Fatigue Life Monitoring Research Articles

Digital image correlation approach for low-cycle fatigue life monitoring of 13HMF power engineering steel

In this paper, strain evolution of 13HMF power engineering steel was analysed during force-controlled low cycle fatigue (LCF). The material performance under cyclic loading was monitored by using Digital Image Correlation (DIC) technique for different values of stress amplitude exceeding the yield strength of the material significantly. Data collected from DIC was compared to the extensometer ones to confirm the effectiveness of the proposed approach. Finally, the cloud data reflecting the fatigue performance of 13HMF was generated in the form of strain-stress amplitude - service life distribution map.

Analysis of PZT Piezoelectric Sensors in Buckling Mode for Dynamic Strain Measurement

Fatigue Life Monitoring is crucial to ensure engineering structures' safety and durability. This paper introduces an innovative approach for fatigue life monitoring using a soft PZT (Lead Zirconate Titanate) piezoelectric sensor operating in buckling mode to measure applied cyclic strains. A particular emphasis is on the utilization of a 3D-printed 'Extension' that serves as the platform upon which the PZT sensor is installed and operates in buckling mode while subjected to cyclic strains. An analytical framework is presented, which encompasses the development of the governing equations to establish a direct relationship between dynamic strain values and the sensor's output. Critical strain attributes, such as amplitude and occurrence strain rate also taken into account. The analytical solutions are validated by a series of experimental tests under various dynamic loading conditions. The PZT sensor, when integrated with the 3D-printed extension and operated in buckling mode, exhibits high sensitivity and functions as a passive dynamic strain measurement sensor, with high potential to be used as self-powered sensor nodes for fatigue life monitoring of engineering structures.

Digital twin‐driven online intelligent assessment of wind turbine gearbox

AbstractRemaining useful fatigue life monitoring of wind turbine drivetrains is important. However, the implementation of real‐time monitoring often faces efficiency and accuracy challenges. In order to resolve this, this paper proposes a vibration‐based damage monitoring digital twin (VBDM‐DT) that enables the online intelligent evaluation of wind turbine gearboxes, using gear tooth surface durability as an example fatigue mode. The VBDM‐DT integrates a random wind load model, a high‐fidelity dynamics model, and a fatigue damage model. The random wind load model takes the wind speed from the supervisory control and data acquisition (SCADA) as input to estimate the input torque of the drivetrain in real time. Simultaneously, VBDM‐DT uses the vibration signals from the condition monitoring system (CMS) to intelligently calibrate the dynamics model, allowing it to be continuously adjusted and optimized in response to actual vibrations. The fatigue damage model takes the real‐time dynamic loads estimated by the high‐fidelity dynamic model as input to achieve real‐time fatigue damage monitoring of key components in the wind turbine gearbox. Applying the VBDM‐DT model to a 2 MW wind turbine gearbox, the results indicate that the model provides satisfactory accuracy in estimating input loads and good adaptability in intelligent calibration of the dynamic model. Based on this model, the fatigue life estimation for gears and bearings is more credible and reliable.

Farm‐wide interface fatigue loads estimation: A data‐driven approach based on accelerometers

AbstractFatigue has become a major consideration factor in modern offshore wind farms as optimized design codes, and a lack of lifetime reserve has made continuous fatigue life monitoring become an operational concern. In this contribution, we discuss a data‐driven methodology for farm‐wide tower‐transition piece fatigue load estimation. We specifically debate the employment of this methodology in a real‐world farm‐wide setting and the implications of continuous monitoring. With reliable nacelle‐installed accelerometer data at all locations, along with the customary 10‐min supervisory control and data acquisition (SCADA) statistics and three strain gauge‐instrumented 'fleet‐leaders', we discuss the value of two distinct approaches: use of either fleet‐leader or population‐based data for training a physics‐guided neural network model with a built‐in conservative bias, with the latter taking precedence. In the context of continuous monitoring, we touch on the importance of data imputation, working under the assumption that if data are missing, then its fatigue loads should be modeled as under idling. With this knowledge at hand, we analyzed the errors of the trained model over a period of 9 months, with monthly accumulated errors always kept below . A particular focus was given to performance under high loads, where higher errors were found. The cause for this error was identified as being inherent to the use of 10‐min statistics, but mitigation strategies have been identified. Finally, the farm‐wide results are presented on fatigue load estimation, which allowed to identify outliers, whose behavior we correlated with the operational conditions. Finally, the continuous data‐driven, population‐based approach here presented can serve as a springboard for further lifetime‐based decision‐making.

