MiCas:From pressure signals to counting beload particles
A new device to measure bedload transport, MiCas, is presented. It analyzes pressure time series by recognizing the imprints of impacts of individual particles as they hit pressurized membranes. A pattern analysis algorithm is used to identify the impact events. The implementation of this principle...
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| Định dạng: | BB |
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| Ngôn ngữ: | eng |
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2020
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| Truy cập trực tuyến: | http://tailieuso.tlu.edu.vn/handle/DHTL/5477 |
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oai:localhost:DHTL-54772024-01-10T09:18:27Z MiCas:From pressure signals to counting beload particles real-time measurements bedload discharge rates bedload transport A new device to measure bedload transport, MiCas, is presented. It analyzes pressure time series by recognizing the imprints of impacts of individual particles as they hit pressurized membranes. A pattern analysis algorithm is used to identify the impact events. The implementation of this principle in a dedicated microprocessor allows for real-time measurements of particle hits and cumulative particle count. MiCas particle counts correlate well with the results of image analysis. MiCas provides hardware-based measurements, hence its key advantages of minimal needs of data storage and low processing times to retrieve bedload discharge rates. 2020-02-18T02:45:33Z 2020-02-18T02:45:33Z 2017 20191209154005.0 130605s2017 BB HydrolinkNo.1, 2017, pp 17-19. 1573-2932 http://tailieuso.tlu.edu.vn/handle/DHTL/5477 eng application/pdf |
| institution |
Trường Đại học Thủy Lợi |
| collection |
DSpace |
| language |
eng |
| topic |
real-time measurements bedload discharge rates bedload transport |
| spellingShingle |
real-time measurements bedload discharge rates bedload transport MiCas:From pressure signals to counting beload particles |
| description |
A new device to measure bedload transport, MiCas, is presented. It analyzes pressure time series by recognizing the imprints of impacts of individual particles as they hit pressurized membranes. A pattern analysis algorithm is used to identify the impact events. The implementation of this principle in a dedicated microprocessor allows for real-time measurements of particle hits and cumulative particle count. MiCas particle counts correlate well with the results of image analysis. MiCas provides hardware-based measurements, hence its key advantages of minimal needs of data storage and low processing times to retrieve bedload discharge rates. |
| format |
BB |
| title |
MiCas:From pressure signals to counting beload particles |
| title_short |
MiCas:From pressure signals to counting beload particles |
| title_full |
MiCas:From pressure signals to counting beload particles |
| title_fullStr |
MiCas:From pressure signals to counting beload particles |
| title_full_unstemmed |
MiCas:From pressure signals to counting beload particles |
| title_sort |
micas:from pressure signals to counting beload particles |
| publishDate |
2020 |
| url |
http://tailieuso.tlu.edu.vn/handle/DHTL/5477 |
| _version_ |
1787821212624224256 |