Automated Defect Detection and Decision-Support in Gas Turbine Blade Inspection
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aerospace Article Automated Defect Detection and Decision-Support in Gas Turbine Blade Inspection Jonas Aust 1,* , Sam Shankland 2, Dirk Pons 1 , Ramakrishnan Mukundan 2 and Antonija Mitrovic 2 1 Department of Mechanical Engineering, University of Canterbury, Christchurch 8041, New Zealand; [email protected] 2 Department of Computer Science and Software Engineering, University of Canterbury, Christchurch 8041, New Zealand; [email protected] (S.S.); [email protected] (R.M.); [email protected] (A.M.) * Correspondence: [email protected]; Tel.: +64-210-241-3591 Abstract: Background—In the field of aviation, maintenance and inspections of engines are vitally important in ensuring the safe functionality of fault-free aircrafts. There is value in exploring automated defect detection systems that can assist in this process. Existing effort has mostly been directed at artificial intelligence, specifically neural networks. However, that approach is critically dependent on large datasets, which can be problematic to obtain. For more specialised cases where data are sparse, the image processing techniques have potential, but this is poorly represented in the literature. Aim—This research sought to develop methods (a) to automatically detect defects on the edges of engine blades (nicks, dents and tears) and (b) to support the decision-making of the inspector when providing a recommended maintenance action based on the engine manual. Findings—For a small sample test size of 60 blades, the combined system was able to detect and locate the defects with an accuracy of 83%. It quantified morphological features of defect size and location. False positive Citation: Aust, J.; Shankland, S.; and false negative rates were 46% and 17% respectively based on ground truth. Originality—The Pons, D.; Mukundan, R.; Mitrovic, A. work shows that image-processing approaches have potential value as a method for detecting defects Automated Defect Detection and in small data sets. The work also identifies which viewing perspectives are more favourable for Decision-Support in Gas Turbine automated detection, namely, those that are perpendicular to the blade surface. Blade Inspection. Aerospace 2021, 8, 30. https://doi.org/10.3390/ Keywords: automated defect detection; blade inspection; gas turbine engines; aircraft; visual inspec- aerospace8020030 tion; image segmentation; image processing; applied computing; computer vision; object detection; maintenance automation; aerospace; MRO Academic Editors: Wim J.C. Verhagen and Kyriakos I. Kourousis Received: 30 December 2020 Accepted: 22 January 2021 1. Introduction Published: 26 January 2021 Aircraft engine maintenance plays a crucial role in ensuring the safe flight state and Publisher’s Note: MDPI stays neutral operation of an aircraft, and image processing—whether by human or automatic methods— with regard to jurisdictional claims in is key to decision-making. Aircraft engines are exposed to extreme environmental factors published maps and institutional affil- such as mechanical loadings, high pressures and operating temperatures, and foreign iations. objects. These contribute to the risk of damage to the engine blades [1–4]. It is vitally important to ensure high quality inspection and maintenance of engines to detect any damage at the earliest stage before it propagates towards more severe outcomes. Missing defects during inspection can cause severe damage to the engine and aircraft and have the potential to cause harm and even fatalities [5–7]. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. There are several levels of inspection, each with their own tools and techniques. A This article is an open access article comprehensive inspection workflow is presented in Figure1. The V-diagram shows the distributed under the terms and different levels and their hierarchy. The more detailed the inspection (further down in conditions of the Creative Commons the diagram), the better the available inspection techniques, but at the same time the Attribution (CC BY) license (https:// higher the cost introduced for further disassembly and reassembly. The different inspection creativecommons.org/licenses/by/ levels can be summarised into two main types of inspection: in-situ borescope inspection 4.0/). performed on-wing or during induction inspection and subsequent module and piece-part Aerospace 2021, 8, 30. https://doi.org/10.3390/aerospace8020030 https://www.mdpi.com/journal/aerospace Aerospace 2021, 8, x FOR PEER REVIEW 2 of 29 Aerospace 2021, 8, 30 2 of 27 performed on-wing or during induction inspection and subsequent module and piece- inspection where the parts are exposed. While borescope inspection is an