Transactions of Nanjing University of Aeronautics & Astronautics
Volume 35,Issue 2,2018 Table of Contents
Alfredo Güemes
,
Antonio Fernandez-Lopez
,
Jaime García-Ramírez
,
Maria Eugenia Reyes-Perez
,
Flor Criado Zurita
2018, 35(2):219-225.
DOI: 10.16356/j.1005-1120.2018.02.219
Abstract:
Probability of detection (POD) graphics allow for a change from qualitative to quantitative assessment for every damage detection system, and as such it is a main request for conventional non-destructive testing (NDT) techniques. Its availability can greatly help towards the industrialization of the corresponding Structural health monitoring (SHM) system. But having in mind that for SHM systems the sensors are at fixed positions, and the location of a potential damage would change its detectability. Consequently robust simulation tools are required to obtain the model assisted probability of detection (MAPOD) which is needed to validate the SHM system. This tool may also help for the optimization of the sensor distribution, and finally will allow a probabilistic risk management. INDEUS,simulation of ultrasonic waves SHM system, was a main milestone in this direction. This article deals with the simulation tools for a strain based SHM system, using fiber optic sensors (FOS). FOS are essentially strain/temperature sensors, either with multi-point or with distributed sensing. The simulation tool includes the finite element model (FEM) for the original and damaged structure, and algorithms to compare the strain data at the pre-established sensors locations, and from this comparison to extract information about damage occurrence and location.
The study has been applied to the structure of an all-composite unmanned aircraft vehicle (UAV) now under construction, designed at Universidad Politecnica de Madrid for the inspection of electrical utilities networks. Distributed sensing optical fibers were internally bonded at the fuselage and wing. Routine inspection is planned to be done with the aircraft at the test bench by imposing known loads. From the acquired strain data, damage occurrence may be calculated as slight deviations from the baselines. This is a fast inspection procedure without requiring trained specialists, and it would allow for detection of hidden damages. Simulation indicates that stringer partial debondings are detected before they become critical, while small delaminations as those produced by barely visible impact damages would require a prohibited number of sensing lines. These simulation tools may easily be applied to any other complex structure, just by changing the FEM models. From these results it is shown how a fiber optic based SHM system may be used as a reliable damage detection procedure.
Probability of detection (POD) graphics allow for a change from qualitative to quantitative assessment for every damage detection system, and as such it is a main request for conventional non-destructive testing (NDT) techniques. Its availability can greatly help towards the industrialization of the corresponding Structural health monitoring (SHM) system. But having in mind that for SHM systems the sensors are at fixed positions, and the location of a potential damage would change its detectability. Consequently robust simulation tools are required to obtain the model assisted probability of detection (MAPOD) which is needed to validate the SHM system. This tool may also help for the optimization of the sensor distribution, and finally will allow a probabilistic risk management. INDEUS,simulation of ultrasonic waves SHM system, was a main milestone in this direction. This article deals with the simulation tools for a strain based SHM system, using fiber optic sensors (FOS). FOS are essentially strain/temperature sensors, either with multi-point or with distributed sensing. The simulation tool includes the finite element model (FEM) for the original and damaged structure, and algorithms to compare the strain data at the pre-established sensors locations, and from this comparison to extract information about damage occurrence and location.
The study has been applied to the structure of an all-composite unmanned aircraft vehicle (UAV) now under construction, designed at Universidad Politecnica de Madrid for the inspection of electrical utilities networks. Distributed sensing optical fibers were internally bonded at the fuselage and wing. Routine inspection is planned to be done with the aircraft at the test bench by imposing known loads. From the acquired strain data, damage occurrence may be calculated as slight deviations from the baselines. This is a fast inspection procedure without requiring trained specialists, and it would allow for detection of hidden damages. Simulation indicates that stringer partial debondings are detected before they become critical, while small delaminations as those produced by barely visible impact damages would require a prohibited number of sensing lines. These simulation tools may easily be applied to any other complex structure, just by changing the FEM models. From these results it is shown how a fiber optic based SHM system may be used as a reliable damage detection procedure.
2 Segmentation of Thermographic Sequences in Frequency Modulated Thermal Wave Imaging for NDE of GFRP
2018, 35(2):226-235.
DOI: 10.16356/j.1005-1120.2018.02.226
Abstract:
Image processing techniques have become highly essential to improve the data usefulness of the raw images obtained for infrared non-destructive evaluation (NDE). The identification of defective regions from a thermogram has been a common problem in the field of NDE. Image segmentation is one of the promising approaches to identify defective regions from thermogram. In the present work, segmentation approach based on clustering is employed. In this image patterns are organized into clusters or groups considering the relationship among these. The method involves finding the centroids of the regions and formation of clusters around each centroid. Thresholding is applied to improve accuracy in formation of clusters. Double thresholding method is adapted to retrieve the shape of defect and to improve the possible diagnosis capabilities of system for NDE applications. The proposed method is investigated with frequency modulated thermal wave imaging (FMTWI) over glass fiber reinforced polymers (GFRP). The GFRP sample consists of square shaped Teflon inserts of different dimensions placed at various depths. A comparative study of the proposed novel segmentation scheme and existing segmentation methods is conducted.
