Chirp Excitation Research Articles

Chirp excitation for natural frequency optical coherence elastography.

Optical coherence elastography (OCE) has recently been used to characterize the natural frequencies of delicate tissues (e.g., the in vivo human cornea) with sub-micron tissue oscillation magnitudes. Here, we investigate broadband spectrum sample stimulation using a contact-based piezoelectric transducer (PZT) chirp excitation and compare its performance with a non-contact, air-pulse excitation for OCE measurements on 1.0-7.5% agar phantoms and an ex vivo porcine cornea under intraocular pressures (IOPs) of 5-40 mmHg. The 3-ms duration air-pulse generated a ∼0-840 Hz excitation spectrum, effectively quantifying the first-order natural frequencies in softer samples (e.g., 1.0%-4.0% agar: 239-782 Hz, 198 Hz/%; porcine cornea: 68-414 Hz, 18 Hz/mmHg, IOP: 5-25 mmHg), but displayed limitations in measuring natural frequencies for stiffer samples (e.g., 4.5%-7.5% agar, porcine cornea: IOP ≥ 30 mmHg) or higher order natural frequency components. In contrast, the chirp excitation produced a much wider spectrum (e.g., 0-5000 Hz), enabling the quantification of both first-order natural frequencies (1.0%-7.5% agar: 253-1429 Hz, 181 Hz/%; porcine cornea: 76-1240 Hz, 32 Hz/mmHg, IOP: 5-40 mmHg) and higher order natural frequencies. A modified Bland-Altman analysis (mean versus relative difference in natural frequency) showed a bias of 20.4%, attributed to the additional mass and frequency introduced by the contact nature of the PZT probe. These findings, especially the advantages and limitations of both excitation methods, can be utilized to validate the potential application of natural frequency OCE, paving the way for the ongoing development of biomechanical characterization methods utilizing sub-micron tissue oscillation features.

Deep-Learning-based damage detection of an experimentally tested full-scale wind turbine blade.

Reducing the Operation and Maintenance (O&M) costs of Wind Farms can substantially contribute towards adopting environmentally sustainable and cost effective energy sources. O&M costs in Wind Turbines can account up to 50% of the Turbine’s whole life cycle, with the majority of it being the frequent manual inspection needed for Wind Turbine Blades (WTB). Vibration-based structural health monitoring (SHM) approaches can be used for detecting WTB damages in an early state, before they lead to catastrophic failure, while they can be used to perform inspection on an informed basis, reducing O&M costs. In the present study, a data-driven damage detection framework is developed for WTBs. A Finite Element Model (FEM) of a full-scale WTB (the Aventa AV-7 “Light Wind Turbine”, sold under the Leichtwindanlagen© name) is developed in ABAQUS FEA using sparce material properties and dimensions and subsequently modified to match a physical WTB. Damage is modelled in the form of a Trailing Edge (TE) longitudinal crack propagated in a stepwise manner. The FE model is updated based on the geometry altering and material property degrading effects of the TE crack. Numerical simulations are performed to obtain the dynamic responses of the blade, under white noise and chirp excitation. A damage detection framework is then developed using Auto-Regressive, with exogenous excitation (ARX) or without (AR), models and its Nonlinear counterparts NARX and NAR models. In addition, model dimensionality reduction is performed using Principal Component Analysis (PCA) and Deep-Autoencoders (D-AE). The results are presented in terms of Receiver Operating Characteristics (ROC) curves.

Decision fusion based on vibrometric data for increase of reliability of damage detection and indentification for plate-like structures

In the realm of structural health monitoring (SHM) for plate-like structures, the need for accurate and reliable damage detection and identification techniques is paramount. This paper explores the application of decision fusion algorithms to vibrometric data, with a focus on increasing the reliability of damage assessment for such structures. The methodology involves leveraging diverse input data sources, including variations in data processing algorithms, excitation parameters, and multiple measurements. By amalgamating these sources of diversity, we aim to mitigate measurement noise and amplify damage indications, ultimately enhancing the precision of the final diagnostic outcome. The study presents results obtained from laser vibrometry measurements on a 10 mm thick aluminum sample containing flat-bottom holes of varying diameters. A network of 12 PZT transducers was used to excite elastic waves, with impulse and chirp excitation techniques employed. Convolution techniques using OpenCV libraries were applied for data processing and fusion. The outcomes reveal a significant reduction in background noise, demonstrating the effectiveness of the fusion approach. Furthermore, the presentation outlines a roadmap for the future development of this methodology, which includes automating data processing, evaluating the impact of damage indicators, processing parameters and usage of different excitation transducers.

