Name
Abstract | ||
|---|---|---|
In the actual environment of security detection, many kinds of liquids often exist in the same detection background, and their dangerous levels are difficult to identify. Therefore, it is very important to research on identifying the dangerous levels of various liquids. The paper establishes the S-parameter database of tested samples under specific detection environment with free space method. In the actual detection, ultra-wide-band (UWB) centimeter wave is used to measure the S-parameters of several detected liquids first. Then the fast independent component analysis (FastICA) algorithm is used for unmixing the mixed signal by Newton's iteration method and the negative entropy maximization search principle. The unmixed signal matches with the sample database adaptively, so the dangerous levels of the detected liquids are identified. Multiple experiments show that FastICA algorithm can reach a matching rate of 95% between water and 90# gasoline or alcohol and 90# gasoline, it also can reach a matching rate of around 73% between water and alcohol. This algorithm has a quick response and high reliability for identification of dangerous liquids. FastICA algorithm in this paper is applied for detecting the dangerous liquids for the first time, and it has high application value. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1142/S0218001419580035 | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
self-adaption, UWB centimeter wave, FastICA, S-parameter, detection of dangerous liquids | Pattern recognition,Fastica algorithm,Artificial intelligence,FastICA,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
33 | 2 | 0218-0014 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dongmei Zhou | 1 | 0 | 0.68 |
| Shi Qiu | 2 | 250 | 29.03 |
| Jiahai Tan | 3 | 0 | 0.34 |
| Xiaofeng Li | 4 | 0 | 0.34 |
| Chen Chen | 5 | 0 | 0.34 |