Image processing techniques have become highly essential to improve the data usefulness of the raw images obtained for infrared non-destructive evaluation (NDE). The identification of defective regions from a thermogram has been a common problem in the field of NDE. Image segmentation is one of the promising approaches to identify defective regions from thermogram. In the present work, segmentation approach based on clustering is employed. In this image patterns are organized into clusters or groups considering the relationship among these. The method involves finding the centroids of the regions and formation of clusters around each centroid. Thresholding is applied to improve accuracy in formation of clusters. Double thresholding method is adapted to retrieve the shape of defect and to improve the possible diagnosis capabilities of system for NDE applications. The proposed method is investigated with frequency modulated thermal wave imaging (FMTWI) over glass fiber reinforced polymers (GFRP). The GFRP sample consists of square shaped Teflon inserts of different dimensions placed at various depths. A comparative study of the proposed novel segmentation scheme and existing segmentation methods is conducted.
2018, 35(2):236-243.
DOI: 10.16356/j.1005-1120.2018.02.236
Abstract:
Non-destructive measurement of absolute stress in steel members can provide useful information to optimize the design of steel structures and allow the safety of existing structures to be evaluated. This paper investigates the non-destructive capability of ultrasonic shear-wave spectroscopy in absolute stress evaluation of steel members. The effect of steel-member stress on the shear-wave amplitude spectrum is investigated, and a method of absolute stress measurement is proposed. Specifically, the process for evaluating absolute stress using shear-wave spectroscopy is summarized. Two steel members are employed to investigate the relationship between the stress and the frequency in shear-wave echo amplitude spectrum. The H-beam loaded by the universal testing machine is evaluated by the proposed method and the traditional strain gauge method for verification. The results show that the proposed method is effective and accurate for determining absolute stress in steel members.Non-destructive measurement of absolute stress in steel members can provide useful information to optimize the design of steel structures and allow the safety of existing structures to be evaluated. This paper investigates the non-destructive capability of ultrasonic shear-wave spectroscopy in absolute stress evaluation of steel members. The effect of steel-member stress on the shear-wave amplitude spectrum is investigated, and a method of absolute stress measurement is proposed. Specifically, the process for evaluating absolute stress using shear-wave spectroscopy is summarized. Two steel members are employed to investigate the relationship between the stress and the frequency in shear-wave echo amplitude spectrum. The H-beam loaded by the universal testing machine is evaluated by the proposed method and the traditional strain gauge method for verification. The results show that the proposed method is effective and accurate for determining absolute stress in steel members.
Non-destructive measurement of absolute stress in steel members can provide useful information to optimize the design of steel structures and allow the safety of existing structures to be evaluated. This paper investigates the non-destructive capability of ultrasonic shear-wave spectroscopy in absolute stress evaluation of steel members. The effect of steel-member stress on the shear-wave amplitude spectrum is investigated, and a method of absolute stress measurement is proposed. Specifically, the process for evaluating absolute stress using shear-wave spectroscopy is summarized. Two steel members are employed to investigate the relationship between the stress and the frequency in shear-wave echo amplitude spectrum. The H-beam loaded by the universal testing machine is evaluated by the proposed method and the traditional strain gauge method for verification. The results show that the proposed method is effective and accurate for determining absolute stress in steel members.Non-destructive measurement of absolute stress in steel members can provide useful information to optimize the design of steel structures and allow the safety of existing structures to be evaluated. This paper investigates the non-destructive capability of ultrasonic shear-wave spectroscopy in absolute stress evaluation of steel members. The effect of steel-member stress on the shear-wave amplitude spectrum is investigated, and a method of absolute stress measurement is proposed. Specifically, the process for evaluating absolute stress using shear-wave spectroscopy is summarized. Two steel members are employed to investigate the relationship between the stress and the frequency in shear-wave echo amplitude spectrum. The H-beam loaded by the universal testing machine is evaluated by the proposed method and the traditional strain gauge method for verification. The results show that the proposed method is effective and accurate for determining absolute stress in steel members.
2018, 35(2):244-255.
DOI: 10.16356/j.1005-1120.2018.02.244
Abstract:
It is difficult to quantitatively detect defects by using the time domain or frequency domain features of Lamb wave signals due to their dispersion and multimodal characteristics. Therefore, it is important to discover an intrinsical parameter of Lamb waves that could be used as a damage sensitive feature. In this paper, quantitative defect detection in aluminium plates is carried out by means of wavenumber analysis approach. The wavenumber of excited Lamb wave mode is a fixed value, given a frequency, a thickness and material properties of the target plate. When Lamb waves propagate to the structural discontinuity, new wavenumber components are created by abrupt wavefield change. The new wavenumber components can be identified in the frequency-wavenumber domain. To estimate spatially dependent wavenumber values, a short-space two-dimensional Fourier transform(FT) method is presented for processing wavefield data of Lamb waves. The results can be used to determine the location, size and depth of rectangular notch. The analysis techniques are demonstrated using simulation examples of an aluminium plate with a rectangular notch. Then, the wavenumber analysis method is applied to simulation data that are obtained through a range of notch depths and widths. The results are analyzed and rules of the technique with regards to estimating notch depth are determined. Based on simulation results, guidelines for using the technique are developed. Finally, experimental wavefield data are obtained in aluminium plates with rectangular notches by a full non-contact transceiving method, i.e., laser-laser method. Band-pass filtering combined with continuous wavelet transform is used to extract a certain frequency component from the full laser-induced wavefield with wide band. Short-space two-dimensional FT method is used for further processing full wavefield data at a certain frequency to estimate spatially dependent wavenumber values. The consistency of simulation and experimental results shows the effectiveness of proposed wavenumber method for quantitative rectangular notch detection.
