Oil Leakage Detection Technology of Casing Based on Relatively Infrared Imaging and Temperature Difference Criterion

2019 ◽  
Vol 08 (01) ◽  
pp. 19-26
Author(s):  
友 丁
2021 ◽  
Author(s):  
Hayeon Park ◽  
Rut Diane Cuebas ◽  
Kyoung-Soo We ◽  
Sung Hoon Kim ◽  
Chang-Gun Lee

Author(s):  
Yuchuan Du ◽  
Xiaoming Zhang ◽  
Feng Li ◽  
Lijun Sun

The degree of crack growth in asphalt pavement is an important decision-making factor in road maintenance management. Automatic crack detection is based mainly on digital images; this factor makes effective detection of the degree of crack growth difficult. Infrared thermography was used, and a detection method for the degree of crack growth on the basis of infrared imaging was proposed. Infrared images included gray-level information on cracks and temperature information; the latter provided one additional dimension of information over ordinary images. Temperature information was used to detect the degree of crack growth. Atmospheric temperature was found to be the main factor that affected the temperature difference between a crack and the road surface. This temperature difference varied significantly for different extents of crack growth, and therefore this difference can be used to detect the degree of crack growth. Two classification functions that divided the degree of crack growth into three grades were obtained by classifying data through the use of a support vector machine. A suitable environmental condition for using the detection model was proposed. The experimental results showed that the average model error was 15.4%, which indicated a good application prospect and an improvement in economic benefit for pavement maintenance.


2014 ◽  
Vol 494-495 ◽  
pp. 793-796 ◽  
Author(s):  
Chuan Jiang Li ◽  
Jia Pan Zhang ◽  
Zi Qiang Zhang ◽  
Ju Li Hu ◽  
Yi Li

The acoustic emission signal of pipeline leakage is characterized by nonlinear and non-stationary. It is not feasible to extract the leakage feature signal in traditional signal processing methods. The leak locations can be detected by employing the improved empirical mode decomposition (EMD) to decompose the acoustic emission signal into several intrinsic mode functions (IMF), choosing IMFs containing leakage characteristics to be reconstructed, and doing correlation analysis. Experimental results show that the positioning accuracy of leakage detection is improved obviously.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jinying Zhang ◽  
Defang Li ◽  
Zhuo Li ◽  
Xin Wang ◽  
Suhui Yang

AbstractLarge-pixel-array infrared emitters are attractive in the applications of infrared imaging and detection. However, the array scale has been restricted in traditional technologies. Here, we demonstrated a light-driven photothermal transduction approach for an ultralarge pixel array infrared emitter. A metal-black coating with nanoporous structures and a silicon (Si) layer with microgap structures were proposed to manage the thermal input and output issues. The effects of the nanoscale structures in the black coating and microscale structures in the Si layer were investigated. Remarkable thermal modulation could be obtained by adjusting the nanoscale and microscale structures. The measured stationary and transient results of the fabricated photothermal transducers agreed well with the simulated results. From the input view, due to its wide spectrum and high absorption, the black coating with nanoscale structures contributed to a 5.6-fold increase in the temperature difference compared to that without the black coating. From the output view, the microgap structures in the Si layer eliminated the in-plane thermal crosstalk. The temperature difference was increased by 340% by modulating the out-of-plane microstructures. The proposed photothermal transducer had a rising time of 0.95 ms and a falling time of 0.53 ms, ensuring a fast time response. This method is compatible with low-cost and mass manufacturing and has promising potential to achieve ultralarge-array pixels beyond ten million.


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