عنوان

Predictive maintenance in dynamic systems :

شابک

3030056457

شابک

3030056465

شابک

9783030056452

شابک

9783030056469

شابک اشتباه

3030056449

شابک اشتباه

9783030056445

عنوان اصلي

Predictive maintenance in dynamic systems :

نام عام مواد

[Book]

ساير اطلاعات عنواني

advanced methods, decision support tools and real-world applications /

نام نخستين پديدآور

Edwin Lughofer, Moamar Sayed-Mouchaweh, editors.

محل نشرو پخش و غیره

Cham, Switzerland :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

[2019]

نام خاص و کميت اثر

1 online resource

متن يادداشت

Includes bibliographical references and index.

متن يادداشت

Intro; Preface; Contents; Contributors; Prologue: Predictive Maintenance in Dynamic Systems; 1 From Predictive to Preventive Maintenance in Dynamic Systems: Motivation, Requirements, and Challenges; 2 Components and Methodologies for Predictive Maintenance; 2.1 Models as Backbone Component; 2.2 Methods and Strategies to Realize Predictive Maintenance; 3 Beyond State-of-the-Art-Contents of the Book; References; Smart Devices in Production System Maintenance; 1 Introduction; 2 State of the Art; 2.1 Definition of Terms; 2.2 Physical Devices/Hardware; 2.2.1 Smartphones and Tablets

متن يادداشت

2.2.2 Smartglasses2.2.3 Smartwatches; 2.3 Market View; 2.4 Device Selection and Potentials; 3 Application Examples in Maintenance; 3.1 Local Data Analysis and Communication for Condition Monitoring; 3.2 Remote Expert Solutions; 3.3 Process Data Visualization for Process Monitoring; 4 Limitations and Challenges; 4.1 Hardware Limitations; 4.2 User Acceptance; 4.3 Information Compression on Smart Devices; 4.4 Legal Aspects; 5 Summary; References; On the Relevance of Preprocessing in Predictive Maintenance for Dynamic Systems; 1 Introduction; 2 Preprocessing; 2.1 Taxonomy; 2.2 Data Cleansing

متن يادداشت

3.2 Experimental Schema3.3 Results; 4 Conclusions; References; Part I Anomaly Detection and Localization; A Context-Sensitive Framework for Mining Concept Drifting Data Streams; 1 Concept Drifting Data Streams; 1.1 Concept Drift; 2 A Novel Framework for Online Learning in Adaptive Mode; 2.1 Basic Components; 2.2 Optimizing for Stream Volatility and Speed; 3 Implementation of a Context-Sensitive Staged Learning Framework; 3.1 The Use of the Discrete Fourier Transform in Classification and Concept Encoding; 3.2 Repository Management; 3.3 The Staged Learning Approach

متن يادداشت

3.3.1 Transition Between Stages3.4 Space and Time Complexity of Spectral Learning; 4 Empirical Study; 4.1 Datasets Used for the Empirical Study; 4.1.1 Synthetic Data; 4.1.2 Synthetic Data Recurring with Noise; 4.1.3 Synthetic Data Recurring with a Progressively Increasing Pattern of Drift; 4.1.4 Synthetic Data Recurring with an Oscillating Drift Pattern; 4.1.5 Real-World Data; 4.2 Parameter Values; 4.3 Effectiveness of Staged Learning Approach; 4.4 Accuracy Evaluation; 4.4.1 ARF vs SOL Accuracy of a Concept; 4.5 Throughput Evaluation; 4.6 Accuracy Versus Throughput Trade-Off

بدون عنوان

0

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

متن يادداشت

This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783030056452

عنوان

Predictive maintenance in dynamic systems.

شماره استاندارد بين المللي کتاب و موسيقي

9783030056445

موضوع مستند نشده

Plant maintenance.

موضوع مستند نشده

Plant maintenance.

موضوع مستند نشده

TEC041000

موضوع مستند نشده

TJK

موضوع مستند نشده

TJK

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Lughofer, Edwin

مستند نام اشخاص تاييد نشده

Sayed-Mouchaweh, Moamar

تاريخ عمليات

20200823081719.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y