It is difficult to quantitatively detect defects by using the time domain or frequency domain features of Lamb wave signals due to their dispersion and multimodal characteristics. Therefore, it is important to discover an intrinsical parameter of Lamb waves that could be used as a damage sensitive feature. In this paper, quantitative defect detection in aluminium plates is carried out by means of wavenumber analysis approach. The wavenumber of excited Lamb wave mode is a fixed value, given a frequency, a thickness and material properties of the target plate. When Lamb waves propagate to the structural discontinuity, new wavenumber components are created by abrupt wavefield change. The new wavenumber components can be identified in the frequency-wavenumber domain. To estimate spatially dependent wavenumber values, a short-space two-dimensional Fourier transform(FT) method is presented for processing wavefield data of Lamb waves. The results can be used to determine the location, size and depth of rectangular notch. The analysis techniques are demonstrated using simulation examples of an aluminium plate with a rectangular notch. Then, the wavenumber analysis method is applied to simulation data that are obtained through a range of notch depths and widths. The results are analyzed and rules of the technique with regards to estimating notch depth are determined. Based on simulation results, guidelines for using the technique are developed. Finally, experimental wavefield data are obtained in aluminium plates with rectangular notches by a full non-contact transceiving method, i.e., laser-laser method. Band-pass filtering combined with continuous wavelet transform is used to extract a certain frequency component from the full laser-induced wavefield with wide band. Short-space two-dimensional FT method is used for further processing full wavefield data at a certain frequency to estimate spatially dependent wavenumber values. The consistency of simulation and experimental results shows the effectiveness of proposed wavenumber method for quantitative rectangular notch detection.
2018, 35(2):256-263.
DOI: 10.16356/j.1005-1120.2018.02.256
Abstract:
Numerous non-destructive techniques are being investigated for assuring quality of the adhesive bonds. The research presented here is focused on non-destructive assessment of carbon fibre reinforced polymer (CFRP) parts. The surface condition directly influences the performance of adhesive bonds. The structural joints should ensure safe usage of a structure. However, some modifications of the surface may lead to weak bond that cannot carry the desired load. This is why there is a search for methods of surface assessment before bonding. Moreover, reliable techniques are required to allow to verify the integrity of the adhesive bond after manufacturing or bonded repair. We focus on the laser induced fluorescence (LIF) method for assessing the surface state. The LIF is a non-contact measurement method. In the context of adhesive bond assessment the electromechanical impedance (EMI) method is studied. The EMI uses surface bonded piezoelectric sensors for excitation and sensing. The investigated samples were made of CFRP layers. The samples were treated at elevated temperatures. The influence of the thermal treatment was studied using LIF. The thermal treatment at 220℃ could be clearly distinguishedrom the rest of the considered samples. The thermally treated plates were bonded to untreated plate and then they were measured with the EMI method to study the influence of the treatment on the adhesive bond. The changes of EMI spectra were significant for the treatment at 280℃ and for some thermally treated samples that were later contaminated with de-icing fluid.
Numerous non-destructive techniques are being investigated for assuring quality of the adhesive bonds. The research presented here is focused on non-destructive assessment of carbon fibre reinforced polymer (CFRP) parts. The surface condition directly influences the performance of adhesive bonds. The structural joints should ensure safe usage of a structure. However, some modifications of the surface may lead to weak bond that cannot carry the desired load. This is why there is a search for methods of surface assessment before bonding. Moreover, reliable techniques are required to allow to verify the integrity of the adhesive bond after manufacturing or bonded repair. We focus on the laser induced fluorescence (LIF) method for assessing the surface state. The LIF is a non-contact measurement method. In the context of adhesive bond assessment the electromechanical impedance (EMI) method is studied. The EMI uses surface bonded piezoelectric sensors for excitation and sensing. The investigated samples were made of CFRP layers. The samples were treated at elevated temperatures. The influence of the thermal treatment was studied using LIF. The thermal treatment at 220℃ could be clearly distinguishedrom the rest of the considered samples. The thermally treated plates were bonded to untreated plate and then they were measured with the EMI method to study the influence of the treatment on the adhesive bond. The changes of EMI spectra were significant for the treatment at 280℃ and for some thermally treated samples that were later contaminated with de-icing fluid.