A fatigue crack quantification model for metallic structure based on strain monitoring data

Obtaining the real-time fatigue crack length of a metallic structure is the prerequisite of the fatigue life monitoring and residual life estimation for an aircraft. This paper proposed a metallic structure's fatigue crack prediction model using strain monitoring data based on deep learning method. A cycle consistent adversarial network was developed to map the strain monitoring data from experimental measurement with those from finite element modeling. A crack size classification model and a crack length quantification model were proposed to classify the crack size range and identify the exact crack length, respectively. The proposed model was applied to predict the fatigue crack growth in centeral hole metallic plates subjected to random loading spectrum. The results showed that the prediction is effective and accurate.

Fatigue Life Measuring System Using Fiber Optic Sensors for CFRP Pantograph Upper Arm

A life assessment method based on FBG sensors is investigated for CFRP upper frames that are subjected to cyclic loading and are prone to fatigue damage and shortened fatigue life. Based on the research of optical fiber sensing technology, a measuring system for the fatigue life monitoring of the upper arm on the carbon fiber composite pantograph is developed and evaluated in this paper. The sensing principle of the optical fiber grating sensor and the construction and installation of the sensing network are described in detail. A carbon fiber composite upper frame fatigue monitoring platform is designed for systematic testing and life is assessed through measured point strain average and strain amplitude combined with a fatigue cumulative damage model. The effectiveness of the designed system is verified by analyzing and comparing the fatigue simulation results of the carbon fiber composite upper arm with the measured data of the sensor installed on the fatigue life test platform of the upper arm. Experimental results show that the system designed by optical fiber sensing technology is capable of accurately detecting the fatigue life of the upper arm of the carbon fiber composite, which can be used for real-time detection of the fatigue life of the upper arm by analyzing the characteristic parameters of the upper arm of the carbon fiber composite.

Effect of Polymer Matrix on Inelastic Strain Development in PI- and PEI-Based Composites Reinforced with Short Carbon Fibers under Low-Cyclic Fatigue

Since the inelastic strain development plays an important role in the low-cycle fatigue (LCF) of High-Performance Polymers (HPPs), the goal of the research was to study the effect of an amorphous polymer matrix type on the resistance to cyclic loading for both polyimide (PI)- and polyetherimide (PEI)-based composites, identically loaded with short carbon fibers (SCFs) of various lengths, in the LCF mode. The fracture of the PI and PEI, as well as their particulate composites loaded with SCFs at an aspect ratio (AR) of 10, occurred with a significant role played by cyclic creep processes. Unlike PEI, PI was less prone to the development of creep processes, probably because of the greater rigidity of the polymer molecules. This increased the stage duration of the accumulation of scattered damage in the PI-based composites loaded with SCFs at AR = 20 and AR = 200, causing their greater cyclic durability. In the case of SCFs 2000 µm long, the length of the SCFs was comparable to the specimen thickness, causing the formation of a spatial framework of unattached SCFs at AR = 200. The higher rigidity of the PI polymer matrix provided more effective resistance to the accumulation of scattered damage with the simultaneously higher fatigue creep resistance. Under such conditions, the adhesion factor exerted a lesser effect. As shown, the fatigue life of the composites was determined both by the chemical structure of the polymer matrix and the offset yield stresses. The essential role of the cyclic damage accumulation in both neat PI and PEI, as well as their composites reinforced with SCFs, was confirmed by the results of XRD spectra analysis. The research holds the potential to solve problems related to the fatigue life monitoring of particulate polymer composites.

Embedded real-time and in-situ fatigue life monitoring sensor with load types identification

Structural fatigue failure has always been a widely concerned research in mechanical equipment. It requires more and more real-time monitoring of structural damage before cracks appear for the intelligent development of modern equipment. Based on embedded technology, a real-time fatigue in-situ fatigue life monitoring sensor (FLMS) is proposed, which has the function of load spectrum identification and linear cumulative damage calculation. The sensor can realize wireless communication through LoRa integration module. After experimental verification, the number of remaining cycles, residual damage and remaining time life can be calculated quickly for different types of loads. The fatigue life prediction error for cycle load is basically within 22%. The maximum and minimum calculation error under random load of the FLMS are 2.27 times and 1.01 times, respectively. And they can be displayed in real time and stored regularly. The integrated sensor can realize the real-time fatigue life prediction of the structure and promote the intelligent development of fatigue life monitoring of the equipment. • This paper proposes a real-time monitoring method for identification of load types based on embedded processor. • The real-time fatigue life monitoring of the FLMS is realized through algorithm integration. • The life error for cycle load is basically within 22%, and it is kept at 2.3 times for random load.

Non-destructive testing and fatigue life prediction at different environmental temperatures

The concept of fatigue fracture entropy (FFE) is utilized and extended to predict and monitor the metal fatigue life of the specimens at different environmental temperatures via infrared technology. An application of the method via a real-time fatigue life monitoring unit is presented wherein, regardless of the environmental temperature, the unit automatically shuts down the machine prior to the onset of fatigue fracture. Results show that FFE is relatively constant for ambient temperatures from 25 °C to 200 °C. The analysis of the results also demonstrates that the variation of the plastic strain energy as a function of the number of cycles to failure can be generalized in a functional form independent of the environmental temperature.