Spatially encoded pure-shift diffusion-ordered NMR spectroscopy yielded by chirp excitation

Spatially-encoded diffusion-ordered NMR spectroscopy (SPEN-DOSY) has emerged as a new time-efficient tool for the analysis of mixtures of small molecules in solution. Time efficiency is achieved using the concept of spatial parallelization of the effective gradient area, instead of the sequential incrementation used in conventional diffusion experiments. The data acquired with such sequences are then usually processed to extract diffusion coefficients, but cases when peak overlap in the 1H spectrum are difficult to address. Such limitation in conventional diffusion experiments is addressed via using the Pure Shift Yielded by CHirp Excitation (PSYCHE)-iDOSY sequence. Here we have adapted the PSYCHE-iDOSY sequence by using echo planar spectroscopic imaging (EPSI) to acquire SPEN-DOSY data. The pure shift mode of PSYCHE separates the overlapped components and a modified Stejskal-Tanner equation is used to extract the corresponding diffusion coefficient. The primary results obtained with the above-mentioned mixtures seem to open the possibility of separating complex mixtures in less time than PSYCHE-iDOSY.

Compact chirped fiber Bragg gratings for single-photon generation from quantum dots

A scalable source of single photons is a key constituent of an efficient quantum photonic architecture. To realize this, it is beneficial to have an ensemble of quantum emitters that can be collectively excited with high efficiency. Semiconductor quantum dots hold great potential in this context due to their excellent photophysical properties. Spectral variability of quantum dots is commonly regarded as a drawback introduced by the fabrication method. However, this is beneficial to realize a frequency-multiplexed single-photon platform. Chirped pulse excitation, relying on the so-called adiabatic rapid passage, is the most efficient scheme to excite a quantum dot ensemble due to its immunity to individual quantum dot parameters. Yet, the existing methods of generating chirped laser pulses to excite a quantum emitter are bulky, lossy, and mechanically unstable, which severely hampers the prospects of a quantum dot photon source. Here, we present a compact, robust, and high-efficiency alternative for chirped pulse excitation of solid-state quantum emitters. Our simple plug-and-play module consists of chirped fiber Bragg gratings, fabricated via femtosecond inscription, to provide high values of dispersion in the near-infrared spectral range, where the quantum dots emit. We characterize and benchmark the performance of our method via chirped excitation of a GaAs quantum dot, establishing high-fidelity single-photon generation. Our highly versatile chirping module coupled to a photon source is a significant milestone toward realizing practical quantum photonic devices.

The microwave spectra of the conformers of n-butyl nitrate

The microwave spectrum of n-butyl nitrate was recorded in the 5 to 20 GHz frequency range using broadband chirp and narrowband pulse excitation molecular jet Fourier transform microwave spectrometers. A quantum chemistry structural analysis yielded thirteen stable conformers. Among them, the five most energetically stable conformers were observed in the experimental spectra. The most stable conformer features a butyl chain with an anti-gauche-anti conformation (AGA) where the γ-carbon atom is about 64° out of the nitrate plane. For this conformer, spectra of all 13C and 15N minor isotopologues could be measured. The conformer with a straight butyl chain (AAA), and three other conformers (GAA, GGA, and AGG) were also observed. Accurate rotational constants, centrifugal distortion constants, and 14N nuclear quadrupole coupling constants could be deduced and compared to the theoretical values.