2018, 35(2):264-274.
DOI: 10.16356/j.1005-1120.2018.02.264
Abstract:
In this paper damage assessment based on guided elastic wave propagation phenomenon is presented. Guided waves are generated by piezoelectric transducer and registered by scanning laser doppler vibrometer (SLDV). Signal processing is based on the analysis of full wavefield measurements gathered from dense mesh of measurement points spanned over area of investigated samples. Full wavefield measurement approach allows creation of animations presenting the guided wave propagation in the structure. Moreover such approach is suitable for analysis of interaction of guided waves with discontinuities located in structure. In the research attention is paid especially on analysis of phenomenon of S0/A0' guided wave mode conversion due to interaction with investigated discontinuities-teflon inserts and impact damage. The presented work is related to glass fibre reinforced polymer (GFRP) samples. In the research, auxiliary non-destructive testing (NDT) method is also utilized. The aim of this method is to indicate the depth of discontinuity, and to prove that delamination was created in the case of impact damage. Auxiliary method is based on terahertz spectroscopy (THz) where the analysis of propagation of electromagnetic waves in the terahertz band is conducted. THz spectroscopy method can be utilized for damage assessment in the dielectric materials like GFRP.
In this paper damage assessment based on guided elastic wave propagation phenomenon is presented. Guided waves are generated by piezoelectric transducer and registered by scanning laser doppler vibrometer (SLDV). Signal processing is based on the analysis of full wavefield measurements gathered from dense mesh of measurement points spanned over area of investigated samples. Full wavefield measurement approach allows creation of animations presenting the guided wave propagation in the structure. Moreover such approach is suitable for analysis of interaction of guided waves with discontinuities located in structure. In the research attention is paid especially on analysis of phenomenon of S0/A0' guided wave mode conversion due to interaction with investigated discontinuities-teflon inserts and impact damage. The presented work is related to glass fibre reinforced polymer (GFRP) samples. In the research, auxiliary non-destructive testing (NDT) method is also utilized. The aim of this method is to indicate the depth of discontinuity, and to prove that delamination was created in the case of impact damage. Auxiliary method is based on terahertz spectroscopy (THz) where the analysis of propagation of electromagnetic waves in the terahertz band is conducted. THz spectroscopy method can be utilized for damage assessment in the dielectric materials like GFRP.
2018, 35(2):275-281.
DOI: 10.16356/j.1005-1120.2018.02.275
Abstract:
Structural health monitoring (SHM) in service has attracted increasing attention for years. Load localization on a structure is studied hereby. Two algorithms, i.e., support vector machine (SVM) method and back propagation neural network (BPNN) algorithm, are proposed to identify the loading positions individually. The feasibility of the suggested methods is evaluated through an experimental program on a carbon fiber reinforced plastic laminate. The experimental tests involve in application of four optical fiber-based sensors for strain measurement at discrete points. The sensors are specially designed fiber Bragg grating (FBG) in small diameter. The small-diameter FBG sensors are arrayed in 2-D on the laminate surface. The testing results indicate that the loading position could be detected by the proposed method. Using SVM method, the 2-D FBG sensors can approximate the loading location with maximum error less than 14 mm. However, the maximum localization error could be limited to about 1 mm by applying the BPNN algorithm. It is mainly because the convergence conditions (mean square error) can be set in advance, while SVM cannot.
Structural health monitoring (SHM) in service has attracted increasing attention for years. Load localization on a structure is studied hereby. Two algorithms, i.e., support vector machine (SVM) method and back propagation neural network (BPNN) algorithm, are proposed to identify the loading positions individually. The feasibility of the suggested methods is evaluated through an experimental program on a carbon fiber reinforced plastic laminate. The experimental tests involve in application of four optical fiber-based sensors for strain measurement at discrete points. The sensors are specially designed fiber Bragg grating (FBG) in small diameter. The small-diameter FBG sensors are arrayed in 2-D on the laminate surface. The testing results indicate that the loading position could be detected by the proposed method. Using SVM method, the 2-D FBG sensors can approximate the loading location with maximum error less than 14 mm. However, the maximum localization error could be limited to about 1 mm by applying the BPNN algorithm. It is mainly because the convergence conditions (mean square error) can be set in advance, while SVM cannot.
2018, 35(2):282-289.
DOI: 10.16356/j.1005-1120.2018.02.282
Abstract:
Signals can be sampled by compressive sensing theory with a much less rate than those by traditional Nyquist sampling theorem, and reconstructed with high probability, only when signals are sparse in the time domain or a transform domain. Most signals are not sparse in real world, but can be expressed in sparse form by some kind of sparse transformation. Commonly used sparse transformations will lose some information, because their transform bases are generally fixed. In this paper, we use principal component analysis for data reduction, and select new variable with low dimension and linearly correlated to the original variable, instead of the original variable with high dimension, thus the useful data of the original signals can be included in the sparse signals after dimensionality reduction with maximize portability. Therefore, the loss of data can be reduced as much as possible, and the efficiency of signal reconstruction can be improved. Finally, the composite material plate is used for the experimental verification. The experimental result shows that the sparse representation of signals based on principal component analysis can reduce signal distortion and improve signal reconstruction efficiency.
