Sensor Systems for Prognostics and Health Management

Cheng, Shunfeng; Azarian, Michael H.; Pecht, Michael G.

doi:10.3390/s100605774

Cited by 188Reliability and Maintenance OptimizationMachine Fault Diagnosis TechniquesSensor Technology and Measurement Systems

Sensor Systems for Prognostics and Health Management

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Cheng, Shunfeng, Azarian, Michael H., Pecht, Michael G.·2010·Sensors

DOI 10.3390/s100605774PMC PMC3247731

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Abstract

Prognostics and health management (PHM) is an enabling discipline consisting of technologies and methods to assess the reliability of a product in its actual life cycle conditions to determine the advent of failure and mitigate system risk. Sensor systems are needed for PHM to monitor environmental, operational, and performance-related characteristics. The gathered data can be analyzed to assess product health and predict remaining life. In this paper, the considerations for sensor system selection for PHM applications, including the parameters to be measured, the performance needs, the electrical and physical attributes, reliability, and cost of the sensor system, are discussed. The state-of-the-art sensor systems for PHM and the emerging trends in technologies of sensor systems for PHM are presented.

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These are important issues when developing a PHM strategy for AV technology.
“To sum up, these are the important issues when developing a PHM strategy for AV technology [49].”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [49]
The Conclusions and the section on sensor-system selection identify important considerations for PHM applications, including monitoring requirements, reliability, cost, and trade-offs. The paper does not specifically assess those issues for AV technology; that application is an extension made by the citing document. (LLM, conf=0.82)
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Authors: Cheng, S., Azarian, M. H., & Pecht, M. G.
Affiliations: University of Maryland, College Park (US)
City University of Hong Kong (HK)
Corresponding author: Pecht, Michael G.
ORCID: Cheng, Shunfeng
Azarian, Michael H.
Pecht, Michael G.
Venue: Sensors
Publisher: MDPI AG
Published: 2010-06-08
Volume: 10
Issue: 6
Pages: 5774-5797
ISSN: 1424-8220 (ISSN-L)
DOI: 10.3390/s100605774
PMC: PMC3247731
OpenAlex: W2149823865
Cited by: 188
References: 56
Citations by year: 2026: 4 · 2025: 10 · 2024: 9 · 2023: 8 · 2022: 10 · 2021: 13 · 2020: 13 · 2019: 11 · 2018: 17 · 2017: 9 · 2016: 16 · 2015: 16 · 2014: 11 · 2013: 12 · 2012: 18
FWCI: 6.71
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/3.0/ (vor)
Locations: Sensors (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
CityU Scholars (submittedVersion, cc-by)
Topics: Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
Physical Sciences › Computer Science › Computer Networks and Communications › Sensor Technology and Measurement Systems
Keywords: prognostics and health management, sensor systems, sensor selection, remaining useful life prediction, product reliability, fault detection, sensor reliability, sensor cost, condition monitoring
MeSH terms: Computer Communication Networks, Health, Humans, Models, Biological, Monitoring, Physiologic, Prognosis, Biosensing Techniques, Delivery of Health Care, Integrated, Disease Management

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