Emission Monitoring Using Optical and Acoustic Sensors Combined with Neural Networks

机译：使用光学和声学传感器结合神经网络进行排放监测

获取原文

获取原文并翻译 | 示例

页面导航

摘要
著录项
相似文献
相关主题

摘要

A simple and low-cost prototype emission monitoring system via flame detection using a combination of optical and acoustic sensors has been developed. Signals from the sensors are extracted using digital signal processing techniques to obtain features which represent flame signatures in relation to emission data. These features are applied to a neural network for training and subsequently for the monitoring of combustion emission. Preliminary results obtained on a combustion test facility show good correlation between reference emission data and those from the monitoring system. The relative error between the predicted emission and the expected value is less than 1.6%.

机译：通过使用光学和声学传感器的组合进行火焰检测，开发了一种简单且低成本的原型排放监测系统。使用数字信号处理技术提取来自传感器的信号，以获得代表与发射数据相关的火焰特征的特征。这些特征被应用于神经网络，以进行训练，随后用于燃烧排放的监测。在燃烧测试设备上获得的初步结果表明参考排放数据与监测系统的排放数据之间具有良好的相关性。预测排放量与预期值之间的相对误差小于1.6％。

著录项

来源
《Conference on Sensors and Their Applications; 20030902-20030904; Limerick; IE》|2003年|P.421-427|共7页
会议地点 Limerick(IE)
作者
K Chua; L Xu; Y Yan;
展开▼
作者单位

Centre for Advanced Instrumentation and Control, School of Engineering, University of Greenwich at Medway, Chatham Maritime, Kent ME4 4TB, UK;

展开▼
会议组织
原文格式 PDF
正文语种 eng
中图分类应用;
关键词

相似文献

外文文献
中文文献
专利

1. Feasibility of integrated optical fibre sensors for condition monitoring of composite structures Part Ⅱ: Combination of Bragg-sensors and acoustic emission detection [J] . W De Waele, J Degrieck, P De Baets, Insight . 2003,第8期

机译：集成光纤传感器用于复合结构状态监测的可行性第二部分：布拉格传感器与声发射检测的结合
2. Stress wave evaluation by accelerometer and acoustic emission sensor for thermally modified wood classification using three types of neural networks [J] . Nasir Vahid, Nourian Sepideh, Avramidis Stavros, Holz als Roh- und Werkstoff . 2019,第1期

机译：使用三种神经网络通过加速度计和声发射传感器对热改性木材分类进行应力波评估
3. Combining convolutional neural networks with unsupervised learning for acoustic monitoring of robotic manufacturing facilities [J] . Jeffrey Bynum, David Lattanzi Advances in Mechanical Engineering . 2021,第4期

机译：结合卷积神经网络对机器人制造设施声学监测的无监督学习
4. Emission Monitoring Using Optical and Acoustic Sensors Combined with Neural Networks [C] . K Chua, L Xu, Y Yan Conference on sensors and their applications . 2003

机译：使用光学和声学传感器与神经网络相结合的发射监控
5. Polymer Optical Fiber Sensor and the Prediction of Sensor Response Utilizing Artificial Neural Networks. [D] . Haroglu, Derya. 2014

机译：聚合物光纤传感器及利用人工神经网络的传感器响应预测。
6. Identification of the Degree of Degradation of Fibre-Cement Boards Exposed to Fire by Means of the Acoustic Emission Method and Artificial Neural Networks [O] . Krzysztof Schabowicz, Tomasz Gorzelańczyk, Mateusz Szymków 2019

机译：借助声发射法和人工神经网络确定纤维水泥板在火中的降解程度
7. Event-based Acoustic Emission Technique for Structural Health Monitoring using Wireless Sensor Networks [O] . Sebastian A. Bachmaier 2012

机译：基于事件的声发射技术，用于使用无线传感器网络进行结构健康监测
8. Classification of acoustic emission waveforms for nondestructive evaluation using neural networks. [R] . Barga, R. S., Melton, R. B., Friesel, M. A. 1990

机译：用神经网络进行无损评估的声发射波形分类。

Emission Monitoring Using Optical and Acoustic Sensors Combined with Neural Networks

摘要

著录项

相似文献

相关主题

期刊订阅