Signals can be sampled by compressive sensing theory with a much less rate than those by traditional Nyquist sampling theorem, and reconstructed with high probability, only when signals are sparse in the time domain or a transform domain. Most signals are not sparse in real world, but can be expressed in sparse form by some kind of sparse transformation. Commonly used sparse transformations will lose some information, because their transform bases are generally fixed. In this paper, we use principal component analysis for data reduction, and select new variable with low dimension and linearly correlated to the original variable, instead of the original variable with high dimension, thus the useful data of the original signals can be included in the sparse signals after dimensionality reduction with maximize portability. Therefore, the loss of data can be reduced as much as possible, and the efficiency of signal reconstruction can be improved. Finally, the composite material plate is used for the experimental verification. The experimental result shows that the sparse representation of signals based on principal component analysis can reduce signal distortion and improve signal reconstruction efficiency.
2018, 35(2):290-299.
DOI: 10.16356/j.1005-1120.2018.02.290
Abstract:
Aero-engine direct thrust control can not only improve the thrust control precision but also save the operating cost by reducing the reserved margin in design and making full use of aircraft engine potential performance. However, it is a big challenge to estimate engine thrust accurately. To tackle this problem, this paper proposes an ensemble of improved wavelet extreme learning machine (EW-ELM) for aircraft engine thrust estimation. Extreme learning machine (ELM) has been proved as an emerging learning technique with high efficiency. Since the combination of ELM and wavelet theory has the both excellent properties, wavelet activation functions are used in the hidden nodes to enhance non-linearity dealing ability. Besides, as original ELM may result in ill-condition and robustness problems due to the random determination of the parameters for hidden nodes, particle swarm optimization (PSO) algorithm is adopted to select the input weights and hidden biases. Furthermore, the ensemble of the improved wavelet ELM is utilized to construct the relationship between the sensor measurements and thrust. The simulation results verify the effectiveness and efficiency of the developed method and show that aero-engine thrust estimation using EW-ELM can satisfy the requirements of direct thrust control in terms of estimation accuracy and computation time.
Aero-engine direct thrust control can not only improve the thrust control precision but also save the operating cost by reducing the reserved margin in design and making full use of aircraft engine potential performance. However, it is a big challenge to estimate engine thrust accurately. To tackle this problem, this paper proposes an ensemble of improved wavelet extreme learning machine (EW-ELM) for aircraft engine thrust estimation. Extreme learning machine (ELM) has been proved as an emerging learning technique with high efficiency. Since the combination of ELM and wavelet theory has the both excellent properties, wavelet activation functions are used in the hidden nodes to enhance non-linearity dealing ability. Besides, as original ELM may result in ill-condition and robustness problems due to the random determination of the parameters for hidden nodes, particle swarm optimization (PSO) algorithm is adopted to select the input weights and hidden biases. Furthermore, the ensemble of the improved wavelet ELM is utilized to construct the relationship between the sensor measurements and thrust. The simulation results verify the effectiveness and efficiency of the developed method and show that aero-engine thrust estimation using EW-ELM can satisfy the requirements of direct thrust control in terms of estimation accuracy and computation time.
2018, 35(2):300-308.
DOI: 10.16356/j.1005-1120.2018.02.300
Abstract:
In this paper, a theoretical model of temperature and velocity of a fiber is derived. A test model simulating seepage indoor is designed. The optical fiber heating temperatures under different compaction degree and seepage velocities are measured through applying AC voltage on the optical fiber. The analyzing results show that the optical fiber heating temperature and seepage velocity are related in quadratic function. The quantitative relations of optical fiber temperature and seepage velocity under different soil types and compaction degree are fitted. Analysis on how the compaction degree influences the relation of optical fiber temperature and seepage velocity shows that with the increase of compaction degree, optical fiber heating temperature will gradually decline. The influence of soil type on fiber heating temperature is very complex. In practice, according to the characteristics of the soil, determining quantitative relationship and implementing quantitative monitoring of the seepage velocity are needed.
In this paper, a theoretical model of temperature and velocity of a fiber is derived. A test model simulating seepage indoor is designed. The optical fiber heating temperatures under different compaction degree and seepage velocities are measured through applying AC voltage on the optical fiber. The analyzing results show that the optical fiber heating temperature and seepage velocity are related in quadratic function. The quantitative relations of optical fiber temperature and seepage velocity under different soil types and compaction degree are fitted. Analysis on how the compaction degree influences the relation of optical fiber temperature and seepage velocity shows that with the increase of compaction degree, optical fiber heating temperature will gradually decline. The influence of soil type on fiber heating temperature is very complex. In practice, according to the characteristics of the soil, determining quantitative relationship and implementing quantitative monitoring of the seepage velocity are needed.
2018, 35(2):309-317.
