Development of Advanced Techniques For Gear Wear Monitoring and Prediction

Gears are widely used in industrial machinery, and gear failure is a main cause of machine failure. Since gear wear is often the initial stage of gear failure, its monitoring and prediction are key to minimising machine downtime, maintenance costs, and safety risks. However, existing gear wear monitoring and prediction techniques face some ongoing technical challenges, including providing direct wear information and wear assessment and prediction in a cost-effective and efficient manner. To tackle the challenges, this research aims to develop a set of advanced techniques for gear wear monitoring and prediction. The four objectives of the research and their corresponding methodologies and outcomes are summarised as follow. (a) To develop a method to obtain direct and comprehensive wear information without disassembling the gearbox. This objective was realised by combining surface replication with image analysis, allowing easy acquisition of high-resolution mould images showing wear evolution on a tooth flank. (b) To investigate the relationship between the features of worn gear surfaces and those of wear debris. To further understand the role of wear debris analysis in wear assessment, a study on various features of macropits and wear particles in the same fatigue process was conducted and provided new insights into gear pitting and its monitoring. (c) To develop an automated system for gear wear assessment. Deep learning models were developed to identify wear mechanisms and severities using gear mould images and wear debris images. High classification accuracies were achieved, and comparisons between the two image sources were made. (d) To develop a gear wear prediction model using direct wear information. A deep generative model was developed and trained on time series of gear mould images. Tests showed that the model using the state-of-the-art AI technology can generate realistic and accurate predictions. Overall, this research addressed the main limitations of existing methods and provided a direct and evidence-based tool for monitoring and predicting gear wear. Its specific contributions include a new moulding-imaging method for monitoring gear wear evolution, a detailed comparison between worn gear surfaces and wear debris in a wear process, and AI and image-based gear wear assessment and prediction models for the first time. The techniques could be performed during regular inspections of machines and used with online methods for increased robustness

Development of Novel Ultrasonic Monitoring Techniques for Improving the Reliability of Wind Turbine Gearboxes

In this work, an ultrasonic method was developed to detect lubricant on rolling bearing raceways and also the load imparted by each of the rolling elements onto the raceways. It has been implemented both in the lab and an operating wind turbine. Sensors were mounted outside the raceway and sound waves reflected from the inner face. The ratio of reflected ultrasound to transmitted (Reflection Coefficient, R) was used to infer the raceway interface condition whilst the change in time of flight of ultrasonic waves was used to deduce the deflection of the raceways and subsequently roller load. Features observed in the field measurements include variation of roller load across different rollers within a complement, variation of roller load and lubrication along with turbine operation and various bearing lubrication condition

30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)

Proceedings of COMADEM 201

Studies in Electrical Machines & Wind Turbines associated with developing Reliable Power Generation

The publications listed in date order in this document are offered for the Degree of Doctor of Science in Durham University and have been selected from the author’s full publication list. The papers in this thesis constitute a continuum of original work in fundamental and applied electrical science, spanning 30 years, deployed on real industrial problems, making a significant contribution to conventional and renewable energy power generation. This is the basis of a claim of high distinction, constituting an original and substantial contribution to engineering science

NASA Thesaurus. Volume 1: Hierarchical listing

There are 16,713 postable terms and 3,716 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary

NASA thesaurus. Volume 1: Hierarchical Listing

There are over 17,000 postable terms and nearly 4,000 nonpostable terms approved for use in the NASA scientific and technical information system in the Hierarchical Listing of the NASA Thesaurus. The generic structure is presented for many terms. The broader term and narrower term relationships are shown in an indented fashion that illustrates the generic structure better than the more widely used BT and NT listings. Related terms are generously applied, thus enhancing the usefulness of the Hierarchical Listing. Greater access to the Hierarchical Listing may be achieved with the collateral use of Volume 2 - Access Vocabulary and Volume 3 - Definitions

Condition-based maintenance: innovation in building maintenance management

Maintenance is a continuous process implemented by Facilities Management (FM) providers as one their core competences to effectively manage and maintain critical assets throughout the whole life of a building and prevent downtime of essential systems. Maintenance actions are usually categorised into two main streams: corrective (CM) and precautionary (PM). In CM equipment is repaired after a failure occurs (i.e. reactively). In contrast, PM is applied based on a fixed-time or age-schedule (i.e. preventive). However, a subdivision of PM that is widely discussed in literature, yet rarely implemented in practice within FM, is Condition-based Maintenance (CBM), which enables maintenance to be applied predictively. CBM exploits the operating condition of equipment to predict a failure occurrence, thus preventing any unexpected downtime and reducing maintenance cost by avoiding unnecessary preventive actions. The underlining theory of CBM is based on the belief that 99 per cent of equipment will evidence some sort of indicators prior to failure. Therefore, it is possible to identify the fault, determine the cause and establish the severity and longevity of the equipment’s optimum life through monitoring and evaluating data collected through various techniques. Nevertheless, although the theoretical foundations of CBM are relevant to building maintenance management, such data and technology-focused strategies are seldom considered to be a viable and feasible option within the FM strategy. Therefore, this thesis details a mixedmethods, action research project undertaken within this industry sector, which has been significantly suppressed of innovative contributions. The study investigates the viability, practicality and impact of implementing an innovative CBM focused maintenance framework that is inclusive of real-time vibration analysis and enhanced with statistical data analysis. The CBM framework is demonstrated to be economically viable, technically feasible and complimentary to the inadequacies of the existing time-based regime. The framework adds value to the buildings maintenance management objectives

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

NASA thesaurus. Volume 3: Definitions

Publication of NASA Thesaurus definitions began with Supplement 1 to the 1985 NASA Thesaurus. The definitions given here represent the complete file of over 3,200 definitions, complimented by nearly 1,000 use references. Definitions of more common or general scientific terms are given a NASA slant if one exists. Certain terms are not defined as a matter of policy: common names, chemical elements, specific models of computers, and nontechnical terms. The NASA Thesaurus predates by a number of years the systematic effort to define terms, therefore not all Thesaurus terms have been defined. Nevertheless, definitions of older terms are continually being added. The following data are provided for each entry: term in uppercase/lowercase form, definition, source, and year the term (not the definition) was added to the NASA Thesaurus. The NASA History Office is the authority for capitalization in satellite and spacecraft names. Definitions with no source given were constructed by lexicographers at the NASA Scientific and Technical Information (STI) Facility who rely on the following sources for their information: experts in the field, literature searches from the NASA STI database, and specialized references

NASA thesaurus. Volume 2: Access vocabulary

The access vocabulary, which is essentially a permuted index, provides access to any word or number in authorized postable and nonpostable terms. Additional entries include postable and nonpostable terms, other word entries and pseudo-multiword terms that are permutations of words that contain words within words. The access vocabulary contains almost 42,000 entries that give increased access to the hierarchies in Volume 1 - Hierarchical Listing