{"title":"Lock-in spectrum: a tool for representing long-term evolution of bearing fault in the time–frequency domain using vibration signal","authors":"Meng Zhang","doi":"10.1108/sr-04-2024-0365","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This study aims to propose a method for monitoring bearing health in the time–frequency domain, termed the Lock-in spectrum, to track the evolution of bearing faults over time and frequency.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>The Lock-in spectrum uses vibration signals captured by vibration sensors and uses a lock-in process to analyze specified frequency bands. It calculates the distribution of signal amplitudes around fault characteristic frequencies over short time intervals.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>Experimental results demonstrate that the Lock-in spectrum effectively captures the degradation process of bearings from fault inception to complete failure. It provides time-varying information on fault frequencies and amplitudes, enabling early detection of fault growth, even in the initial stages when fault signals are weak. Compared to the benchmark short-time Fourier transform method, the Lock-in spectrum exhibits superior expressive ability, allowing for higher-resolution, long-term monitoring of bearing condition.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>The proposed Lock-in spectrum offers a novel approach to bearing health monitoring by capturing the dynamic evolution of fault frequencies over time. It surpasses traditional methods by providing enhanced frequency resolution and early fault detection capabilities.</p><!--/ Abstract__block -->","PeriodicalId":49540,"journal":{"name":"Sensor Review","volume":"24 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-07-25","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-04-2024-0365","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
Abstract
Purpose
This study aims to propose a method for monitoring bearing health in the time–frequency domain, termed the Lock-in spectrum, to track the evolution of bearing faults over time and frequency.
Design/methodology/approach
The Lock-in spectrum uses vibration signals captured by vibration sensors and uses a lock-in process to analyze specified frequency bands. It calculates the distribution of signal amplitudes around fault characteristic frequencies over short time intervals.
Findings
Experimental results demonstrate that the Lock-in spectrum effectively captures the degradation process of bearings from fault inception to complete failure. It provides time-varying information on fault frequencies and amplitudes, enabling early detection of fault growth, even in the initial stages when fault signals are weak. Compared to the benchmark short-time Fourier transform method, the Lock-in spectrum exhibits superior expressive ability, allowing for higher-resolution, long-term monitoring of bearing condition.
Originality/value
The proposed Lock-in spectrum offers a novel approach to bearing health monitoring by capturing the dynamic evolution of fault frequencies over time. It surpasses traditional methods by providing enhanced frequency resolution and early fault detection capabilities.
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.