essential first part inspection where the parts are exposed. While borescope inspection is an essential mean of inspection to determine the health and condition of the parts and subsequently first mean of inspection to determine the health and condition of the parts and subse- makequently the make decision the decision as to whether as to whether further disassemblyfurther disassembly and detailed and detailed inspection inspection is required, is itrequired, also has it limitations also has limitations of relatively of relatively low image low quality image and quality poor and lighting poor lighting conditions condi- inside thetions engine inside [ 8the]. Furthermore, engine [8]. Furthermore, there is limited there accessibility,is limited accessibility, which creates which the creates need the to use differentneed to use borescope different tips,borescope which tips, in turnwhich leads in tu torn leads a high to variationa high variation of images of images [9]. Due[9]. to theDue challenging to the challenging borescope borescope inspection inspection environment, environment, this this research research focuses focuses on on piece-part piece- inspections,part inspections, where where these these conditions conditions can can be betterbe better controlled. controlled. If successful,If successful, the the proposed pro- methodposed method could becould refined be refined and mightand might then then be transferablebe transferable to to higher higher levels levels of of inspection,inspec- namely,tion, namely, module module and borescope and borescope inspection. inspection. FigureFigure 1. 1.Inspection Inspection workflowworkflow and and hierar hierarchychy of of levels levels of of inspection. inspection. DuringDuring allall visual inspections, a a skilled skilled technician technician obtains obtains an an appropriate appropriate view view of the of the partpart and and evaluatesevaluates the condition by by searching searching for for any any damages. damages. When When a defect a defect is detected, is detected, thethe inspector inspector hashas toto make a a decision decision whether whether or or not not it itis isacceptable, acceptable, i.e., i.e., check check if it if is it within is within engineengine manualmanual limits. This This dec decisionision is is based based on on the the inspector’s inspector’s experience experience and and to some to some extentextent onon thethe riskrisk appetite. Some Some inspectors inspectors tend tend to to take take a more a more risk risk adverse adverse stand, stand, which which maymay leadlead toto aa costlycostly tear down down of of the the engine engine or or scrapping scrapping of ofairworthy airworthy parts. parts. Both Both tasks, tasks, defectdefect detectiondetection and evaluation, are are time time cons consuminguming and and tedious tedious processes processes that that are areprone prone toto human human errorerror causedcaused by by fatigue fatigue or or complacency. complacency. This This entails entails the the risk risk of missing of missing a critical a critical defectdefect duringduring inspection. Thus, Thus, there there is is a aneed need to to overcome overcome those those risks risks and and support support the the humanhuman operator,operator, whilewhile improvingimproving the inspectioninspection quality and and repeatability, repeatability, and and decreas- decreasing theing inspection the inspection times. times. Ultimately, Ultimately, this hasthis the has potential the potential to improve to improve aviation aviation safety safety through reductionthrough reduction of accidents of accidents in which in defects which were defec missedts were duringmissed theduring inspection the inspection task [10 task,11]. [10,11].In this research, the focus is on defects present on the leading and trailing edges of compressorIn this blades.research, These the focus blades is areon defects located pr asesent per Figureon the2 leading and highlighted and trailing in edges yellow. of An isolatedcompressor blade blades. is presented These blades next toare it. located as per Figure 2 and highlighted in yellow. An isolated blade is presented next to it. The most common edge defects are dents, nicks and tears. An overview of the defect types and their characteristics together with a sample photograph is shown in Figure3 below. It should be noted that the sample images show severe defects. This is for demonstration purposes only, to highlight the difference between the different defect types. The test dataset also contained blade images with smaller defects that are more difficult to detect. Detecting those defect types is important as they can lead to fatigue cracks [13] resulting in material separation and breakage of the entire blade under centrifugal load [14], which has the potential to cause severe