Metal Loss Defect Failure Analysis and Prognostics Considering Defect Interactions and Complex Service Conditions
Creators: Zhang, Han
Publisher: name: University of Alberta Library
Year: 2023

<p>Clean energy has attracted intensive attention as the global energy transition is accelerated. Pipelines are significant for achieving large-scale clean energy transportation. Meanwhile, gears are vital components in wind turbines. Metal loss defects are dominant faults of pipelines and gears, impairing reliability and safety operations. Faulty equipment could result in enormous economic loss, catastrophic environmental pollution, and horrible casualties. Failure analysis and prognostics are critical for preventing equipment failures by investigating failure mechanisms and predicting operating conditions. Based on the obtained results, appropriate maintenance strategies can be enabled to improve equipment reliability and curtail operation costs. In engineering applications, pipelines and gears usually encounter complex service conditions. All these factors make deeply understanding the failure mechanisms of pipelines and gears subjected to metal loss defects and complex service conditions challenging. Thus, it is important to improve failure analysis and prognostics by considering complex service conditions. <br>
This thesis aims to obtain insights into the mechanical and failure characteristics of some equipment subjected to metal loss defects and complex service conditions through more accurate failure analysis. The procured insights are further applied to improve prognostic methods. To this end, the overall objective of this research is to achieve more accurate failure analysis and develop advanced prognostic methods for equipment subjected to metal loss defects and complex service conditions. The research objective breaks down into four sub-objectives.<br>
First, novel interaction rules are developed to achieve more accurate limit spacing distance estimation by incorporating corrosion depth and material properties. An integrated prognostic method is proposed to accurately and efficiently predict the reliability of pipelines with multiple corrosion defects. The proposed method is more beneficial for the reliability prediction of corroded pipelines than conventional ones. How inner pressure fluctuations impact corroded pipelines’ reliability is also discussed. <br>
Second, a comprehensive study on how hydrogen damage affects failure behaviors and residual strength of corroded high-strength pipelines is conducted. To quantify the effect of hydrogen damage on residual strength and achieve accurate estimation, a new burst model and a GA-BP neural network are developed for hydrogen pipelines. The proposed methods are valuable for the safety and development of hydrogen transportation. <br>
Third, insights into the mechanical behaviors of high-strength pipelines subjected to the coexistence of inner corrosion and spanning are procured through a systematic FE analysis, providing useful information to help face the challenge that the spanning is becoming more frequent. Parametric analysis is conducted to study the impact of essential factors, such as corrosion geometric features, spanning length, etc. The research results are valuable for improving pipeline integrity management. <br>
Last, how pitting influences the contact status and surface wear of meshing gears is investigated by FEM and UMESHIMOTION. An improved integrated prognostic method is developed for gear surface wear. Uncertainty in the wear coefficient from a population perspective and the effect of the variations in tooth profiles on wear propagation are incorporated. The proposed prognostic method is valuable in reducing parameter uncertainty and improving surface wear simulation. <br>
The research in this thesis provides insightful investigations into the failure and mechanical behaviors of pipelines and gears subjected to metal loss defects and complex service conditions. Innovative models and prognostic methods are developed to improve prediction performance. The research results will contribute to preventing unexpected failures of equipment used in the clean energy industry, lowering operation costs, and ensuring stable energy supplies worldwide.</p>