Probabilistic Risk Assessment: Impact of Human Factors on Nondestructive Evaluation and Sensor Degradation on Structural Health Monitoring
Abstract
Managing human factors in nondestructive evaluation is critical for maintaining inspection reliability. Reliability of structural health monitoring systems is particularly sensitive to sensor degradation over time. To investigate the impact of these issues, probabilistic models for risk assessment and cost‐benefit analysis tools have been developed. Quantitative studies are presented evaluating the effects of variations in probability of detection associated with human factors, plus in‐situ sensor degradation effects on life cycle measures such as cost and probability of failure.
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Strain-gauge acoustic emission transducers and ultrasonic eddy current sensors suffer from sensor bond degradation and can result in inconsistent sensitivity.
“Additionally, strain-gauge acoustic emission transducers and ultrasonic eddy current sensors suffer from sensor bond degradation processes and can result in inconsistent sensitivity (Aldrin et al., 2007).”
From Impact of Sensor Degradation on Measurement Uncertainty in Prognostics and Maintenance Decision-Making: (2025) · cites this paper as Aldrin et al., 2007
In Aldrin et al. (2007), sensor degradation slightly reduces total maintenance costs due to fewer repairs.
“The results show that sensor degradation significantly increases the probability of failure (e.g., an increase in random missed detection rate to 10% or detectable crack size to 0.07 inches leads to higher failure risks), while slightly reducing total maintenance costs due to fewer repairs, highlighting the critical need for sensor replacement or recalibration to balance safety and cost.”
From Impact of Sensor Degradation on Measurement Uncertainty in Prognostics and Maintenance Decision-Making: (2025) · cites this paper as Aldrin et al. (2007)
Aldrin et al. (2007) employed a probabilistic risk assessment and cost-benefit analysis to evaluate how sensor degradation affects the reliability of SHM systems.
“To address this, Aldrin et al. (2007) employed a probabilistic risk assessment and cost-benefit analysis to evaluate how sensor degradation affects the reliability of SHM systems.”
From Impact of Sensor Degradation on Measurement Uncertainty in Prognostics and Maintenance Decision-Making: (2025) · cites this paper as Aldrin et al. (2007)
In Aldrin et al. (2007), sensor degradation significantly increases the probability of failure.
“The results show that sensor degradation significantly increases the probability of failure (e.g., an increase in random missed detection rate to 10% or detectable crack size to 0.07 inches leads to higher failure risks), while slightly reducing total maintenance costs due to fewer repairs, highlighting the critical need for sensor replacement or recalibration to balance safety and cost.”
From Impact of Sensor Degradation on Measurement Uncertainty in Prognostics and Maintenance Decision-Making: (2025) · cites this paper as Aldrin et al. (2007)
Cited by
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Thai, T.-T. N., Do, P., Iung, B., & Gardoni, P. (2025) · International Journal of Prognostics and Health Management · doi:10.36001/ijphm.2025.v16i4.4306 · Cited by 5 · see citing works
- Authors
- Aldrin, J. C., Medina, E. A., Allwine, D. A., QadeerAhmed, M., Fisher, J., Knopp, J. S., & Lindgren, E. A.
- Affiliations
- Austral Engineering and Software (United States) (US)
- United States Air Force Research Laboratory (US)
- Venue
- AIP Conference Proceedings
- Publisher
- AIP
- Published
- 2007
- Volume
- 894
- Pages
- 1461-1468
- ISSN
- 0094-243X (ISSN-L)
- OpenAlex
- W1480250692
- Cited by
- 6
- References
- 0
- Citations by year
- 2024: 1 · 2021: 1
- FWCI
- 4.27
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- AIP conference proceedings (publishedVersion)
- Funders
- Small Business Innovation Research
- U.S. Air Force
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Mechanical Engineering › Non-Destructive Testing Techniques
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
- Keywords
- probabilistic risk assessment, human factors, non-destructive testing, sensor degradation, structural health monitoring, inspection reliability, detection probability, cost-benefit analysis, life cycle cost, failure probability
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