The low-cycle fatigue life assessment method for online monitoring of steam turbine rotors

The paper presents a simple method for the low-cycle fatigue life monitoring of steam turbine rotors. The method makes use of the equivalent strain energy density rule of notch stress-strain analysis proposed by Molski and Glinka. The method is applied to low-cycle fatigue analyses of steam turbine rotors operating at non-isothermal conditions. A strain energy correction factor is introduced to include the distortion strain energy density. Assessment of the proposed method was done by comparing their estimations with the strain amplitudes obtained from the finite element analysis employing elasitc-plastic material model. The inclusion of energy correction factor obtained from the elastic-plastic finite element analysis significantly improves the accuracy of strain amplitudes and fatigue life estimations. The strain calculation algorithm is based on an analytical solution of the equivalent strain energy equation what makes it very useful for real time fatigue calculations.

Verification of an airframe fatigue life monitoring system using ex-service structure

Abstract In this paper the verification of the Royal Australian Air Force's (RAAF) F/A-18 Hornet Airframe Service Life Monitoring system is summarised. The availability of a significant number of RAAF ex-service centre fuselage sections with known usage facilitated this effort. Using an enhanced teardown procedure, in-service crack growth was identified at a significant number of locations. By comparing measured in-service growth with full scale fatigue test-demonstrated growth, and fitting failure distributions to the in-service data, the effectiveness of the monitoring system in maintaining a specific probability of failure was assessed.

Fatigue Life Monitoring System for Aircraft to Flexibilize Operations and Maintenance Planning

The damage tolerance analysis, which uses the force structural management plan, is usually employed in airplane fatigue life prediction. This plan, based on a mission “mix” defined at the airplane structure design phase, induces the squadrons to follow this mix and interferes in the fleet’s usage efficiency. Deviations in the mission mix have impacts on inspection intervals and maintenance costs. In this paper, a fatigue life monitoring system is proposed. It is able to incorporate each mission, individually, in a specific aircraft’s fatigue life analysis, adjusting the maintenance plan into a more realistic usage profile, based on the individual aircraft tracking methodology. This monitoring system is implemented in a computer software and it is applied to F-5E fighter aircraft of the Brazilian Air Force. In addition, experimental fatigue tests that simulate critical locations of this aircraft are compared with the proposed monitoring system, which shows ability to predict, in conservative and approximate ways, the crack length after each flight, disregarding the predefined mission mix. This makes the flexibilization of the operations possible without jeopardizing the inspection and maintenance planning.

Research on 800 MN hydraulic press monitoring system

In this paper, a capable of loading, stress and strain monitoring system is developed, which is based on fatigue reliability analysis theory. The 800 MN die-forging hydraulic press body structure system on pre-tightened condition was studied and developed a capable of loading, stress and strain monitoring and data processing methods. This system also has on-line compressor structural static strength and fatigue life monitoring and prediction function, which has been conducted laboratory experiments. The experiment using the actual use conditions close to the press at the time of piecewise continuous loading mode, the signal at any time monitoring of each measuring point is abnormal. The experimental results show that using electrometric method detecting the working stress and strain state is feasible, reproduction can be achieved through press technology parameters of the real-time data acquisition, the system can meet with the using requirements, it has practical value.

Proportional monitoring of the acoustic emission in crypto-conditions

The work is aimed at studying corrosion and fatigue properties of aluminum alloys by means of acoustic emission (AE). During material degradation are acoustic events scanned and evaluated. The main objective of the article is a description of behavior of aluminum alloys degraded in specific conditions and critical degradation stages determination. The first part of the article describes controlled degradation of the material in the crypto–conditions. The acoustic emission method is used for process analyzing. This part contains the AE signals assessment and comparing aluminium alloy to steel. Then the specimens are loaded on high-cyclic loading apparatus for fatigue life monitoring. Also, the synergy of fatigue and corrosion processes is taken into account.The aim is the description of fatigue properties for aluminum alloys that have already been corrosion-degraded. Attention is also focused on the structure of fatigue cracks. The main part of the article is aimed at corrosion degradation of aluminium alloys researched in real time by means of AE. The most important benefit of AE detection/recording is that it provides information about the process in real time. Using this measurement system is possible to observe the current status of the machines/devices and to prevent serious accidents.

