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

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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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Figure 1. An example of PHM application for an automobile [15].CC BY · PubMed Central

Figure 2. Integrated sensor system for PHM [17].CC BY · PubMed Central

Figure 3. Flowchart of FMMEA process [18,19].CC BY · PubMed Central

Figure 4. Schematic figure of PME-based MLCC [21].CC BY · PubMed Central

Figure 5. ePrognostic sensor system [17].CC BY · PubMed Central

Figure 6. Example of sensing location [36] (Sensor card is put in the express card slot of a laptop).CC BY · PubMed Central

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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 › Physics and Astronomy › Instrumentation › 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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