Machine Health and Condition Monitoring
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".
Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 7564
Special Issue Editor
Special Issue Information
Short Introduction: Condition monitoring methods have now been used to determine machine health for many decades. At present, the ongoing developments in sensing, data, computing, infrastructure and advanced analytics mean that we are seeing unparalleled growth in the technologies being successfully applied to condition monitoring. This Special Issue entitled “Machine Health and Condition Monitoring” will review the breadth and depth of such developments, from the system level down to detailed individual elements within the system. Table 1 provides typical functions that will be covered.
This Special Issue will bring together papers detailing advancements enabled by the increased availability of sensors and data, used in conjunction with advanced analysis methods. This may include any aspect of condition monitoring, from novel or improved sensing, working with increased amounts of sensor data such as high-frequency continuous vibration data or video/high-resolution image capture, managing data quality, pre-processing, and feature extraction. We are also interested in works utilizing or improving existing knowledge such as physics-based models or incorporating domain knowledge through the use of NLP/text mining to extract useful information from text records such as equipment logbooks, maintenance reports or manuals. Research on the development of data-driven models using advanced statistics, machine learning/artificial intelligence for the identification and prognosis of machine health status, including digital twins, is also of interest. Further, we are accepting papers presenting methods for aiding asset management, such as decision support, operational research and optimization.
Table 1: Condition monitoring system functions included in the scope of this Special Issue.
|
Function |
Examples |
|
Advisory |
Decision support; prioritized operations; maintenance planning; optimization |
|
Prognostic |
Availability; future health/capability; remaining useful Life (RUL); digital twin |
|
Diagnostic |
Current health; status; usage; BIT code; failure/fault diagnostic; RCA |
|
State Detection |
Exceedance monitoring; anomaly detection; alerting; trending; configuration; BIT; segmentation; regime recognition |
|
Manipulation |
Pre-processing; feature or information extraction; frequency domain data; normalization |
|
Sensor or Record Data |
Physical parameters (temperature; speed; vibration); date/time; GPS; video; picture; text |
Prof. Dr. Honor Powrie
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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Keywords
- machine health
- condition monitoring
- asset management
- novel/advanced sensing
- physics-based/data-driven models
- big data
- AI/ML
- advanced statistics, digital twins, OR/optimization.
