A Design Method of Active Photoelectric Detection Sensor Based on 1-D Multiunit p-i-n Detector and Its Detection Model

Li, Hanshan; Zhang, Xiaoqian; Gao, Junchai

doi:10.1109/jsen.2022.3209675

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…The photoelectric detector noise consists of internal and external noise. The internal noise is mainly thermal noise, Johnson noise, and preamplifier noise [23]. An equivalent model is established, as shown in figure 7, where I L is the photocurrent, I nt is thermal noise, I ns is Johnson noise, R f is the feedback resistance, and R load is the output resistance.…”

Section: Electric Noisementioning

confidence: 99%

Influencing factors and uncertainty analysis for Kerr electro-optic effect based electric field measurements in transformer oil under impulse voltage

Gao,

Zhao,

Zhang

et al. 2024

Meas. Sci. Technol.

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The design of insulating structures for transformers under impulse voltage relies predominantly on simulation software due to the absence of experimental validation. This underscores the pressing need for comprehensive research into the spatial electric field and charge properties of oil-paper/pressboard insulation systems. In response to this imperative, a suite of specialized instruments leveraging the Kerr electro-optic effect to meticulously measure the spatial electric field within oil-pressboard structures under impulse voltage was established. As the precision of measurements hinges upon a multitude of influencing factors, this study embarks on a multifaceted examination, centering its focus on four pivotal dimensions: incident laser beam angle, electrical noise, temperature and non-ideal optical elements. A quantitative calculation method for electric field measurement errors was presented, and on the basis of which, suppression methods are proposed for the error sources having the largest impacts on the experimental results. Finally, the overall measurement uncertainty of the device is systematically evaluated.

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Section: Electric Noisementioning

confidence: 99%

Influencing factors and uncertainty analysis for Kerr electro-optic effect based electric field measurements in transformer oil under impulse voltage

Gao,

Zhao,

Zhang

et al. 2024

Meas. Sci. Technol.

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“…where, the coordinates of each neighboring pixel within the selected neighborhood are denoted by M , while the total number of coordinates within set M is denoted by Q [34].…”

Section: B Infrared Target Image Preprocessingmentioning

confidence: 99%

An Infrared Target Images Recognition and Processing Method Based on the Fuzzy Comprehensive Evaluation

Wu,

He,

Zhao

2024

IEEE Access

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In response to the issues of relatively low image contrast, blurry boundaries of infrared small targets, and various environmental noise interferences in thermal imaging systems, resulting in reduced target recognition rates and tracking effectiveness. This paper proposes an infrared target image recognition algorithm based on fuzzy comprehensive assessment. Built upon infrared image sequences captured by an on-board thermal imager, the algorithm employs grayscale processing, neighborhood mean filtering, and second-order difference method to filter and enhance the infrared target images. This process improves the quality of infrared target images and enhances the contrast between targets and backgrounds. The algorithm utilizes the maximum interclass variance method for segmenting the infrared target images, combining it with the Canny operator to extract target edges, thereby obtaining clearer details of the infrared target edges. Finally, based on the extracted target feature information, the algorithm calculates the confidence of each marked region, establishes the membership function of target likelihood, employs a comprehensive weighted approach to construct the target confidence function, and compares the confidence of marked regions with that of the template image to achieve precise target recognition. Experimental validation against theoretical methods and comparisons with other approaches demonstrate the effectiveness and feasibility of the proposed method, providing theoretical support for reliable target tracking in electro-optical imaging systems.

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“…Multi-view inspection is one of the important techniques for achieving accurate and fast flame and smoke monitoring in various applications [170]- [173]. The utilization of video streams from multiple cameras located in different locations allows for detecting flame and smoke faster and attaining a more accurate estimation of the current combustion state.…”

Section: Multi-view Inspection Of Combustion Flaresmentioning

confidence: 99%

AI-Enhanced Gas Flares Remote Sensing and Visual Inspection: Trends and Challenges

Radi,

Li,

Boumaraf

et al. 2024

IEEE Access

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The real-time analysis of gas flares is one of the most challenging problems in the operation of various combustion-involving industries, such as oil and gas refineries. Despite the crucial role of gas flares in securing safe plant operation and lowering environmental pollution, they are among the least monitored components of petrochemical plants due to their harsh working environments. Remote sensing techniques are emerging as potential alternatives for conventional sampling-based techniques in visual inspection and performance analysis. This paper presents an in-depth review of significant achievements in Gas flares monitoring over past two decades and highlights ongoing challenges in Artificial Intelligence (AI)enhanced remote inspection. By reading the content, both industry professionals and academic researchers can gain a comprehensive knowledge of improvements from the integration of AI and remote sensing, understanding the trend of Gas flares monitoring. The paper commences with an analysis of RGB camerabased methods, focusing on how their combination with cutting-edge machine learning and deep learning algorithms can significantly improve the detection, segmentation, and measurement of gas flare systems. It then explores the use of hyper-spectral imaging techniques, including infrared cameras and space-borne satellite sensors, underscoring their potential in remote monitoring and performance analysis. Additionally, the effectiveness of multi-view inspection methods is assessed, highlighting how these approaches enhance the monitoring capabilities. Finally, the paper identifies key research areas that require further attention. It also presents a clearer direction for future progress, emphasizing the importance of continuous research to foster advancements and facilitate broader commercial adoption.

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A Design Method of Active Photoelectric Detection Sensor Based on 1-D Multiunit p-i-n Detector and Its Detection Model

Cited by 6 publications

References 13 publications

Influencing factors and uncertainty analysis for Kerr electro-optic effect based electric field measurements in transformer oil under impulse voltage

Influencing factors and uncertainty analysis for Kerr electro-optic effect based electric field measurements in transformer oil under impulse voltage

An Infrared Target Images Recognition and Processing Method Based on the Fuzzy Comprehensive Evaluation

AI-Enhanced Gas Flares Remote Sensing and Visual Inspection: Trends and Challenges

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