Helicopter Maintenance Research Articles

Development of a neural network approach for risk management in helicopter technical condition diagnostics

The object of the study is the quality of helicopter maintenance based on digital diagnostic tools. To ensure the required quality, quantitative risk assessment models for the in-depth and express diagnostics system of helicopter gas turbine engines in a neural network environment are proposed. The assessment of diagnostic efficiency is based on the analysis of probable control risks by standard deviations, which distinguishes the proposed approach from the traditional one. Two diagnostic modes are considered: rapid diagnostics exemplified by vibration diagnostics, and in-depth diagnostics, including both vibration diagnostics and pyrometric control. These diagnostic methods make it possible to implement a remote monitoring system at aircraft repair facilities, which significantly reduces maintenance labor intensity. As a result, it was found that control risks depend not only on the metrological level of measuring instruments but also on a combination of the statistical nature of control agents in their system composition according to the following characteristics: statistical parameters of the controlled indicator, distribution laws, and values of uncertainty of measuring instruments, as well as the uncertainty of control standards (tolerances). In the modeling process, risks were assessed as a function of the ratio of uncertainties of measuring instruments to the uncertainty of the controlled parameter, with varying values of the standard (tolerance). This approach will allow, in practice, the creation of a more effective system for monitoring and collecting statistical information on the operational reliability of the Mi-8 helicopter engine, where the quality of control is predicted to a greater extent based on the metrological indicators of the measuring instruments and methods

Study on Vibration Adjustment Mechanism of S-76D Helicopter Rotor System Based on HUMS System

In recent years, helicopter maintenance technology has been developing rapidly and is transitioning from time-based periodic maintenance to condition-based maintenance. Helicopter Health and Usage Monitoring System (HUMS system) plays an important role in this process. The excitation forces originating from the helicopter rotor system are the primary cause of airframe vibration, and the HUMS system monitors the main rotor balance and trajectory data during each flight and provides an adjustment solution and predicts the vibration level in case of overruns. This paper summarizes the vibration measurement, cause analysis and vibration adjustment methods by studying the vibration adjustment mechanism of the S-76D helicopter rotor system, and provides solution for the same type of vibration problems of the helicopter.

Differences between Experts and Novices in the Use of Aircraft Maintenance Documentation: Evidence from Eye Tracking

Maintenance is a highly procedural activity requiring motor and cognitive engagement. The aim of this experimental study was to examine how expertise affects maintenance tasks, in particular, the use of procedural documents. A total of 22 aircraft maintenance technicians were divided into two groups according to their level of expertise. Helicopter maintenance was evaluated in a real work environment, using an eye tracker, a fixed camera, and NASA-TLX to measure workload. Both groups reported a high mental load. Novices showed elevated levels of effort and mental demand. Experts were faster at all levels of the task and spent less time consulting maintenance documentation. The acquisition of procedural information was greater at the start of the task, where the gap between groups was more pronounced. This may be related to the overall planning of the task, in addition, the task was atomized, with frequent back-and-forth between execution and information intake, for all participants. Novices had a longer document consultation duration, spread over a greater number of consultations, but did not have a higher average consultation time. The results indicate a higher mental load for novices, potentially linked to an increased atomization of the task, as shown by the frequency of consultations.

Influence of geometric constraints on aircraft design

The paper considers the requirements to helicopter operating conditions, forming geometrical constraints at the design stages and their influence on the geometrical appearance of the helicopter as a whole, structural design and layout of individual components and assemblies of helicopters. The methodology of forming the system of geometrical constraints is based on the generalised requirements to ensure the operational and technical characteristics of the helicopter: ensuring the basing and production of take-off and landing operations on marine vessels, ensuring transportability, ease of access to the cockpit, ease of access to the units during maintenance, reducing the labour intensity of individual helicopter maintenance operations.

Havacılık Sektöründe Zaman Baskısının Teknostrese Etkisi: Uçak Bakım Teknisyenleri Üzerine Bir Araştırma (The Effect of Time Pressure on Technostress in Aviation Industry: Research on Aircraft Maintenance Technicians)

Purpose – The purpose of this study is to examine the effect of time pressure on technostress in aviation industry and whether the time pressure and technostress perception of aircraft maintenance technicians differ according to demographic characteristics. Design/methodology/approach – The sampling of the study consists of 177 aircraft and helicopter maintenance technicians working in the public sector in Malatya province. Questionnaire method was used to collect data in the study. The data obtained from the questionnaire were subjected to scale validity and reliability, confirmatory factor analysis, correlation, simple linear regression, T-test and ANOVA analysis in SPSS 21 and AMOS 24 package programs. Findings – According to the research results, it was seen that time pressure positively affects the technostress in the aviation industry. It was observed that the perception of time pressure of maintenance technicians according to the age group and education level, and the perception of technostress according to the working time and education level differ. However, according to the marital status and job title, it was observed that there is no significant difference in maintenance technicians' time pressure and technostress perception. Discussion – In this study carried out in the aviation industry, it was determined that time pressure and technostress are positively related and time pressure is a determinant of the change in the perception of technostress of maintenance technicians. According to demographic characteristics, technicians' time pressure and technostress perception differ. It is possible to say that time pressure and technostress can cause errors caused by the human factor in the aircraft maintenance industry. The study is thought to make a contribution to the literature related to the aviation, aircraft maintenance and flight safety.

