摘要
由于海水的污染源主要是来自轮船和入海口。该系统采用三块TCS230颜色传感器,监测轮船经过后海水的颜色变化的情况,数据采用就地处理,并运用改进型BP神经网络算法进行污染模式训练和模式识别。通过nRF401无线数字收发器,把污染识别的结果发送回监视器,再通过字符和语音对识别结果进行报告。把轮船污染数据采集器安装在轮船尾部两侧进行实时监测,结果表明,监测速度快,精确度高。
Due to water pollution sources was mainly from the vessels and into the sea. The system uses three TCS230 color sensor to monitor the ship through the water after the color changes, the data used in situ processing, and using improved BP neural network algorithm training and pattem recognition of pollution patterns. By nRF401 wireless digital transceiver, the pollution, the results of recognition sent back to the monitor, and through the character and voice of the recognition results to report. The ship pollution data collector installed on ships on both sides of the tail of real-time monitoring results show that the monitoring of speed and high accuracy.
出处
《自动化与仪表》
北大核心
2010年第3期13-18,共6页
Automation & Instrumentation
基金
广西自然科学基金重点项目(桂科自0832018Z)
广西科技攻关项目(桂科攻0895004-4)