book

Prognostics and Health Management

by Douglas Goodman, James P. Hofmeister, Ferenc Szidarovszky

June 2019

Intermediate to advanced

384 pages

11h 27m

English

Wiley

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1.1 What Is Prognostics?1.2 Foundation of Reliability Theory1.3 Failure Distributions Under Extreme Stress Levels1.4 Uncertainty Measures in Parameter Estimation1.5 Expected Number of Failures1.6 System Reliability and Prognosis and Health Management1.7 Prognostic Information1.8 Decisions on Cost and Benefits1.9 Introduction to PHM: SummaryReferencesFurther Reading
2.1 Introduction to Approaches for Prognosis and Health Management/Monitoring (PHM)2.2 Model‐Based Prognostics2.3 Data‐Driven Prognostics2.4 Hybrid‐Driven Prognostics2.5 An Approach to Condition‐Based Maintenance (CBM)2.6 Approaches to PHM: SummaryReferencesFurther Reading
3.1 Introduction to Failure Signatures3.2 Basic Types of Signatures3.3 Model Verification3.4 Evaluation of FFS Curves: Nonlinearity3.5 Summary of Data Transforms3.6 Degradation Rate3.7 Failure Progression Signatures and System Nodes3.8 Failure Progression Signatures: SummaryReferencesFurther Reading
4.1 Introduction to Heuristic‐Based Modeling of Signatures4.2 General Modeling Considerations: CBD Signatures4.3 CBD Modeling: Degradation‐Signature Models4.4 DPS Modeling: FFP to DPS Transform Models4.5 FFS Modeling: Failure Level and Signature Modeling4.6 Heuristic‐Based Approach to Modeling of Signatures: SummaryReferencesFurther Reading
5.1 Introduction to Non‐Ideal Data: Effects and Conditioning5.2 Heuristic‐Based Approach Applied to Non‐Ideal CBD Signatures5.3 Errors and Non‐Ideality in FFS Data5.4 Heuristic Method for Adjusting FFS Data5.5 Summary: Non‐Ideal Data, Effects, and ConditioningReferencesFurther Reading

6.1 PHM System: Review6.2 Design Approaches for a PHM System6.3 Sampling and Polling6.4 Initial Design Specifications6.5 Special RMS Method for AC Phase Currents6.6 Diagnostic and Prognostic Procedure6.7 Specifications: Robustness and Capability6.8 Node Specifications6.9 System Verification and Performance Metrics6.10 System Verification: Advanced Prognostics6.11 PHM System Verification: EMA Faults6.12 PHM System Verification: Functional Integration6.13 Summary: A Robust Prototype PHM SystemReferencesFurther Reading
7.1 Introduction to Prognostic Enabling7.2 Prognostic Targets: Evaluation, Selection, and Specifications7.3 Example: Cost‐Benefit of Prognostic Approaches7.4 Reliability: Bathtub Curve7.5 Chapter Summary and Book ConclusionReferencesFurther Reading

Content preview from Prognostics and Health Management

List of Figures

Figure 1.1	Core prognostic frameworks in a PHM system. Source: based on IEEE (2017).
Figure 1.2	Framework diagram for a PHM system. Source: based on CAVE3 (2015).
Figure 1.3	Graph of the exponential CDF with λ = 3.
Figure 1.4	Graph of the Weibull CDF with β = 1.2 and η = 5.
Figure 1.5	Graph of the exponential PDF with λ = 3.
Figure 1.6	Graphs of gamma PDFs.
Figure 1.7	Graphs of Weibull PDFs.
Figure 1.8	Failure rates of Weibull variables.
Figure 1.9	Failure rates of gamma variables.
Figure 1.10	Failure rate of the standard normal variable.
Figure 1.11	Failure rate of the lognormal variable with μ = 0 and σ = 1.
Figure 1.12	Logistic failure rate with μ = 0 and σ = 1.
Figure 1.13	Gumbel failure rate.
Figure 1.14	Log‐logistic failure rate with μ = 0.
Figure 1.15	Integration domain.
Figure 1.16	High‐level block diagram of a PHM system.
Figure 1.17	A framework for CBM for PHM. Source: after CAVE3 (2015).
Figure 1.18	Taxonomy of prognostic approaches.
Figure 1.19	Example of an FFP signature – a curvilinear (convex), noisy characteristic curve.
Figure 1.20	Ideal DPS transfer curve superimposed on an FFP signature.
Figure 1.21	Ideal DPS, degradation threshold, and functional failure.
Figure 1.22	Normalized and transformed FFP and DPS transformed into FFS.
Figure 1.23	Ideal FFS – transfer curve for CBD.
Figure 1.24	Variability in DPS transfer curves.
Figure 1.25	FFS transforms of the DPS plots shown in Figure 1.23.
Figure 1.26	FFS and prognostic ...