Demodulation of the overlapping reflection spectrum of serial FBGs based on a weighted differential evolution algorithm.

This study addresses the wavelength demodulation problem of the overlapping reflection spectrum of serial fiber Bragg gratings (FBGs) with nearly-identical wavelength. Specifically, a novel demodulation model for the overlapping reflection spectrum was presented based on spectrum similarity, and this model encodes FBGs through reflectivity. Subsequently, a weighted differential evolution algorithm was employed to calculate the FBG wavelengths. And the factors affecting the demodulation accuracy of the proposed method were simulated and analyzed. Finally, the proposed method was applied to demodulate the overlapping reflection spectra of serial FBGs. The experiment results indicate that the proposed method is suitable for completely overlapping, partially overlapping, and non-overlapping reflection spectra of serial FBGs. The wavelength demodulation accuracy demonstrated here in fully overlapping situations for two, three, and four FBGs was only 4.5, 14.9, and 24.6 pm, respectively.

A Novel Adaptive Time-Frequency Filtering Approach to Enhance the Ultrasonic Inspection of Stainless Steel Structures.

Ultrasonic nondestructive testing (NDT) provides a valuable insight into the integrity of stainless steel structures, but the noise caused by the scattering of stainless steel microstructure often limits the effectiveness of inspection. This work presents a novel adaptive filtering approach to enhance the signal-to-noise ratio (SNR) of a measured ultrasonic signal from the inspection of a stainless steel component, enabling the detection of hidden flaws under strong noise. After the spectral modeling of the noisy ultrasonic NDT signal, the difference between the spectral characteristics of a flaw echo and that of grain noise is highlighted, and a reference spectrum model to estimate the frequency spectrum of the echo reflected by any possible flaw is developed. Then, the signal is segmented and the similarity between the spectra of data segments and the reference spectra is evaluated quantitatively by the spectral similarity index (SSI). Based on this index, an adaptive time-frequency filtering scheme is proposed. Each data segment is processed by the filtering to suppress the energy of noise. The processed data segments are recombined to generate the de-noised signal after multiplying weighting coefficients, which again is determined by the SSI. The performance of the proposed method for SNR enhancement is evaluated by both the simulated and experimental signal and the effectiveness has been successfully demonstrated.

Detection of Ultrasonic Stress Waves in Structures Using 3D Shaped Optic Fiber Based on a Mach-Zehnder Interferometer.

This work proposes a 3D shaped optic fiber sensor for ultrasonic stress waves detection based on the principle of a Mach–Zehnder interferometer. This sensor can be used to receive acoustic emission signals in the passive damage detection methods and other types of ultrasonic signals propagating in the active damage detection methods, such as guided wave-based methods. The sensitivity of an ultrasonic fiber sensor based on the Mach–Zehnder interferometer mainly depends on the length of the sensing optical fiber; therefore, the proposed sensor achieves the maximum possible sensitivity by wrapping an optical fiber on a hollow cylinder with a base. The deformation of the optical fiber is produced by the displacement field of guided waves in the hollow cylinder. The sensor was first analyzed using the finite element method, which demonstrated its basic sensing capacity, and the simulation signals have the same characteristics in the frequency domain as the excitation signal. Subsequently, the primary investigations were conducted via a series of experiments. The sensor was used to detect guided wave signals excited by a piezoelectric wafer in an aluminum plate, and subsequently it was tested on a reinforced concrete beam, which produced acoustic emission signals via impact loading and crack extension when it was loaded to failure. The signals obtained from a piezoelectric acoustic emission sensor were used for comparison, and the results indicated that the proposed 3D fiber optic sensor can detect ultrasonic signals in the specific frequency response range.

Complex sparse Bayesian learning for guided wave dispersion curve estimation in plate-like structures.

This paper proposes a new dispersion curve estimation method that employs the complex sparse Bayesian learning (CSBL). It is well accepted that guided wave packets are distorted because of the differences in propagation velocities at different frequencies; thus, the preceding velocity-frequency curve estimation is beneficial for wave packet recovery, feature recognition and defect localization. Conventional dispersion curve estimation methods, such as two-dimensional Fourier transform and multiple signal classification, are suitable for array signal and are restricted by the transducer aperture, leading to a small application scope. According to the frequency-response model of the guided wave, for each frequency, the responses obtained by the transducers can be sparsely represented based on an overcomplete dictionary matrix constructed using multiple discretized wavenumbers and known distances. A CSBL algorithm was developed to infer the posterior probability density function of the weight vector in the sparse representation. The non-zero elements in the sparse weight vector mean that the corresponding dictionary atoms indicated wavenumbers are contained in the frequency response, and the velocity-frequency curve can be finally derived from the wavenumber-frequency curve. The proposed CSBL method has a satisfactory capability to solve this sparse representation of the complex frequency response because a hierarchical form of the Laplace prior is employed to achieve a high degree of sparsity of the weight vector. This method effectively incorporates the real and imaginary parts of the complex frequency response by employing the same hyperparameter to integrate the known information. This method requires only a few randomly placed transducers; thus, it has a wide range of applications. The effectiveness of the proposed approach was validated using multiple guided-wave signals obtained through numerical simulations and an experimental study on a plate structure.

Microbial regulation of soil carbon properties under nitrogen addition and plant inputs removal.

