Abstract
The weather factors with on-site EMC measurement may differ a lot from the standard calibration condition, so it is necessary to analyze the impact of weather factors, such as temperature, humidity and atmosphere pressure, on the measurement accuracy of the antennas. Based on experimental study, digital signal processing, improved vector fitting methods and artificial neural networks (ANN), a comprehensive strategy is presented to analyze and predict the impact of weather factors on antenna's characteristics. Experiments and digital signal processing technology are utilized to obtain the frequency response of an antenna under various weather conditions, and an improved vector fitting method is then proposed to acquire the transfer function of the antenna, while a BP neural network is constructed to establish the nonlinear mapping between the weather factors and the antenna's frequency-domain parameters. Experimental and analyzed results show that, the proposed methodology can cope with the concrete impact from weather factors, and thereby realize effective prediction of the antenna's frequency characteristics with regards to variation of the weather conditions.
| Original language | English |
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| Title of host publication | 2009 Proceedings of the 44th International Universities Power Engineering Conference (UPEC) |
| Place of Publication | New York |
| Publisher | IEEE |
| Number of pages | 5 |
| ISBN (Print) | 9781424468232 |
| Publication status | Published - 2009 |
| Event | The 44th International Universities' Power Engineering Conference - Glasgow, United Kingdom Duration: 1 Sept 2009 → 4 Sept 2009 |
Conference
| Conference | The 44th International Universities' Power Engineering Conference |
|---|---|
| Country/Territory | United Kingdom |
| City | Glasgow |
| Period | 1/09/09 → 4/09/09 |
Keywords
- power system measurement
- artificial intelligence
- backpropagation
- electromagnetic compatibility
- environmental factors
- neural nets
- power engineering computing