Research on the Impact of HUMS Technology on Civil Helicopter Maintenance Tasks

Research on the Impact of HUMS Technology on Civil Helicopter Maintenance Tasks

Automatic regime detection for Rotor Track and Balance using vibration only sensor data

ABSTRACTRotor Track and Balance (RTB) is an important part of regular helicopter maintenance. The ability to perform this service assessment during normal operations, rather than with a series of explicit RTB flights, would greatly reduce the time the vehicle is non-operational and the maintenance costs associated with these flights and adjustments. This paper presents a novel methodology for identifying the RTB-related flight regimes, using a minimal number of vibration signals and comparing these to repeatable and stable characteristic vibration profiles. The technique is stable, with an 81% success in correct identification of the flight regime, when applied to a whole flight with a number of unknown regime events. The method can be run in real time, making it an effective way of identifying periods of flight that are suitable for RTB measurements. A new technique for visually representing any real-time flight signal, such as vibration, is also presented.

Limitations of Helicopter Training within 14 CFR Part 147

According to the 2018 Federal Aviation Administration (FAA) aircraft registration database, 10,500 of the 210,000 general aviation aircraft are helicopters (FAA, 2018). While making up only 5% of aircraft, helicopter are found in niche markets that are highly specialized such as aerial tourism, news reporting, rescue operations, and medical transport. In order to maintain airworthiness, these aircraft are inspected and maintained by Airframe and Powerplant (A&P) mechanics. Due to an increasing number of retirements, there is a need to train new mechanics. In order to earn an A&P certificate, a student must undergo 1,900 hour of training. The current curriculum used to train prospective mechanics is monitored and regulated by the Federal Aviation Administration under 14 CFR Part 147-Aviation Maintenance Technician Schools. However, within Part 147, helicopter training is only taught at a level 1 which requires only lecture instruction with no hands-on requirements. Furthermore, of the 1,900 hours of training required, only 1 hour is required for helicopter specific training. This lack of training creates a possible gap in knowledge. When the maintenance on helicopters is performed to subpar levels there are catastrophic results. To demonstrate this, case studies of three specific accidents were used. All three accidents were caused by improper helicopter maintenance and resulted in fatalities. Major helicopter companies have attempted to mitigate this gap by creating additional training for A&P technicians after graduation from a Part 147 school. However, this additional training is costly and requires more time investment from students before they can enter the workforce.

Interactive visualizations for decision support: Application of Rasmussen's abstraction-aggregation hierarchy

Data visualization has of late received an enormous amount of attention from both researchers and practitioners. Even the popular press often includes impressive visualizations of various data sets. Interactive visualizations frequently include data visualizations, but they differ in that users employ the visualizations to make inferences, reach conclusions, and make decisions that result in changed and/or new visualizations. Data visualizations emphasize “what is,” but interactive visualizations address “what if.” In this way, interactive visualizations are often intended for decision support. This article addresses the design of interactive visualizations for decision support. An overall methodology is presented; central to this methodology is Jens Rasmussen's abstraction-aggregation hierarchy. The results of two applications and evaluations of the outcomes of using this methodology are discussed. The first application focused on interactive visualizations for helicopter maintenance. The second application addressed “enterprise diagnostics” in the automobile industry where subjects were asked to diagnose the cause of failed automobile brands. The results of these two applications are used to assess the efficacy of the proposed methodology.

Estudio de costos de mantenimiento en helicópteros militares mediante la aplicación del costeo abc

<p>Bajo información de la Fuerza Aérea Colombiana e investigaciones del mantenimiento en helicópteros, se evidencian mecanismos de control y clasificación de actividades. Esto se desarrolla al incorporar una metodología que permite evaluar, medir y simplificar la manera de manejar los costos de las operaciones realizadas en el mantenimiento de aeronaves. Se enfoca en helicópteros MIL MI 17, para tener claridad sobre los procesos y las actividades llevadas a cabo.</p>

Information Acquisition of Maintenance, Repair and Overhaul/Operations System for Helicopters

The helicopter Maintenance, Repair and Overhaul/Operations (MRO) system enables the best sharing of the maintenance resources and maintenance ability in a wide area, so as to promote the specialization of the helicopter maintenance organizations. Information acquisition is an important and difficult part of the helicopter MRO system. This paper systematically analyzes the condition monitoring methods which are used to monitor the rotational speed, temperature, pressure, vibration and flight parameter in different parts of a helicopter, and then it puts forward some improved ways for information acquisition. Considering the helicopter’s features, the process of information acquisition is illustrated. In addition, this paper presents the basic requirements of data sampling, and it also shows a detailed discussion on data format and data transmission in the helicopter MRO system. At the end of the paper, a system mode and architecture of helicopter MRO system are proposed.