An On-Line Fatigue Life Monitoring System for Boiler Drums Based on the Inverse Problem of Heat Conduction Method

A method based on solution of the inverse heat conduction problem was presented for online stress monitoring and fatigue life analysis of boiler drums. The mathematical model of the drum temperature distribution is based on the assumptions that the difference of temperature along the longitudinal axis of the boiler drum is negligible with changes only in the radial direction and the circumferential direction, and that the outer surface of drum is thermally insulated. Combining this model with the control-volume method provides temperatures at different points on a cross-section of the drum. With the temperature data, the stresses of the boiler drum are derived according to the FEM and the life expectancy of it is calculated based on the rain flow method. Applying this method to the cold start-up process of a 300 MW boiler demonstrated the absence of errors caused by the boundary condition assumptions on the inner surface of the drum and an applicable technique for the online stress monitoring and fatigue life analysis of boiler drums.

Fatigue Life Monitoring Program of RMAF MiG-29

The Royal Malaysian Airforce (RMAF) operates one squadron of MiG-29 which were designed on Safe Life principle. RMAF conducts a fatigue life monitoring program to these airplanes. This activity is conducted based on the experience of having the fatigue life monitoring program to the RMAF F/A-18D. The fatigue life of RMAF MiG-29 is based on the wing-fuselage lug joint structure, and Low Cycle Fatigue (LCF) approach is adopted. The stress spectra of this component, is derived through mapping of g-spectra to the 1-g stress level of the lug. The g-history is obtained from the accelerator installed in the airplane, while the 1-g stress level is obtained by finite element modeling of the wing structure and lug joints. Rainflow cycle counting procedure was then applied. The fatigue characteristics (strain-life) of the lug material was obtained from the laboratory test, using the lug material sample, combined with the empirical formula of strain-life diagram. Notched effect is taken into account using Neuber theory. Mean stress effect is dealt with using Smith-Watson-Topper formula. Miner’s rule is used to calculate the fatigue damage accumulation. A fatigue life prediction software for RMAF MiG-29 which incorporates the above concepts had been developed. Currently, this software is operational with the RMAF MiG-29, and is being used as part of its Aircraft Structural Integrity Program (ASIP). This paper reports on the development of the fatigue life monitoring strategy and software for the RMAF MiG-29.

On line fatigue life monitoring methodology for power plant components

Fatigue is one of the most important aging effects of power plant components. Information about fatigue helps in assessing structural degradation of the components and so assists in planning in-service inspection and maintenance. It may also support the future life extension programme of a power plant. In the present paper, the development of a methodology for on line fatigue life monitoring using available plant instrumentation is presented. The Green's function technique is used to convert plant data to stress-time data. Using a rainflow cycle counting method, stress-time data are analysed and the fatigue usage factor is computed from the material fatigue curve. Various codes are developed to generate Green's functions, to convert plant data to stress-time data, to find the fatigue usage factor and to display fatigue information. Using the developed codes, information about the fatigue life of various components of a power plant can be updated, stored and displayed interactively by plant operators. Three different case studies are reported in the present paper. These are the fatigue analyses of a thick pipe, of a nozzle connected to a pressure vessel and of a reducer connecting a heat exchanger to its piping system.

In-flight computation of helicopter transmission fatigue life expenditure

Estimates of the safe fatigue life of critical helicopter transmission components may be made if in-service load data together with component fatigue data are available. Instrumentation has been developed to provide inflight computation and indication of the current values of fatigue life expended for critical gears in single- or twin-engine helicopter transmission systems. In addition, basic transmission load data in the form of totalized times spent in a number of contiguous torque bands are continually updated and stored during flight. The basic load data together with values of life expenditure for critical gears for the current flight can be automatically printed out after flight. This development opens the way towards fatigue life monitoring of individual transmissions. Nomenclature A, B = gear fatigue curve shape constants / = torque readings per second G = torque bandwidth Kj = constant referred to hypothetical torque load spectrum 1

The fatigue of aircraft structures

Current procedures for fatigue design and for fatigue life estimation, substantiation and monitoring of aircraft structures are reviewed. Major gaps in the present state of knowledge are identified and further research directed towards filling these gaps is discussed. Brief reference is made to the major fields of basic or fundamental research connected with the fatigue of structures including, the application of fracture mechanics to the theory of crack propagation, elevated temperature behaviour of aircraft materials, atmospheric turbulence, reliability based design and aeroelastic behaviour. It is seen that with the present advances in aircraft design and utilisation the fatigue assessment of aircraft structures is an increasingly complex problem for which no general method of solution has yet been established. At present reliance is placed on extensive testing of design details and components, usually in conjunction with a full scale fatigue test, to validate the fatigue analysis and substantiate, or provide the essential data used for fatigue life monitoring. There is however a well developed trend for basic studies of the various aspects of fatigue behaviour, to find increasing application in the interpretation of experimental results for fatigue life assessment and improved methods of fatigue design.