Lamb wave based damage imaging under nonlinear chirp excitation

Considering a trade-off between temporal-spatial resolution and multi-mode nature of Lamb waves, tone bursts with short durations are usually used as excitations in Lamb wave based damage detection. A short-duration excitation usually requires a large amplitude to carry sufficient energy so as to obtain response signals with enough signal-to-noise ratio and cover a large inspection area. In this paper, an alternative Lamb wave damage imaging method using nonlinear chirp (nonlinear frequency modulation, NLFM) excitation with a long duration and a small amplitude is proposed. The signal processing techniques of pulse compression and dispersion compensation are adopted to compress the long-duration wave packets of response signals into short ones. Compared with conventional tone burst excitations with short durations and small amplitudes, due to the long duration of the nonlinear chirp excitation and the use of pulse compression, sufficient energy can be applied to transducers under small amplitude excitations so the image contrast in imaging will not degrade. Furthermore, as large amplitude excitations are no longer required, high voltage amplifiers are not necessary so the hardware of the Lamb wave testing system is simplified. Experiments on a carbon steel plate with an artificial crack are carried out and Lamb wave signals are collected using a linear array consisting of nine PZTs. Experimental results under the NLFM signal and conventional tone bursts are provided. Experimental results show that under the condition of the same excitation amplitude, the proposed method under the NLFM excitation can achieve better imaging quality compared with methods under conventional tone bursts.

A comparative study on detection of polymer-shelled microbubbles by different excitation pulses.

Contrast agents are widely used in ultrasound imaging. Many imaging techniques have been developed to improve the contrast between tissue and the agents, based on the nonlinear response of microbubbles. In this study, heterodyne excitation was introduced and was compared with traditional sinusoidal signal and chirp excitation for visualizing polymer-shelled microbubbles and degassed water in a tissue-mimicking phantom. Pulse inversion technique was implemented under plane wave (PW) and focused imaging mode. Image enhancement was evaluated by contrast-to-tissue ratio (CTR) at different transmitting peak negative pressures (PNPs). Experimental results showed that heterodyne excitation had a better suppression effect on tissue signals in PW imaging. The CTR reached an approximation of 17 dB at a low peak negative pressure, which was much higher compared to other excitations. In focused wave imaging, a saturation threshold of CTR was observed for the sinusoidal wave burst and chirp excitation at high PNPs. Heterodyne excitation showed considerable contrast-to-noise ratio under both imaging modes. The response of a polymer-shelled microbubble under heterodyne excitation was simulated. Simulations suggest that in future work, specific filters are required to extract the nonlinear components, such as at the two-peak frequencies around fundamental frequency, to achieve a better image enhancement effect.

Subsurface impact damage imaging for composite structures using 3D digital image correlation

An integrated system is proposed to visualize subsurface barely visible impact damage (BVID) in composite structures using three-dimensional (3D) digital image correlation (3D DIC). This system uses a pair of digital cameras to record video frames in the field-of-view (FOV) of the structure’s surface, capturing the wavefield generated via chirp excitation in the near-ultrasonic frequency range. Significant pitfalls of previous efforts of damage imaging using two-dimensional DIC have been largely mitigated. First, 3D DIC enables capturing out-of-plane displacements, which are much larger in amplitude versus in-plane displacements that a single camera would be limited to sensing, thus increasing the signal-to-noise ratio. This enhancement in turn increases the sensitivity of the stereo-camera system. Second, a total wave energy (TWE) damage imaging condition is proposed to visualize the local damage region. The monogenic signal obtained via Reisz transform (RT) is employed to compute the instantaneous amplitude, with which the local wave energy can be calculated spatially over time. Since a high displacement amplitude and thus high wave energy will occur in the damage region due to the local resonance, the proposed TWE imaging condition can relax the Nyquist sampling requirement, unlike guided-wave-based structural health monitoring techniques which require fully reconstructing the wavefield and wave modes through sampling that satisfies the Nyquist criterion. As such, a much lower camera frame rate is adequate for the proposed system. Consequently, the maximum spatial resolution of the camera for a given FOV can be achieved at the expense of a reduced frame rate. With the maximized pixel resolution and reduced frame rate for employing the TWE imaging condition, composite structures can be inspected or monitored with a larger FOV. As a result, there is no longer any need to apply signal enhancement techniques, such as sample interleaving, image stitching, or averaging, to increase the effective performance of the camera. Rather than needing thousands of repeated videos for minimizing the incoherent noise, only a single stereo-video with a few seconds of sampling duration is necessary for damage imaging. The use of a powerful piezo-shaker also increases the wave signal amplitude and further enhances sensitivity without permanent adhesion. To demonstrate this stereo-camera concept with the TWE imaging condition, the system was used to image damage in two carbon fiber reinforced polymer composite honeycomb panels, which had been subjected to low-velocity impacts (2 J). For each panel, two excitation configurations were used to verify the robustness of the system. Initial damage maps produced for a 100 × 100-mm FOV using a three-second stereo-video show accurate damage imaging ability that is independent of excitation location and comparable to benchmark damage images computed from laser Doppler vibrometer data and those gathered from ultrasonic and X-ray computerized tomography scans. This efficient and reliable integrated system demonstrated high potential for in-time damage inspection on composite aircraft and other critical structures.

