Valve regulated lead acid battery diagnostic system based on infrared thermal imaging and fuzzy algorithm

Author(s):  
Neeraj Khera ◽  
Shakeb A. Khan ◽  
Obaidur Rahman
2020 ◽  
Vol 12 (2) ◽  
pp. 230-234
Author(s):  
Junbiao Xu ◽  
Qiang Liu ◽  
Zhang Zhang ◽  
Wen Jiang ◽  
Liwen Chong

This article proposes a detection method based on thermal imaging for lead acid-battery leakage. First of all, thermal images were obtained by scanning the lead acid-battery with an infrared camera, and the images were categorized into the two sets of train and test. Then, two methods were introduced to analyze the thermal images to determine whether there was a leakage in the battery. One method used Support Vector Machine (SVM) to train the Local Binary Pattern (LBP) texture features of the images. The other method used deep learning to detect images, and trained the obtained data by DenseNet. The results demonstrate that the two methods are accurate, and show feasibility of thermal imaging to detect lead acid-battery leakage.


2013 ◽  
Vol 12 (11) ◽  
pp. 2175-2182 ◽  
Author(s):  
Jiakuan Yang ◽  
Xinfeng Zhu ◽  
Lei Li ◽  
Jianwen Liu ◽  
Ramachandran Vasant Kumar

1995 ◽  
Vol 30 (2) ◽  
pp. 299-304 ◽  
Author(s):  
Cameron D. Skinner ◽  
Eric D. Salin

Abstract Soil lead levels were determined on and around a former battery manufacturing site. Lead concentrations ranging from 120 ppm to 5.1’ were found. The highest concentrations were found close to the factory site. When it was possible to obtain samples over a continuous depth range, it was found that lead concentration decreased with depth and that it increased above underground foundations.


Author(s):  
Thomas G. Robins ◽  
M.S. Bornman ◽  
Rodney I. Ehrlich ◽  
Anthony C. Cantrell ◽  
Elma Pienaar ◽  
...  

2021 ◽  
pp. 103789
Author(s):  
Zhuo Li ◽  
Shaojuan Luo ◽  
Meiyun Chen ◽  
Heng Wu ◽  
Tao Wang ◽  
...  

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