively evaluated in the problem of license plate localization. The extended set of examples confirmed that the fuzzy optimized Gabor filter with adequately fuzzified parameters detected the desired license plate texture components and highly improved the object detection when compared to the classic Gabor filter. The robustness of the proposed approach was further demonstrated on other images of various origin containing text and different textures, captured using low-cost or modest quality acquisition procedures. The possibility to fine tune the fuzzification procedure to better suit certain applications offers the potential to further boost detection performance.

A pragmatic eLCR for an ultrasensitive detection of methicillin-resistant Staphylococcus aureus in joint synovial fluid: superior to qPCR

The Analyst ◽  
2021 ◽  
Author(s):  
Jinyuan Chen ◽  
Hongxiang Wei ◽  
Xinyu Fang ◽  
Yuanqing Cai ◽  
Zhenzhen Zhang ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Synovial Fluid ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
Detection Method ◽  
Low Cost ◽  
Ultrasensitive Detection ◽  
Gene Detection ◽  
Methicillin Resistant ◽  
Cost Identification

A pragmatic electrochemical mecA gene detection method for a rapid, accurate and low-cost identification of MRSA in the joint synovial fluid of PJI patients.

scholarly journals A Novel Longitudinal Speed Estimator for Four-Wheel Slip in Snowy Conditions

2021 ◽  
Vol 11 (6) ◽  
pp. 2809
Author(s):  
Dongmin Zhang ◽  
Qiang Song ◽  
Guanfeng Wang ◽  
Chonghao Liu
Keyword(s):  
Control Strategies ◽  
Low Cost ◽  
Estimation Error ◽  
Slip Rate ◽  
Vehicle Speed ◽  
Acceleration Sensor ◽  
Wheel Slip ◽  
Longitudinal Acceleration ◽  
Tire Rotation ◽  
Speed Estimator

This article proposes a novel longitudinal vehicle speed estimator for snowy roads in extreme conditions (four-wheel slip) based on low-cost wheel speed encoders and a longitudinal acceleration sensor. The tire rotation factor, η, is introduced to reduce the deviation between the rotation tire radius and the manufacturer’s marked tire radius. The Local Vehicle Speed Estimator is defined to eliminate longitudinal vehicle speed estimation error. It improves the tire slip accuracy of four-wheel slip, even with a high slip rate. The final vehicle speed is estimated using two fuzzy control strategies that use vehicle speed estimates from speed encoders and a longitudinal acceleration sensor. Experimental and simulation results confirm the algorithm’s validity for estimating longitudinal vehicle speed for four-wheel slip in snowy road conditions.

scholarly journals DISMIR: a deep learning-based cancer-detection method by integrating DNA sequence and methylation information of individual cell-free DNA reads

2021 ◽  
Author(s):  
Jiaqi Li ◽  
Lei Wei ◽  
Xianglin Zhang ◽  
Wei Zhang ◽  
Haochen Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Dna Sequence ◽  
Cancer Detection ◽  
High Throughput Sequencing ◽  
Detection Method ◽  
Low Cost ◽  
Sequencing Data ◽  
Cell Free Dna ◽  
Free Dna ◽  
Novel Approach

ABSTRACTDetecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel non-invasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise prediction with low-depth cfDNA sequencing data. Here we propose a novel approach named DISMIR, which can provide ultrasensitive and robust cancer detection by integrating DNA sequence and methylation information in plasma cfDNA whole genome bisulfite sequencing (WGBS) data. DISMIR introduces a new feature termed as “switching region” to define cancer-specific differentially methylated regions, which can enrich the cancer-related signal at read-resolution. DISMIR applies a deep learning model to predict the source of every single read based on its DNA sequence and methylation state, and then predicts the risk that the plasma donor is suffering from cancer. DISMIR exhibited high accuracy and robustness on hepatocellular carcinoma detection by plasma cfDNA WGBS data even at ultra-low sequencing depths. Analysis showed that DISMIR tends to be insensitive to alterations of single CpG sites’ methylation states, which suggests DISMIR could resist to technical noise of WGBS. All these results showed DISMIR with the potential to be a precise and robust method for low-cost early cancer detection.

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