Performance of a chirped-pulse Fourier transform millimeter wave spectrometer in the range of 75-110 GHz.

We present a home-built chirped-pulse Fourier transform millimeter wave (CP-FTMMW) spectrometer. The setup is devoted to the sensitive recording of high-resolution molecular spectroscopy in the W band between 75 and 110GHz. We describe the experimental setup in detail, including a characterization of the chirp excitation source, the optical beam path, and the receiver. The receiver is a further development of our 100GHz emission spectrometer. The spectrometer is equipped with a pulsed jet expansion and a DC discharge. Spectra of methyl cyanide as well as hydrogen cyanide (HCN) and hydrogen isocyanide (HNC) products from the DC discharge of this molecule are recorded to characterize the performance of the CP-FTMMW instrument. The formation of the HCN isomer is favored by a factor of 63 with respect to HNC. Hot/cold calibration measurements enable a direct comparison of the signal and noise levels of the CP-FTMMW spectra to those of the emission spectrometer. For the CP-FTMMW instrument, we find many orders of magnitude of signal enhancement and a much stronger noise reduction due to the coherent detection scheme.

Damage Identification for Isotropic Structures Using Lamb Wave Based on a Reference-Free Location Imaging Method

A Lamb wave-based reference-free damage localization imaging algorithm is proposed for online determination of the imperceptible defects due to harsh service environments, complex alternating, and impact loads in the plain isotropic structures (mainly aluminum alloys), which are crucial components of aircraft skin, bogies, and underframes of high-speed train, so as to overcome the deficiencies of the majority of localization imaging methods that rely on reference data in a healthy state. The analyses were implemented by configuring specific transducer arrays to pick alternate reference signals from the existing transmitter–receiver paths. A chirp excitation approach was introduced to choose the actuation frequency of ultrasonic Lamb wave more concisely and effectively. Simulations and experiments were conducted to recognize and pinpoint the defects in four damage scenarios in aluminum alloy plates with 12 surface-mounted piezoelectric transducers, and the damage area identified by the proposed methodology was compatible with the genuine position. The results between simulations and experiments are likewise essentially consistent, demonstrating that the proposed algorithm is able to identify and localize damage in plain isotropic structures without the requirement of healthy reference signals.

High-resolution NMR spectroscopy for measuring complex samples based on chemical-shift-difference selection.

NMR spectroscopy serves as an immensely powerful tool for component assignments and molecular structure elucidations. However, proton NMR spectra are generally trapped with spectral congestion caused by limited frequency differences and complex multiplets. 2D NMR can effectively relieve spectral congestion, but its resolution and acquisition efficiency are restricted by the broad spectral bandwidth. Herein, we introduce an NMR method based on chemical-shift-difference selection by chirp excitation to record high-resolution 2D NMR spectra for extracting coupling correlation networks and multiplet structures, suitable for measurements on complex samples. The performance of the proposed method is illustrated in determining diastereotopic methylene protons, small frequency-difference coupled proton pairs of furanose, pyranose and benzene rings. This study is expected to benefit molecular structure elucidation and composition analysis of complex samples in chemistry, biochemistry and metabonomics.

