مشخصات مقاله:
عنوان فارسی مقاله:
یک روش سیستماتیک برای تعریف معماری سیستم مدیریت پیش آگاهی و سلامت
عنوان انگلیسی مقاله:
A systematic methodology for Prognostic and Health Management system architecture definition
کلمات کلیدی مقاله:
مدیریت پیش آگهی و بهداشت (PHM)، معماری سیستم، مهندسی سیستم (SE)، تعمیر و نگهداری هواپیما
کلمات کلیدی انگلیسی:
Prognostic and Health Management (PHM) – System architecture – System engineering (SE) – Aircraft maintenance
مناسب برای رشته های دانشگاهی زیر:
مهندسی صنایع
مناسب برای گرایش های دانشگاهی زیر:
مهندسی سیستم های سلامت
وضعیت مقاله انگلیسی و ترجمه:
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فهرست مطالب:
Abstract
Keywords
1. Introduction
2. Architecture definition methodology
2.1. Architecture definition process
2.1.1. Task 1: define system framework
2.1.2. Task 2: develop system architecture
2.1.3. Task 3: allocate requirements to architecture elements to form derived requirements
2.2. Validation and verification considerations
3. Application towards PHM system architecture development
3.1. Framework
3.2. System functions
3.3. Functional architecture
3.3.1. External systems and interfaces
3.3.2. PHM internal elements and interfaces
3.4. Physical architecture
3.5. Requirements derivation and allocation
3.6. Architecture validation and verification
4. Case study 1: PHM architecture SysML modeling
4.1. Functional structure modeling
4.2. Logical behavior modeling
4.2.1. State diagrams
4.2.2. Activity diagrams
4.3. Physical structure modeling
5. Case study 2: PHM architecture analysis
5.1. Functions analysis
5.2. Interface analysis
5.3. Traceability analysis
5.4. Compliance analysis
5.4.1. OSA-CBM (ISO-13374)
5.4.2. IEEE standard 1856
6. Conclusions and future work
Acknowledgment
Appendix. Supplementary materials
Research Data
References
قسمتی از مقاله انگلیسی:
1. Introduction
Prognostics and health management (PHM) has emerged as one of the key solutions for improving system reliability, safety, maintainability, supportability, and economic affordability for major industrial assets (e.g. aircraft, power plants, trains). A growing amount of literature has evaluated diagnostic and prognostic technologies with the aim to optimize asset operations and maintenance while improving safety, reliability, and cost-effectiveness [1,2]. Moreover, many papers discuss key aspects of system maintenance and PHM systems, such as maintenance principles [3–5], cost and efficiency [6–8], safety and reliability [9]. PHM describes a set of capabilities involving both diagnostics and prognostics: diagnostics concerns the process of fault detection and isolation, while prognostics is the process of predicting the future state or remaining useful life (RUL) according to current or historical conditions [10]. In Niu’s research [11], it is stated that the design team should have a thorough understanding of methods for optimal selection of monitoring strategies, tools, and algorithms needed to detect, isolate, and predict the time evolution of the fault, as well as systems, approaches for designing experiments and testing protocols, performance metrics, and means to verify and validate the effectiveness and performance of the selected models. PHM research has a specific focus towards the management of some of this complexity via monitoring, diagnostic, and prognostic technologies. The strategic application of PHM technologies has been shown to effectively reduce equipment/ process downtime and lower maintenance costs [12]. Part of the challenge of PHM, particularly for manufacturers, is to know exactly how to apply PHM within the operations to gain the maximum actionable information [12].