Project scheduling under uncertainty using fuzzy modelling and solving techniques

In the real world, projects are subject to numerous uncertainties at different levels of planning. Fuzzy project scheduling is one of the approaches that deal with uncertainties in project scheduling problem. In this paper, we provide a new technique that keeps uncertainty at all steps of the modelling and solving procedure by considering a fuzzy modelling of the workload inspired from the fuzzy/possibilistic approach. Based on this modelling, two project scheduling techniques, Resource Constrained Scheduling and Resource Leveling, are considered and generalized to handle fuzzy parameters. We refer to these problems as the Fuzzy Resource Constrained Project Scheduling Problem (FRCPSP) and the Fuzzy Resource Leveling Problem (FRLP). A Greedy Algorithm and a Genetic Algorithm are provided to solve FRCPSP and FRLP respectively, and are applied to civil helicopter maintenance within the framework of a French industrial project called Helimaintenance.

Fuzzy uncertainty modelling for project planning: application to helicopter maintenance

Maintenance is an activity of growing interest, especially for critical systems. In particular, aircraft maintenance costs are becoming an important issue in the aeronautical industry. Managing an aircraft maintenance centre is a complex activity. One of the difficulties comes from the numerous uncertainties that affect the activity and disturb the plans in the short and medium term. Based on a helicopter maintenance planning and scheduling problem, we study in this paper the integration of uncertainties into tactical and operational multi-resource, multi-project planning (respectively Rough Cut Capacity Planning and the Resource Constraint Project Scheduling Problem). Our main contributions are in modelling the periodic workload on a tactical level considering uncertainties in macro-task work content, and modelling the continuous workload on the operational level considering uncertainties in task duration. We model uncertainties using a fuzzy/possibilistic approach instead of a stochastic approach since very limited data are available. We refer to the problems as the Fuzzy Rough Cut Capacity Problem (FRCCP) and the Fuzzy Resource Constraint Project Scheduling Problem (RCPSP). We apply our models to helicopter maintenance activity within the frame of the Helimaintenance project, an industrial project approved by the French Aerospace Valley cluster that aims at building a centre for civil helicopter maintenance.

How to take into account general and contextual knowledge for interactive aiding design: Towards the coupling of CSP and CBR approaches

The goal of this paper is to show how it is possible to support design decisions with two different tools relying on two kinds of knowledge: case-based reasoning operating with contextual knowledge embodied in past cases and constraint filtering that operates with general knowledge formalized using constraints. Our goals are, firstly to make an overview of existing works that analyses the various ways to associate these two kinds of aiding tools essentially in a sequential way. Secondly, we propose an approach that allows us to use them simultaneously in order to assist design decisions with these two kinds of knowledge. The paper is organized as follows. In the first section, we define the goal of the paper and recall the background of case-based reasoning and constraint filtering. In the second section, the industrial problem which led us to consider these two kinds of knowledge is presented. In the third section, an overview of the various possibilities of using these two aiding decision tools in a sequential way is drawn up. In the fourth section, we propose an approach that allows us to use both aiding decision tools in a simultaneous and iterative way according to the availability of knowledge. An example dealing with helicopter maintenance illustrates our proposals.

LOW COST DATABASE DESIGN FOR 3D VIEWING AND ACCESS

Using the popular desktop software, Microsoft Access and Visual Basic coding, a database inventory was designed for a helicopter maintenance plant. This design aims to provide the managers and maintenance engineers a reliable tool to view the inventory list in its shops. This design model uses real time data from the shop floor and the data provided in the Blackhawk Technical Manual for Army operations. This project provides integration between Pro/ENGINEER and Microsoft Access. Microsoft Access is a desktop database application which is inexpensive and available readily. PTC© Pro/ENGINEER is interactive, powerful parametric modeling software for 3D viewing and modeling. In effect, this design aims to provide the managers with a better understanding and quick access to inventory list of the shop floor and as such better utilization of all the available resources.

