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Development of Neuro-Intelligent Gas Sensing System for Water Environmental Monitering

水环境监测神经智能气体传感系统开发

基本信息

批准号：
05044086
负责人：
MORIIZUMI Toyosaka
金额：
$ 2.56万
依托单位：
TOKYO INSTITUTE OF TECHNOLOGY
依托单位国家：
日本
项目类别：
Grant-in-Aid for international Scientific Research
财政年份：
1993
资助国家：
日本
起止时间：
1993 至 1994
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-05044086/
关键词：
Gas Sensor Environmental Monitoring Chemometrix

项目摘要

Water environmental monitoring system has been developed. The system consists of sensors array, measuring system and a computer with an artificial neural network algorithm for gas indentification. The system is designed for measuring oxygen, ammonia and hydrogen sulfide dissolved in water solution from river.1. Sensors fabrication and selection : Thin film tin oxide semiconductor gas sensors were fabricated. Calcium oxide and aluminum were doped to increase the sensor selectivity. It was found that the sensors responded to alcohol, ammonium and acetaldehyde. Thin film and bulk type dissolved oxygen sensor have been also developed. It was found that the thin film type is suitable for disposable use and the bulk type is suitable for long term measurement. The commercial semiconductor gas sensors (Figaro _<800, >813, _<824, >823) were also used for testing the system. It was found that they are suitable for measuring ammonia and hydrogen sulfide.2. Measurement system : Dip type and flow t … More hrough cell type measuring systems have been developed by combining the sensors. They were used to measure samples in solution phase and gas phase respectively. The former one has a detection limit for ammonia and hydrogen sulfide at 2 ppm with the response time of 3 minutes, while they were 100 ppm and 20 seconds for the latter.3. Recognition algorithm : The artificial neural network with the error back propagation algorithm has been used with the above system to enhance the gas recognition capability. After the network was trained with standard gas, it has been found that the recognition error for hydrogen sulfide and ammonia were 2 ppm and 2-25 ppm, respectively.4. Measurement of river water : The developed system was used to measure the samples from Chao-Praya river in Bangkok. It was found that the concentration of ammonia and hydrogen sulfide in the samples were lower than 3 ppm, which is the detection limit of the system.In summary, we have been developed a water quality monitoring system using array sensors tpgether with artificial neural network to enhance the system performance. The system has a detection limit of 3 ppm for dissolved ammonia and hydrogen sulfide. We propose that the system can be modified for measuring gas concentration in 100 ppb range by combining the dip type sensors together with flow through cell system. Less

开发了水环境监测系统。该系统由传感器阵列、测量系统和具有用于气体识别的人工神经网络算法的计算机组成。该系统设计用于测量河流水溶液中溶解的氧气、氨和硫化氢。 1．传感器的制造和选择：制造了薄膜氧化锡半导体气体传感器。掺杂氧化钙和铝以提高传感器的选择性。研究发现，传感器对酒精、铵和乙醛有反应。还开发了薄膜型和体型溶解氧传感器。结果发现，薄膜型适合一次性使用，散装型适合长期测量。商用半导体气体传感器（Figaro _<800、>813、_<824、>823）也用于测试系统。结果表明，它们适用于氨气和硫化氢的测量。 2．测量系统：通过组合传感器开发了浸入式和流动式测量系统。它们分别用于测量液相和气相样品。前者对氨和硫化氢的检测限为2 ppm，响应时间为3分钟，而后者为100 ppm，响应时间为20秒。 3．识别算法：上述系统采用带有误差反向传播算法的人工神经网络，增强了气体识别能力。用标准气体对网络进行训练后，发现硫化氢和氨的识别误差分别为2 ppm和2-25 ppm。 4．河水测量：开发的系统用于测量曼谷Chao-Praya河的样本。结果发现样品中氨和硫化氢的浓度低于3 ppm，这是系统的检测限。综上所述，我们开发了一种采用阵列传感器与人工神经网络相结合的水质监测系统，以增强系统性能。该系统对溶解氨和硫化氢的检测限为 3 ppm。我们建议通过将浸入式传感器与流通池系统结合起来，对该系统进行修改，以测量 100 ppb 范围内的气体浓度。较少的