Non-Contact Vibro-Acoustic Object Recognition Using Laser Doppler Vibrometry and Convolutional Neural Networks

Laser Doppler vibrometers (LDVs) have been widely adopted due to their large number of benefits in comparison to traditional contacting vibration transducers. Their high sensitivity, among other unique characteristics, has also led to their use as optical microphones, where the measurement of object vibration in the vicinity of a sound source can act as a microphone. Recent work enabling full correction of LDV measurement in the presence of sensor head vibration unlocks new potential applications, including integration within autonomous vehicles (AVs). In this paper, the common AV challenge of object classification is addressed by presenting and evaluating a novel, non-contact vibro-acoustic object recognition technique. This technique utilises a custom set-up involving a synchronised loudspeaker and scanning LDV to simultaneously remotely solicit and record responses to a periodic chirp excitation in various objects. The 864 recorded signals per object were pre-processed into spectrograms of various forms, which were used to train a ResNet-18 neural network via transfer learning to accurately recognise the objects based only on their vibro-acoustic characteristics. A five-fold cross-validation optimisation approach is described, through which the effects of data set size and pre-processing type on classification accuracy are assessed. A further assessment of the ability of the CNN to classify never-before-seen objects belonging to groups of similar objects on which it has been trained is then described. In both scenarios, the CNN was able to obtain excellent classification accuracy of over 99.7%. The work described here demonstrates the significant promise of such an approach as a viable non-contact object recognition technique suitable for various machine automation tasks, for example, defect detection in production lines or even loose rock identification in underground mines.

RESEARCH ON MAGNETO–ACOUSTIC IMAGING UNDER CHIRP CURRENT EXCITATION

Magneto–acoustic signals reflect the electrical properties of tissues, which is meaningful for the diagnosis of tumors, bleeding and other diseases. The low signal-to-noise ratio (SNR) of the magneto–acoustic signals limits the image quality of the magneto–acoustic imaging. A chirp coded excitation signal processing method for magneto–acoustic imaging is proposed in this paper. The SNR of magneto–acoustic signal is improved. In this paper, magneto–acoustic signals under different pulse widths chirp coded excitation are studied by simulation and experimental measurement. The SNRs of the magneto–acoustic signals are increased by 7.5, 16.3, 42.2, and 90.1 times under 10, 20, 50 and 100[Formula: see text][Formula: see text]s chirp excitation, respectively, for the beef and copper ring sample. At the same time, the processing time was significantly shortened to 1.2% of the average method under the single pulse excitation. The chirp coded method is of great significance to improve the SNR of magneto–acoustic signals, image quality and imaging efficiency.

PREFACE: A SPECIAL SELECTION ON EMERGING TECHNIQUES FOR BIOMECHANICS–PART II

PREFACE: A SPECIAL SELECTION ON EMERGING TECHNIQUES FOR BIOMECHANICS–PART II

In situ seismic testing for experimental modal analysis of civil structures

This paper presents a novel excitation method for in situ experimental modal analysis (EMA) and compares its performance to ambient vibration analysis, also known as operational modal analysis (OMA). The method consists of base excitation through ground accelerations generated through a large mobile shaker, a unique form of building excitation which has not been studied to date. The controllable and repeatable nature of the excitation complements some limitations of OMA, including inconsistent excitation conditions and low energy at high frequencies. The method is applied to an instrumented eleven-story building in Austin, Texas, resulting in observations of significant energy input up to 50 Hz. The high input bandwidth is essential to characterizing high order modes which ambient sources do not excite. Using a five-minute set of multiple 20-s chirp excitations from 5 to 50 Hz in two directions (vertical and transverse), it is shown that the in situ seismic EMA yields modes which are not identified through standard ambient OMA. The differences in identification methods were most noticeable above 7 Hz, where vertical contributions accounted for a significant portion of the modal response. Above 11 Hz, ambient excitation was too weak for proper OMA, but EMA enabled the identification of high-order “local” modes, although their complete identification was limited by low sensor density. The primary benefit of OMA comes from processing time series of much longer duration (20 min), which reduced variation in most of the modal estimates, given the fairly consistent ambient excitation conditions during testing. Overall, in situ seismic testing is shown to be a viable option for forced vibration testing of very large civil structures. With refinements in the testing methods, the technique could be used as a complement to ambient vibration testing in contexts where the ambient excitation bandwidth is limited or quick, short-term tests are desired.