Helicopter maintenance error analysis: Beyond the third order of the HFACS-ME

In this paper a statistical analysis of a sample of 58 helicopter maintenance-induced safety occurrences is conducted to study helicopter accidents and incidents’ survivability and the severity distribution of such occurrences. Analysis is also carried out to identify helicopter main and sub-systems mostly exposed to maintenance errors and to determine various types of such errors. Expected inherent relations between rotorcraft components affected and types of associated maintenance errors are investigated. Human factors-based triggers of these accidents and severe incidents are explored. The concept of Specific Failures (SFs) that immediately precede each of such occurrences is introduced for more detailed representation of the last breached individual and organizational safety barriers. Root causes of these safety occurrences were then sought utilizing the Human Factors Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy with a refined focus on its third order categories’ list. The rotorcraft characteristics influencing individuals and organizational behaviours within Maintenance, Repair and Overhaul organizations (MROs) are discussed in the light of the root cause investigation results. Relevance to industry The study of human reliability within helicopter maintenance industry is waited to emphasise the understanding of causes and propagation mechanisms of maintainers' errors and their consequences on the overall aviation safety. Previous works often investigated maintenance errors and their roles in promoting aviation accidents of fixed-wing aircraft; this research is investigating the case of rotorcraft.

Test duration in choice of helicopter maintenance policy

Abstract In the course of a review of the maintenance policy for a certain type of helicopter, it was found necessary to determine whether the frequency of one of the scheduled tests could be reduced without a shorter mean time between failures (MTBF). A sequential-testing procedure was worked out for an experiment in which hypotheses on the ratio of the respective MTBFs under the new and present maintenance policies are to be verified. In it, two groups of helicopters, subjected to the respective maintenance systems, are observed (Manipulation of two groups in parallel neutralizes the effect of uncontrolled factors, such as variation of the helicopters' operational load and the maintenance-quality level). It is assumed that the failure rates are constant. A decision-making algorithm, and a matlab program, were constructed. The program yielded the decision parameters, densities and mean test duration up to the positive/negative decision in dependence on the actual MTBF ratio, the permissible level of the latter, and the given error probability levels. Prediction of the test duration, together with the operating characteristic, permits more rational planning of the experiment, hence of the maintenance policy.

The ANNIGMA-wrapper approach to fast feature selection for neural nets

This paper presents a novel feature selection approach for backpropagation neural networks (NNs). Previously, a feature selection technique known as the wrapper model was shown effective for decision trees induction. However, it is prohibitively expensive when applied to real-world neural net training characterized by large volumes of data and many feature choices. Our approach incorporates a weight analysis-based heuristic called artificial neural net input gain measurement approximation (ANNIGMA) to direct the search in the wrapper model and allows effective feature selection feasible for neural net applications. Experimental results on standard datasets show that this approach can efficiently reduce the number of features while maintaining or even improving the accuracy. We also report two successful applications of our approach in the helicopter maintenance applications.

A practical approach for the indirect prediction of structural fatigue from measured flight parameters

The perceived benefits of permanent usage monitoring equipment in helicopters include savings in the cost of helicopter maintenance and a favourable impact on safety and fleet management. Unlike indirect fatigue monitoring, direct load monitoring relies on a large number of sensors which requires high operational and maintenance costs. In this paper, a learning network has been developed, and during training sessions allowed to learn how to predict fatigue damage indirectly from flight parameters. Each training example consists of instantaneous fatigue damage induced during a small time step, and flight parameters measured during the time step. The instantaneous damage values are evaluated through a new approach called the progressive damage model. By considering the laws of aerodynamics and dynamics, the network combines the flight parameters in such a way that the resulting features can be mapped into fatigue. About 10.5 flying hours of data were used to train the network. After training, the network was blind tested using flight parameters from 5.8 flying hours. The network was found to predict the fatigue damage of two rotating components indirectly from the flight parameters with accuracy better than the accuracy of a strain gauge system with 5 per cent measurement error.

Analog neural network-based helicopter gearbox health monitoring system.

The development of a reliable helicopter gearbox health monitoring system (HMS) has been the subject of considerable research over the past 15 years. The deployment of such a system could lead to a significant saving in lives and vehicles as well as dramatically reduce the cost of helicopter maintenance. Recent research results indicate that a neural network-based system could provide a viable solution to the problem. This paper presents two neural network-based realizations of an HMS system. A hybrid (digital/analog) neural system is proposed as an extremely accurate off-line monitoring tool used to reduce helicopter gearbox maintenance costs. In addition, an all analog neural network is proposed as a real-time helicopter gearbox fault monitor that can exploit the ability of an analog neural network to directly compute the discrete Fourier transform (DFT) as a sum of weighted samples. Hardware performance results are obtained using the Integrated Neural Computing Architecture (INCA/1) analog neural network platform that was designed and developed at The Charles Stark Draper Laboratory. The results indicate that it is possible to achieve a 100% fault detection rate with 0% false alarm rate by performing a DFT directly on the first layer of INCA/1 followed by a small-size two-layer feed-forward neural network and a simple post-processing majority voting stage.