Machine Health and Condition Monitoring

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

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