optical detection
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Micromachines ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 101
Author(s):  
Fu-Ming Tzu ◽  
Shih-Hsien Hsu ◽  
Jung-Shun Chen

This paper describes the non-contact optical detection of debris material that adheres to the substrates of color filters (CFs) and thin-film transistors (TFTs) by area charge-coupled devices (CCDs) and laser sensors. One of the optical detections is a side-view illumination by an area CCD that emits a coherency light to detect debris on the CF. In contrast to the height of the debris material, the image is acquired by transforming the geometric shape from a square to a circle. As a result, the side-view illumination from the area CCD identified the height of the debris adhered to the black matrix (BM) as well as the red, green, and blue of a CF with 95, 97, 98, and 99% accuracy compared to the golden sample. The uncertainty analysis was at 5% for the BM, 3% for the red, 2% for the green, and 1% for the blue. The other optical detection, a laser optical interception with a horizontal alignment, inspected the material foreign to the TFT. At the same time, laser sensors intercepted the debris on the TFT at a voltage of 3.5 V, which the five sets of laser optics make scanning the sample. Consequently, the scanning rate reached over 98% accuracy, and the uncertainty analysis was within 5%. Thus, both non-contact optical methods can detect debris at a 50 μm height or lower. The experiment presents a successful design for the efficient prevention of a valuable component malfunction.


2022 ◽  
Author(s):  
Ionela Fringu ◽  
Anca Lascu ◽  
Ana-Maria Macsim ◽  
Ion Fratilescu ◽  
Camelia Epuran ◽  
...  

2022 ◽  
Author(s):  
Joana Krämer ◽  
Rui Kang ◽  
Laura M. Grimm ◽  
Luisa De Cola ◽  
Pierre Picchetti ◽  
...  

Author(s):  
Kanae Hiyoshi ◽  
Narumi Fukuda ◽  
Asuka Shiraishi ◽  
Sachiko Tsuda

2021 ◽  
Vol 8 ◽  
Author(s):  
Alexandre Castagna ◽  
Heidi Dierssen ◽  
Emanuele Organelli ◽  
Margarita Bogorad ◽  
Jonas Mortelmans ◽  
...  

Phaeocystis globosa is a nuisance haptophyte species that forms annual blooms in the southern North Sea and other coastal waters. At high biomass concentration, these are considered harmful algal blooms due to their deleterious impact on the local ecosystems and economy, and are considered an indicator for eutrophication. In the last two decades, methods have been developed for the optical detection and quantification of these blooms, with potential applications for autonomous in situ or remote observations. However, recent experimental evidence suggests that the interpretation of the optical signal and its exclusive association with P. globosa may not be accurate. In the North Sea, blooms of P. globosa are synchronous with those of the diatom Pseudo-nitzschia delicatissima, another harmful bloom-forming species with similar pigmentation and optical signature. Here we combine new and published measurements of pigmentation composition and inherent optical properties from pure cultures of several algal and cyanobacterial groups, together with environmental spectroscopy data, to identify the pigments generating the optical signals captured by two established algorithms. We further evaluate the association of those pigments and optical signals with P. globosa. We found that the interpretation of the pigment(s) generating the optical signals were incorrect and that previous methods are not specific to P. globosa, even in the context of the phytoplankton assemblage of the southern North Sea. Additionally, we found that the optical and pigment signatures of Phaeocystis species are part of a broad pigmentation trend across unrelated taxonomic groups related to chlorophyll c3 presence, with important consequences for the interpretation of pigment and optical data. We then develop and evaluate an algorithm to detect this pigmentation pattern with minimal influence of co-occurring species and elaborate general recommendations for the future development of algorithms.


2021 ◽  
Vol 27 ◽  
pp. 101454
Author(s):  
Kais Daoudi ◽  
Krithikadevi Ramachandran ◽  
Hussain Alawadhi ◽  
Rabah Boukherroub ◽  
Elhadj Dogheche ◽  
...  

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