DOI: 10.16356/j.1005-1120.2018.02.309
Abstract:
Bubble plumes are important during the process of air-sea exchange, and optical-fiber phase detection is a suitable way to observe bubble plumes entrained by breaking waves. This paper designs a new optical-fiber probe (OFP) made of sapphire to overcome the limitations of existing materials (e.g., high brittleness, poor corrosion resistance, and narrow bandwidth) and thereby enhance the detection performance of the OFP by improving its structure. Based on total internal reflection and light refraction, a simulation model of the probe is established in the Zemax optical design software to optimize the probe tip and matching mode of the two probe tips. The results show that the optimum OFP tip is a conical sapphire one with a cone angle of 35°. Tests are then conducted on a bespoke OFP sensor, the results of which are consistent with those predicted theoretically. The simulation results lay the foundation for the integrated design of OFP sensors and the optimization of their internal optics. The findings could also be applied to OFPs with multiple tips.
Bubble plumes are important during the process of air-sea exchange, and optical-fiber phase detection is a suitable way to observe bubble plumes entrained by breaking waves. This paper designs a new optical-fiber probe (OFP) made of sapphire to overcome the limitations of existing materials (e.g., high brittleness, poor corrosion resistance, and narrow bandwidth) and thereby enhance the detection performance of the OFP by improving its structure. Based on total internal reflection and light refraction, a simulation model of the probe is established in the Zemax optical design software to optimize the probe tip and matching mode of the two probe tips. The results show that the optimum OFP tip is a conical sapphire one with a cone angle of 35°. Tests are then conducted on a bespoke OFP sensor, the results of which are consistent with those predicted theoretically. The simulation results lay the foundation for the integrated design of OFP sensors and the optimization of their internal optics. The findings could also be applied to OFPs with multiple tips.
12 Fault Estimation and Accommodation for a Class of Nonlinear System Based on Neural Network Observer
2018, 35(2):318-325.
DOI: 10.16356/j.1005-1120.2018.02.318
Abstract:
The problem of fault estimation and accommodation of nonlinear systems with disturbances is studied using adaptive observer and neural network techniques. A robust adaptive learning algorithm based on switching βs-modification is developed to realize the accurate and fast estimation of unknown actuator faults or component faults. Then a fault tolerant controller is designed to restore system performance. Dynamic error convergence and system stability can be guaranteed by Lyapunov stability theory. Finally, simulation results of quadrotor helicopter attitude systems are presented to illustrate the efficiency of the proposed techniques.
The problem of fault estimation and accommodation of nonlinear systems with disturbances is studied using adaptive observer and neural network techniques. A robust adaptive learning algorithm based on switching βs-modification is developed to realize the accurate and fast estimation of unknown actuator faults or component faults. Then a fault tolerant controller is designed to restore system performance. Dynamic error convergence and system stability can be guaranteed by Lyapunov stability theory. Finally, simulation results of quadrotor helicopter attitude systems are presented to illustrate the efficiency of the proposed techniques.
2018, 35(2):326-333.
DOI: 10.16356/j.1005-1120.2018.02.326
Abstract:
The effect of curing age on chloride diffusion coefficient of recycled aggregate concrete subjected to different compressive stresses was investigated. A compression loading setup was both designed and fabricated. The chloride diffusion coefficients of recycled aggregate concrete under compressive stresses were measured by the rapid chloride ion migration (RCM) method. The experimental results show that the chloride diffusion coefficients of recycled aggregate concrete (RAC) under different compressive stress ratios generally decrease with the increase of curing age. For RAC subjected to the same compressive stress ratios, the chloride diffusion coefficients approximately have power functions with curing ages and the relationship models are proposed. Moreover, the influence of curing age on chloride diffusion coefficient firstly decreases and then increases as the compressive stress ratio increases.
The effect of curing age on chloride diffusion coefficient of recycled aggregate concrete subjected to different compressive stresses was investigated. A compression loading setup was both designed and fabricated. The chloride diffusion coefficients of recycled aggregate concrete under compressive stresses were measured by the rapid chloride ion migration (RCM) method. The experimental results show that the chloride diffusion coefficients of recycled aggregate concrete (RAC) under different compressive stress ratios generally decrease with the increase of curing age. For RAC subjected to the same compressive stress ratios, the chloride diffusion coefficients approximately have power functions with curing ages and the relationship models are proposed. Moreover, the influence of curing age on chloride diffusion coefficient firstly decreases and then increases as the compressive stress ratio increases.
2018, 35(2):334-342.
DOI: 10.16356/j.1005-1120.2018.02.334
Abstract:
Twin support vector machine (TWSVM) is a new development of support vector machine (SVM) algorithm. It has the smaller computation scale and the stronger ability to cope with unbalanced problems. In this paper, TWSVM is introduced into aircraft engine gas path fault diagnosis. The generalization capacity of Gauss kernel function usually used in TWSVM is relatively weak. So a mixed kernel function is used to improve performance to ensure that the TWSVM algorithm can better balance a strong generalization ability and a good learning ability. Experimental results prove that the cross validation training accuracy of TWSVM using the mixed kernel function averagely increases 2%. Grid search is usually applied in parameter optimization of TWSVM, but it heavily depends on experience. Therefore, the hybrid particle swarm algorithm is introduced. It can intelligently and rapidly find the global optimum. Experiments prove that its training accuracy is better than that of the classical particle swarm algorithm by 5%.
