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Electrochemical sensor for detection of multiple environmental contaminants through advanced signal processing

机译:电化学传感器可通过高级信号处理来检测多种环境污染物

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The possibility of large-scale attacks using chemical warfare agents (CWAs) has exposed the critical need for fundamental research enabling the reliable, unambiguous, and early detection of trace CWAs and toxic industrial chemicals. This paper presents an unique approach for identification and classification of environmental contaminants by perturbing an electrochemical (EC) sensor with an oscillating potential rather than static voltage levels for extraction of statistically rich information from the current response. The dynamic response, being a function of the degree and mechanism of contamination, is then processed with a symbolic dynamic filter for extraction of representative patterns, which are then classified using a trained neural network. The approach presented in this paper promises to extend sensing power and sensitivity of these EC sensors by augmenting and complementing the sensor technology with state-of-the-art embedded real time signal processing capabilities.
机译:使用化学战剂(CWA)进行大规模攻击的可能性暴露了对基础研究的关键需求,这些基础研究能够可靠,明确和早期地检测痕量CWA和有毒工业化学品。本文提出了一种用于识别和分类环境污染物的独特方法,该方法通过用振荡电势而非静态电压电平干扰电化学(EC)传感器来从电流响应中提取丰富的统计信息。然后根据污染程度和机理对动态响应进行处理,然后使用符号动态过滤器对其进行处理,以提取代表性模式,然后使用经过训练的神经网络对这些模式进行分类。本文提出的方法有望通过使用先进的嵌入式实时信号处理功能来增强和补充传感器技术,从而扩展这些EC传感器的传感能力和灵敏度。

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