Exploring Prognostic and Diagnostic Techniques for Jet Engine Health Monitoring: A Review of Degradation Mechanisms and Advanced Prediction Strategies

Maintenance is crucial for aircraft engines because of the demanding conditions to which they are exposed during operation. A proper maintenance plan is essential for ensuring safe flights and prolonging the life of the engines. It also plays a major role in managing costs for aeronautical companies. Various forms of degradation can affect different engine components. To optimize cost management, modern maintenance plans utilize diagnostic and prognostic techniques, such as Engine Health Monitoring (EHM), which assesses the health of the engine based on monitored parameters. In recent years, various EHM systems have been developed utilizing computational techniques. These algorithms are often enhanced by utilizing data reduction and noise filtering tools, which help to minimize computational time and efforts, and to improve performance by reducing noise from sensor data. This paper discusses the various mechanisms that lead to the degradation of aircraft engine components and the impact on engine performance. Additionally, it provides an overview of the most commonly used data reduction and diagnostic and prognostic techniques

A hybrid framework for remaining useful life estimation of turbomachine rotor blades

Hybrid methods for prognosis of mechanical components have the potential of improving remaining useful life (RUL) estimations. Hybrid methods combine physics-based and data-driven methods to diagnose faults and predict when failures will occur. In this work, we propose a hybrid framework that estimates the RUL from routine maintenance inspection data and condition monitoring data. This hybrid framework is applied to turbomachine rotor blades. Blade tip timing (BTT) measurements are used for condition monitoring. The least squares spectral analysis (LSSA) method is used to find the natural frequency. The natural frequency is a function of the blade's health state and is used to infer the crack length in the blade’s root. To accommodate for artificial rotational stiffening, an interpolation model of the blade's Campbell diagram, generated from a finite element model, is used. In the proposed methodology, we use an ensemble physics-based model that serves as a prior probability density function for a Gaussian process regression (GPR) model. The predictive distribution of the GPR model is constructed by conditioning the physics-based model on the observed data from routine maintenance inspections. We also compare this hybrid diagnosis model to the physics-based technique and other data-driven methods. The hybrid diagnosis model outperformed the physics-based method and data-driven methods. The unscented Kalman filter (UKF) is used to estimate and forecast the evolution of the crack length over time. Paris’ law coefficients are used as hidden latent variables in a hybrid degradation model. In the diagnosis and prognosis phases, we use the unscented transform to efficiently approximate the probability density functions of the crack length and the crack growth law parameters. Finally, we compare the applied hybrid model to a purely physics-based model and show that the hybrid model outperforms the physics-based model in predicting the length of a crack. We demonstrate that the hybrid model increases the accuracy and precision of RUL prediction from physics-based models with 60% on average.https://www.elsevier.com/locate/ymssp2023-01-17hj2023Mechanical and Aeronautical Engineerin

An improved key-phase-free blade tip-timing technique for nonstationary test conditions and its application on large-scale centrifugal compressor blades

7partially_openopenHe, Changbo; Antoni, Jerome; Daga, Alessandro Paolo; Li, Hongkun; Chu, Ning; Lu, Siliang; Li, ZhixiongHe, Changbo; Antoni, Jerome; Daga, Alessandro Paolo; Li, Hongkun; Chu, Ning; Lu, Siliang; Li, Zhixion

Accuracy Characterization of a MEMS Accelerometer for Vibration Monitoring in a Rotating Framework

Active and passive vibration control systems are of paramount importance in many engineering applications. If an external load excites a structure’s resonance and the damping is too low, detrimental events, such as crack initiation, growth and, in the worst case, fatigue failure, can be entailed. Damping systems can be commonly found in applications such as industrial machines, vehicles, buildings, turbomachinery blades, and so forth. Active control systems usually achieve higher damping effectiveness than passive ones, but they need a sensor to detect the working conditions that require damping system activation. Recently, the development of such systems in rotating structures has received considerable interest among designers. As a result, the development of vibration monitoring equipment in rotating structures is also a topic of particular interest. In this respect, a reliable, inexpensive and wireless monitoring system is of utmost importance. Typically, optical systems are used to measure vibrations, but they are expensive and require rather complex processing algorithms. In this paper, a wireless system based on a commercial MEMS accelerometer is developed for rotating blade vibration monitoring. The proposed system measurement accuracy was assessed by means of comparison with a reference wired measurement setup based on a mini integrated circuit piezoelectric (ICP) accelerometer adapted for data acquisition in a rotating frame. Both the accelerometers were mounted on the tip of the blade and, in order to test the structure under different conditions, the first four blade resonances were excited by means of piezoelectric actuators, embedded in a novel experimental setup. The frequency and amplitude of acceleration, simultaneously measured by the reference and MEMS sensors, were compared with each other in order to investigate the viability and accuracy of the proposed wireless monitoring system. The rotor angular speed was varied from 0 to 300 rpm, and the data acquisitions were repeated six times for each considered condition. The outcomes reveal that the wireless measurement system may be successfully used for vibration monitoring in rotating blades