Twin support vector machine (TWSVM) is a new development of support vector machine (SVM) algorithm. It has the smaller computation scale and the stronger ability to cope with unbalanced problems. In this paper, TWSVM is introduced into aircraft engine gas path fault diagnosis. The generalization capacity of Gauss kernel function usually used in TWSVM is relatively weak. So a mixed kernel function is used to improve performance to ensure that the TWSVM algorithm can better balance a strong generalization ability and a good learning ability. Experimental results prove that the cross validation training accuracy of TWSVM using the mixed kernel function averagely increases 2%. Grid search is usually applied in parameter optimization of TWSVM, but it heavily depends on experience. Therefore, the hybrid particle swarm algorithm is introduced. It can intelligently and rapidly find the global optimum. Experiments prove that its training accuracy is better than that of the classical particle swarm algorithm by 5%.
2018, 35(2):343-352.
DOI: 10.16356/j.1005-1120.2018.02.343
Abstract:
An advanced airload and noise prediction method based on computational fluid dynamics/computational structural dynamics (CFD/CSD) coupling for helicopter rotor has been developed in this paper. In the present method, Navier-Stokes equation is applied as the governing equation, and a moving overset grid system is generated in order to account for the blade motions in rotation, flapping and pitching. The blade structural analysis is based on 14-DOF Euler beam model, and the finite element discretization is conducted on Hamilton's variational principle and moderate deflection theory. Aerodynamic noise is calculated by Farassat 1A formula derived from FW-H equation. Using the developed method, numerical example of UH-60A is performed for aeroelastic loads calculation in a low-speed forward flight, and the calculated results are compared with both those from isolated CFD method and available experimental data. Then, rotor noise is emphatically calculated by CFD/CSD coupling method and compared with the isolated CFD method. The results show that the aerodynamic loads calculated from CFD/CSD method are more satisfactory than those from isolated CFD method, and the exclusion of blade structural deformation in rotor noise calculation may cause inaccurate results in low-speed forward flight state.
An advanced airload and noise prediction method based on computational fluid dynamics/computational structural dynamics (CFD/CSD) coupling for helicopter rotor has been developed in this paper. In the present method, Navier-Stokes equation is applied as the governing equation, and a moving overset grid system is generated in order to account for the blade motions in rotation, flapping and pitching. The blade structural analysis is based on 14-DOF Euler beam model, and the finite element discretization is conducted on Hamilton's variational principle and moderate deflection theory. Aerodynamic noise is calculated by Farassat 1A formula derived from FW-H equation. Using the developed method, numerical example of UH-60A is performed for aeroelastic loads calculation in a low-speed forward flight, and the calculated results are compared with both those from isolated CFD method and available experimental data. Then, rotor noise is emphatically calculated by CFD/CSD coupling method and compared with the isolated CFD method. The results show that the aerodynamic loads calculated from CFD/CSD method are more satisfactory than those from isolated CFD method, and the exclusion of blade structural deformation in rotor noise calculation may cause inaccurate results in low-speed forward flight state.
2018, 35(2):353-360.
DOI: 10.16356/j.1005-1120.2018.02.353
Abstract:
Perturbation to symmetry and adiabatic invariants are studied for the fractional Lagrangian system and the fractional Birkhoffian system in the sense of Riemann-Liouville derivatives. Firstly, the fractional Euler-Lagrange equation, the fractional Birkhoff equations as well as the fractional conservation laws for the two systems are listed. Secondly, the definition of adiabatic invariant for fractional mechanical system is given, then perturbation to symmetry and adiabatic invariants are established for the fractional Lagrangian system and the fractional Birkhoffian system under the special and general infinitesimal transformations, respectively. Finally, two examples are devoted to illustrate the results.
Perturbation to symmetry and adiabatic invariants are studied for the fractional Lagrangian system and the fractional Birkhoffian system in the sense of Riemann-Liouville derivatives. Firstly, the fractional Euler-Lagrange equation, the fractional Birkhoff equations as well as the fractional conservation laws for the two systems are listed. Secondly, the definition of adiabatic invariant for fractional mechanical system is given, then perturbation to symmetry and adiabatic invariants are established for the fractional Lagrangian system and the fractional Birkhoffian system under the special and general infinitesimal transformations, respectively. Finally, two examples are devoted to illustrate the results.
2018, 35(2):361-370.
DOI: 10.16356/j.1005-1120.2018.02.361
Abstract:
A fast and accurate algorithm is established in this paper to increase the precision of ballistic trajectory prediction. The algorithm is based on the six-degree-of-freedom (6DOF) trajectory equations, to estimate the projectile attitude angles in every measuring time. Hereby, the algorithm utilizes the Davidon-Fletcher-Powell (DFP) method to solve nonlinear equations and Doppler radar trajectory test information containing only position coordinates of the projectile to reconstruct the angular information. The ″position coordinates by the test″ and ″angular displacements by reconstruction″ at the end phase of the radar measurement are used as an initial value for the trajectory computation to extrapolate the trajectory impact point. The numerical simulations validate the proposed method and demonstrate that the estimated impact point agrees very well with the real one. Morover, other artillery trajectory can be predicted by the algorithm, and other trajectory models, such as 4DOF and 5DOF models, can also be incorporated into the proposed algorithm.