Study and comparison of pulse compression techniques with three types of excitation for high-temperature EMAT detection

To address the low conversion efficiency and high ultrasonic attenuation in the detection of hot castings and forgings, the pulse compression technique (PCT) is an important and efficient method for improving the signal-to-noise ratio (SNR) and range resolution of ultrasonic echoes. A finite element model was established for the process of detection using a spiral coil electromagnetic acoustic transducer (EMAT) with three types of excitation, these being chirp signals, Barkercoded signals and combined Barker-coded signals, and the PCT processions were also provided. The SNR and range resolution of the PCTs with three types of excitation were compared using simulations and verified by experiments. The self-developed and water-cooled EMAT with three PCTs was used to measure a high-temperature forging and the pulse compression effect was also compared. The results indicate that the PCT with Barker-coded excitation has the highest SNR and the PCT with chirp excitation and combined Barker-coded excitation processes a higher range resolution. When the tested forging is at 710°C and compared with the traditional tone-burst excitation, the SNR from the PCT with combined Barker-coded excitation can be improved by 8.5 dB and the ultrasonic echo width can be reduced by 100%.

Fast Acquisition of High-Quality Nuclear Magnetic Resonance Pure Shift Spectroscopy via a Deep Neural Network.

Pure shift methods improve the resolution of proton nuclear magnetic resonance spectra at the cost of time. The pure shift yielded by chirp excitation (PSYCHE) method is a promising pure shift method. We propose a method of reconstructing the undersampled PSYCHE spectra based on deep learning to accelerate the spectra acquisition. It only takes 17 s to obtain a high-quality pure shift spectrum. The network can completely remove undersampling artifacts and chunking sidebands and improve the signal-to-noise ratio, obtaining completely clean pure shift spectra. The reconstruction quality is better than the iterative soft thresholding method. In addition, the network can differentiate low-level signals and chunking sidebands with similar intensities in the mixture, remove sidebands, and retain signals, promoting correct mixture analysis.

NMR diffusion analysis of catalytic conversion mixtures from lignocellulose biomass using PSYCHE-iDOSY

The component analysis and structure characterization of complex mixtures of biomass conversion remain a challenging work. Hence, developing effective and easy to use techniques is necessary. Diffusion-ordered NMR spectroscopy (DOSY) is a non-selective and non-invasive method capable of achieving pseudo-separation and structure assignments of individual compounds from biomass mixtures by providing diffusion coefficients (D) of the components. However, the conventional 1H DOSY NMR is limited by crowded resonances when analyzing complex mixtures containing similar chemical structure resulting in similar coefficient. Herein we describe the application of an advanced diffusion NMR method, Pure Shift Yielded by CHirp Excitation DOSY (PSYCHE-iDOSY), which can record high-resolution signal diffusion spectra efficiently separating compounds in model and genuine mixture samples from cellulose, hemicellulose and lignin. Complicated sets of isomers (d-glucose/d-fructose/d-mannose and 1,2-/1,5-pentadiol), homologous compounds (ethylene glycol and 1,2-propylene glycol), model compounds of lignin, and a genuine reaction system (furfuryl alcohol hydrogenolysis with ring opening) were successfully separated in the diffusion dimension. The results show that the ultrahigh-resolution DOSY technique is capable of detecting and pseudo-separating the mixture components of C5/C6 sugar conversion products and its derivative hydrogenation/hydrogenolysis from lignocellulose biomass.

On the Optimization of Spread Spectrum Chirps Into Arbitrary Position and Width Pulse Signals. Application to Ultrasonic Sensors and Systems

This work presents in detail a new method for the optimization of rectangular spread spectrum excitation signals for its use in simple and low-cost ultrasonic pulsers, but that could be extended to other applications based on spread spectrum signals. Starting from rectangular linear frequency modulated (RLFM) chirps, it uses the transfer function of the transmitted signal and received echoes from reference specimens to iterate through a recursive algorithm to obtain arbitrary position and width pulse (APWP) signals with the desired bandwidth, maximizing the energy and the flatness of the spectrum, and enhancing the resolution and dynamic range of conventional chirp excitation signals. This optimization procedure can be repeated for any transducer and material, so that it achieves the best performance in each experimental environment. Such characteristics are ideal for Time-of-Flight estimation, imaging, and applications in which spectral regularity is needed, such as the Split Spectrum Processing (SSP) algorithm, which is used as example to test the performance of the proposed excitation signals. It also allows to specify and change the bandwidth reducing the need to change the transducers. The method is tested with different transducers (2 and 5 MHz focused transducers) and complex composite materials (aluminum-carbon aviation composite and high porosity GFRP composite) in immersion setup for imaging applications using SSP algorithm.