Blade faults diagnosis in multi stage rotor system by means of wavelet analysis

Blade fault is one of the most causes of gas turbine failures. Vibration spectral analysis and blade pass frequency (BPF) monitoring are the most widely used methods for blade fault diagnosis. These methods however have limitations in the detection of incipient faults due to weak and/or transient signals, as well as inability to diagnose the blade faults types. This study investigates the applications of wavelet analysis in blade fault diagnosis of a multi stage rotor system, as an extension of previous works which involved a single stage only. Results showed that conventional wavelet analysis has limitations in segregating the BPFs and locating the faults. An improvement in Morlet wavelet was made to achieve high resolution in both time and frequency domains. Two new wavelets for high time-frequency resolutions were formulated and added to the standard MATLAB Wavelet Toolbox. The optimal parameters for the high frequency resolution wavelet were found at the centre of frequency, ????=4 and bandwidth, ??=0.5. For high time resolution wavelet, the optimal parameters were ????=4 and ??=10. A novel algorithm was formulated by combining the two newly developed wavelets. A variety of blade faults including blade creep rubbing, blade tip rubbing, stage rubbing, blade loss of part and blade twisting were tested and their vibration responses measured in a laboratory test facility. The proposed method showed potential in segregating closely spaced BPFs components and identifying the faulty stage and fault location. The method demonstrated the ability in differentiating various blade faults based on a unique pattern (“fingerprint”) of each fault produced by the newly added wavelet. The formulated algorithm was demonstrated to be suitable in monitoring rotor systems with multiple blade stages

12th International Conference on Vibrations in Rotating Machinery

Since 1976, the Vibrations in Rotating Machinery conferences have successfully brought industry and academia together to advance state-of-the-art research in dynamics of rotating machinery. 12th International Conference on Vibrations in Rotating Machinery contains contributions presented at the 12th edition of the conference, from industrial and academic experts from different countries. The book discusses the challenges in rotor-dynamics, rub, whirl, instability and more. The topics addressed include: - Active, smart vibration control - Rotor balancing, dynamics, and smart rotors - Bearings and seals - Noise vibration and harshness - Active and passive damping - Applications: wind turbines, steam turbines, gas turbines, compressors - Joints and couplings - Challenging performance boundaries of rotating machines - High power density machines - Electrical machines for aerospace - Management of extreme events - Active machines - Electric supercharging - Blades and bladed assemblies (forced response, flutter, mistuning) - Fault detection and condition monitoring - Rub, whirl and instability - Torsional vibration Providing the latest research and useful guidance, 12th International Conference on Vibrations in Rotating Machinery aims at those from industry or academia that are involved in transport, power, process, medical engineering, manufacturing or construction

A review on failure modes of wind turbine components

To meet the increasing energy demand, renewable energy is considered the best option. Its patronage is being encouraged by both the research and industrial community. The main driving force for most renewable systems is solar energy. It is abundant and pollutant free compared to fossil products. Wind energy is also considered an abundant medium of energy generation and often goes hand in hand with solar energy. The last few decades have seen a sudden surge in wind energy compared to solar energy due to most wind energy systems being cost effective compared to solar energy. Wind turbines are often categorised as large or small depending on their application and energy generation output. Sustainable materials for construction of different parts of wind turbines are being encouraged to lower the cost of the system. The turbine blades and generators perform crucial roles in the overall operation of the turbines; hence, their material composition is very critical. Today, most turbine blades are made up of natural fiber‐reinforced polymer (NFRP) as well as glass fiber‐reinforced polymer (GFRP). Others are also made from wood and some metallic materials. Each of the materials introduced has specific characteristics that affect the system’s efficiency. This investigation explores the influence of these materials on turbine efficiency. Observations have shown that composites reinforced with nanomaterials have excellent mechanical characteristics. Carbon nanotubes have unique characteristics that may make them valuable in wind turbine blades in the future. It is possible to strengthen carbon nanotubes with various kinds of resins to get a variety of different characteristics. Similarly, the end‐of‐life treatment methods for composite materials is also presented

12th International Conference on Vibrations in Rotating Machinery

Since 1976, the Vibrations in Rotating Machinery conferences have successfully brought industry and academia together to advance state-of-the-art research in dynamics of rotating machinery. 12th International Conference on Vibrations in Rotating Machinery contains contributions presented at the 12th edition of the conference, from industrial and academic experts from different countries. The book discusses the challenges in rotor-dynamics, rub, whirl, instability and more. The topics addressed include: - Active, smart vibration control - Rotor balancing, dynamics, and smart rotors - Bearings and seals - Noise vibration and harshness - Active and passive damping - Applications: wind turbines, steam turbines, gas turbines, compressors - Joints and couplings - Challenging performance boundaries of rotating machines - High power density machines - Electrical machines for aerospace - Management of extreme events - Active machines - Electric supercharging - Blades and bladed assemblies (forced response, flutter, mistuning) - Fault detection and condition monitoring - Rub, whirl and instability - Torsional vibration Providing the latest research and useful guidance, 12th International Conference on Vibrations in Rotating Machinery aims at those from industry or academia that are involved in transport, power, process, medical engineering, manufacturing or construction