A fast and accurate algorithm is established in this paper to increase the precision of ballistic trajectory prediction. The algorithm is based on the six-degree-of-freedom (6DOF) trajectory equations, to estimate the projectile attitude angles in every measuring time. Hereby, the algorithm utilizes the Davidon-Fletcher-Powell (DFP) method to solve nonlinear equations and Doppler radar trajectory test information containing only position coordinates of the projectile to reconstruct the angular information. The ″position coordinates by the test″ and ″angular displacements by reconstruction″ at the end phase of the radar measurement are used as an initial value for the trajectory computation to extrapolate the trajectory impact point. The numerical simulations validate the proposed method and demonstrate that the estimated impact point agrees very well with the real one. Morover, other artillery trajectory can be predicted by the algorithm, and other trajectory models, such as 4DOF and 5DOF models, can also be incorporated into the proposed algorithm.
2018, 35(2):371-382.
DOI: 10.16356/j.1005-1120.2018.02.371
Abstract:
Conventional method for hose-drogue model of aerial refueling system is known to be complex due to the flexible body of hose. And as reported, drogues are unstable in atmospheric turbulence, which greatly decreases docking success rates. This paper proposes a dynamic model for a hose-drogue aerial refueling system based on Kane equation and rigid multi-body dynamics, and analyzes its performance. Furthermore, the nonlinear dynamic model is linearized at the equilibrium point and simplified from full order to 2nd order. Based on the simplified 2nd order model, active control strategies, including proportion integral derivative(PID) and liner quadratic regulator(LQR) control laws, are designed to inhibit the pendulum movement of drogue due to, atmospheric turbulences. Numerical simulation results show the significant correctness of the proposed dynamic model by steady-state drag and balance position of drogue when the tanker flights under different conditions. Moreover, the steady state position error varies within 1 cm, thanks to either controller, when the drogue suffers from moderate-level atmospheric turbulences. Further, the PID controller exhibits better control effect and higher control precision than LQR controller.
Conventional method for hose-drogue model of aerial refueling system is known to be complex due to the flexible body of hose. And as reported, drogues are unstable in atmospheric turbulence, which greatly decreases docking success rates. This paper proposes a dynamic model for a hose-drogue aerial refueling system based on Kane equation and rigid multi-body dynamics, and analyzes its performance. Furthermore, the nonlinear dynamic model is linearized at the equilibrium point and simplified from full order to 2nd order. Based on the simplified 2nd order model, active control strategies, including proportion integral derivative(PID) and liner quadratic regulator(LQR) control laws, are designed to inhibit the pendulum movement of drogue due to, atmospheric turbulences. Numerical simulation results show the significant correctness of the proposed dynamic model by steady-state drag and balance position of drogue when the tanker flights under different conditions. Moreover, the steady state position error varies within 1 cm, thanks to either controller, when the drogue suffers from moderate-level atmospheric turbulences. Further, the PID controller exhibits better control effect and higher control precision than LQR controller.
2018, 35(2):383-396.
DOI: 10.16356/j.1005-1120.2018.02.383
Abstract:
A parachute-payload model with randomize wind gust is developed to study the landing accuracy of the parachute decelerator system,which can be exactly described by the landing site distribution. The research focuses on the steady descent phase of the parachute descent process, so the parachute and the payload suspension formulation during the phase are mainly discussed. In addition, since the wind effects have a significant impact on the land site distribution of the passive decelerator system and it is difficult to obtain the exact wind profile in practice, major features of parachute-payload system are studied via the randomized wind gust formulation. As the randomized wind gust formulation is adopted, the wind effect can be considered without the exact wind gust profile and the parachute aerodynamic simulation can be fulfilled with uncertainties.Finally, the model is validated and discussed, and the parachute land site distributions with different wind randomize profiles are presented for comparison. The results show that when parachute is less stable, the land site tends to have a larger variance.
A parachute-payload model with randomize wind gust is developed to study the landing accuracy of the parachute decelerator system,which can be exactly described by the landing site distribution. The research focuses on the steady descent phase of the parachute descent process, so the parachute and the payload suspension formulation during the phase are mainly discussed. In addition, since the wind effects have a significant impact on the land site distribution of the passive decelerator system and it is difficult to obtain the exact wind profile in practice, major features of parachute-payload system are studied via the randomized wind gust formulation. As the randomized wind gust formulation is adopted, the wind effect can be considered without the exact wind gust profile and the parachute aerodynamic simulation can be fulfilled with uncertainties.Finally, the model is validated and discussed, and the parachute land site distributions with different wind randomize profiles are presented for comparison. The results show that when parachute is less stable, the land site tends to have a larger variance.
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