电子鼻技术漂移补偿算法的进展

IF 1.6 4区工程技术 Q3 INSTRUMENTS & INSTRUMENTATION

Sensor Review Pub Date : 2024-08-30 DOI:10.1108/sr-06-2024-0554

Lei Ren, Guolin Cheng, Wei Chen, Pei Li, Zhenhe Wang

{"title":"电子鼻技术漂移补偿算法的进展","authors":"Lei Ren, Guolin Cheng, Wei Chen, Pei Li, Zhenhe Wang","doi":"10.1108/sr-06-2024-0554","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This paper aims to explore recent advances in drift compensation algorithms for Electronic Nose (E-nose) technology and addresses sensor drift challenges through offline, online and neural network-based strategies. It offers a comprehensive review and covers causes of drift, compensation methods and future directions. This synthesis provides insights for enhancing the reliability and effectiveness of E-nose systems in drift issues.</p>\n<h3>Design/methodology/approach</h3>\n<p>The article adopts a comprehensive approach and systematically explores the causes of sensor drift in E-nose systems and proposes various compensation strategies. It covers both offline and online compensation methods, as well as neural network-based approaches, and provides a holistic view of the available techniques.</p>\n<h3>Findings</h3>\n<p>The article provides a comprehensive overview of drift compensation algorithms for E-nose technology and consolidates recent research insights. It addresses challenges like sensor calibration and algorithm complexity, while discussing future directions. Readers gain an understanding of the current state-of-the-art and emerging trends in electronic olfaction.</p>\n<h3>Originality/value</h3>\n<p>This article presents a comprehensive review of the latest advancements in drift compensation algorithms for electronic nose technology and covers the causes of drift, offline drift compensation algorithms, online drift compensation algorithms and neural network drift compensation algorithms. The article also summarizes and discusses the current challenges and future directions of drift compensation algorithms in electronic nose systems.</p>","PeriodicalId":49540,"journal":{"name":"Sensor Review","volume":"22 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advances in drift compensation algorithms for electronic nose technology\",\"authors\":\"Lei Ren, Guolin Cheng, Wei Chen, Pei Li, Zhenhe Wang\",\"doi\":\"10.1108/sr-06-2024-0554\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>This paper aims to explore recent advances in drift compensation algorithms for Electronic Nose (E-nose) technology and addresses sensor drift challenges through offline, online and neural network-based strategies. It offers a comprehensive review and covers causes of drift, compensation methods and future directions. This synthesis provides insights for enhancing the reliability and effectiveness of E-nose systems in drift issues.</p>\\n<h3>Design/methodology/approach</h3>\\n<p>The article adopts a comprehensive approach and systematically explores the causes of sensor drift in E-nose systems and proposes various compensation strategies. It covers both offline and online compensation methods, as well as neural network-based approaches, and provides a holistic view of the available techniques.</p>\\n<h3>Findings</h3>\\n<p>The article provides a comprehensive overview of drift compensation algorithms for E-nose technology and consolidates recent research insights. It addresses challenges like sensor calibration and algorithm complexity, while discussing future directions. Readers gain an understanding of the current state-of-the-art and emerging trends in electronic olfaction.</p>\\n<h3>Originality/value</h3>\\n<p>This article presents a comprehensive review of the latest advancements in drift compensation algorithms for electronic nose technology and covers the causes of drift, offline drift compensation algorithms, online drift compensation algorithms and neural network drift compensation algorithms. The article also summarizes and discusses the current challenges and future directions of drift compensation algorithms in electronic nose systems.</p>\",\"PeriodicalId\":49540,\"journal\":{\"name\":\"Sensor Review\",\"volume\":\"22 1\",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sensor Review\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1108/sr-06-2024-0554\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INSTRUMENTS & INSTRUMENTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sensor Review","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1108/sr-06-2024-0554","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}

引用次数: 0

摘要

目的本文旨在探讨电子鼻（E-nose）技术漂移补偿算法的最新进展，并通过离线、在线和基于神经网络的策略解决传感器漂移难题。本文对漂移的原因、补偿方法和未来方向进行了全面综述。文章采用综合方法，系统地探讨了电子鼻系统中传感器漂移的原因，并提出了各种补偿策略。文章涵盖离线和在线补偿方法，以及基于神经网络的方法，并对现有技术进行了全面介绍。文章探讨了传感器校准和算法复杂性等挑战，同时讨论了未来的发展方向。原创性/价值本文全面综述了电子鼻技术漂移补偿算法的最新进展，涵盖了漂移原因、离线漂移补偿算法、在线漂移补偿算法和神经网络漂移补偿算法。文章还总结并讨论了电子鼻系统漂移补偿算法目前面临的挑战和未来的发展方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Advances in drift compensation algorithms for electronic nose technology

Purpose

This paper aims to explore recent advances in drift compensation algorithms for Electronic Nose (E-nose) technology and addresses sensor drift challenges through offline, online and neural network-based strategies. It offers a comprehensive review and covers causes of drift, compensation methods and future directions. This synthesis provides insights for enhancing the reliability and effectiveness of E-nose systems in drift issues.

Design/methodology/approach

The article adopts a comprehensive approach and systematically explores the causes of sensor drift in E-nose systems and proposes various compensation strategies. It covers both offline and online compensation methods, as well as neural network-based approaches, and provides a holistic view of the available techniques.

Findings

The article provides a comprehensive overview of drift compensation algorithms for E-nose technology and consolidates recent research insights. It addresses challenges like sensor calibration and algorithm complexity, while discussing future directions. Readers gain an understanding of the current state-of-the-art and emerging trends in electronic olfaction.

Originality/value

This article presents a comprehensive review of the latest advancements in drift compensation algorithms for electronic nose technology and covers the causes of drift, offline drift compensation algorithms, online drift compensation algorithms and neural network drift compensation algorithms. The article also summarizes and discusses the current challenges and future directions of drift compensation algorithms in electronic nose systems.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Sensor Review 工程技术-仪器仪表

CiteScore

3.40

自引率

6.20%

发文量

审稿时长

3.7 months

期刊介绍： Sensor Review publishes peer reviewed state-of-the-art articles and specially commissioned technology reviews. Each issue of this multidisciplinary journal includes high quality original content covering all aspects of sensors and their applications, and reflecting the most interesting and strategically important research and development activities from around the world. Because of this, readers can stay at the very forefront of high technology sensor developments. Emphasis is placed on detailed independent regular and review articles identifying the full range of sensors currently available for specific applications, as well as highlighting those areas of technology showing great potential for the future. The journal encourages authors to consider the practical and social implications of their articles. All articles undergo a rigorous double-blind peer review process which involves an initial assessment of suitability of an article for the journal followed by sending it to, at least two reviewers in the field if deemed suitable. Sensor Review’s coverage includes, but is not restricted to: Mechanical sensors – position, displacement, proximity, velocity, acceleration, vibration, force, torque, pressure, and flow sensors Electric and magnetic sensors – resistance, inductive, capacitive, piezoelectric, eddy-current, electromagnetic, photoelectric, and thermoelectric sensors Temperature sensors, infrared sensors, humidity sensors Optical, electro-optical and fibre-optic sensors and systems, photonic sensors Biosensors, wearable and implantable sensors and systems, immunosensors Gas and chemical sensors and systems, polymer sensors Acoustic and ultrasonic sensors Haptic sensors and devices Smart and intelligent sensors and systems Nanosensors, NEMS, MEMS, and BioMEMS Quantum sensors Sensor systems: sensor data fusion, signals, processing and interfacing, signal conditioning.