BACKGROUND: Soil microbial communities and their associated enzyme activities play key roles in carbon cycling in terrestrial ecosystems. Soil microbial communities are sensitive to resource availability, but the mechanisms of microbial regulation have not been thoroughly investigated. Here, we tested the mechanistic relationships between microbial responses and multiple interacting resources. METHODS: We examined soil carbon properties, soil microbial community structure and carbon-related functions under nitrogen addition and plant inputs removal (litter removal (NL), root trench and litter removal (NRL)) in a pure Larix principis-rupprechtii plantation in northern China. RESULTS: We found that nitrogen addition affected the soil microbial community structure, and that microbial biomass increased significantly once 100 kg ha-1 a-1 of nitrogen was added. The interactions between nitrogen addition and plant inputs removal significantly affected soil bacteria and their enzymatic activities (oxidases). The NL treatment enhanced soil microbial biomass under nitrogen addition. We also found that the biomass of gram-negative bacteria and saprotrophic fungi directly affected the soil microbial functions related to carbon turnover. The biomass of gram-negative bacteria and peroxidase activity were key factors controlling soil carbon dynamics. The interactions between nitrogen addition and plant inputs removal strengthened the correlation between the hydrolases and soil carbon. CONCLUSIONS: This study showed that nitrogen addition and plant inputs removal could alter soil enzyme activities and further affect soil carbon turnover via microbial regulation. The increase in soil microbial biomass and the microbial regulation of soil carbon both need to be considered when developing effective sustainable forest management practices for northern China. Moreover, further studies are also needed to exactly understand how the complex interaction between the plant and below-ground processes affects the soil microbial community structure.

Sparse representation for Lamb-wave-based damage detection using a dictionary algorithm.

Lamb waves are being investigated extensively for structural health monitoring (SHM) because of their characteristics of traveling long distances with little attenuation and sensitivity to minor local damage in structures. However, Lamb waves are dispersive, which results in the complex overlap of waveforms in the damage detection applications of the SHM community. This paper proposes a sparse representation strategy based on an l1-norm optimization algorithm for guided-Lamb-wave-based inspections. A comprehensive dictionary is designed containing various waveforms under diverse conditions so that the received waveform can be decomposed into a spatial domain for the identification of damage location. Furthermore, the l1-norm optimization algorithm is employed to pursue the sparse solution related to the physical damage location. The functionality of the created dictionary is validated by both metal beam and composite wind turbine experiments. The results indicate a great potential for the proposed sparse representation using a dictionary algorithm, which provides an effective alternative approach for damage detection.

Guided torsional wave generation of a linear in-plane shear piezoelectric array in metallic pipes.

Cylindrical guided waves based techniques are effective and promising tools for damage detection in long pipes. The essential operations are generation and reception of guided waves in the structures utilizing transducers. A novel in-plane shear (d36 type) PMNT wafer is proposed to generate and receive the guided wave, especially the torsional waves, in metallic pipes. In contrast to the traditional wafer, this wafer will directly introduce in-plane shear deformation when electrical field is conveniently applied through its thickness direction. A single square d36 PMNT wafer is bonded on the surface of the pipe positioned collinearly with its axis, when actuated can predominantly generate torsional (T) waves along the axial direction, circumferential shear horizontal (C-SH) waves along circumferential direction, and other complex cylindrical Lamb-like wave modes along other helical directions simultaneously. While a linear array of finite square size d36 PMNT wafers was equally spaced circumferentially, when actuated simultaneously can nearly uniform axisymmetric torsional waves generate in pipes and non-symmetric wave modes can be suppressed greatly if the number of the d36 PMNT wafer is sufficiently large. This paper first presents the working mechanism of the linear d36 PMNT array from finite element analysis (FEA) by examining the constructive and destructive displacement wavefield phenomena in metallic pipes. Furthermore, since the amplitude of the received fundamental torsional wave signal strongly depends on frequency, a series of experiments are conducted to determine the frequency tuning curve for the torsional wave mode. All results indicate the linear d36 PMNT array has potential for efficiently generating uniform torsional wavefield of the fundamental torsional wave mode, which is more effective in monitoring structural health in metallic pipes.

Fundamental understanding of wave generation and reception using d(36) type piezoelectric transducers.

A new piezoelectric wafer made from a PMN-PT single crystal with dominant piezoelectric coefficient d36 is proposed to generate and detect guided waves on isotropic plates. The in-plane shear coupled with electric field arising from the piezoelectric coefficient is not usually present for conventional piezoelectric wafers, such as lead zirconate titanate (PZT). The direct piezoelectric effect of coefficient d36 indicates that under external in-plane shear stress the charge is induced on a face perpendicular to the poled z-direction. On thin plates, this type of piezoelectric wafer will generate shear horizontal (SH) waves in two orthogonal wave propagation directions as well as two Lamb wave modes in other wave propagation directions. Finite element analyses are employed to explore the wave disturbance in terms of time-varying displacements excited by the d36 wafer in different directions of wave propagation to understand all the guided wave modes accurately. Experiments are conducted to examine the voltage responses received by this type of wafer, and also investigate results of tuning frequency and effects of d31 piezoelectric coefficient, which is intentionally ignored in the finite element analysis. All results demonstrate the main features and utility of proposed d36 piezoelectric wafer for guided wave generation and detection in structural health monitoring.