Non-contact Vibration Measurement Research Articles

Coupling deflectometry measurements on membranes to the force analysis technique: opportunities and challenges

This work is grounded on the force analysis technique, an identification method that directly uses a structure's equation of motion to formulate an inverse problem, explicitly identifying the force causing the system's motion. This technique has mainly been applied on heavy objects since contact vibration measurements using accelerometers on light and thin structures are biased by the added mass and are complex to setup. Using non-contact and full-field vibration measurements (here, deflectometry), opens the possibility of applying the force analysis technique to such structures. This research aims to investigate the opportunities offered by the identification of space-time varying loadings of various types (acoustical, mechanical, and turbulent boundary layer) all these loadings being applied on a membrane. Through this study, we also strive to highlight the challenges and opportunities brought by of coupling non-contact and full-field measurements on membranes to the force analysis technique.

An impulsive noise filter for rail vibration measurements using a laser Doppler vibrometer on a moving platform

This paper proposes a new impulsive noise (i.e., IN) filter for non-contact rail vibration measurements performed by a laser Doppler vibrometer (i.e., LDV) placed on a moving rail car. The development of the filter is motivated by the fact that such measurements can be contaminated by IN, which is caused by a high level of speckle noise due to the movement of the LDV. Consequently, some portions of the LDV signals can be distorted, leading to missing measurements from some rail segments. The proposed filter consists of two main steps: (i) detecting the signal segments containing the IN (i.e., detection step), and (ii) replacing the detected segments to estimate their IN-free values (i.e., estimation step). The performance of the filter was evaluated on a synthetic signal, which was created by combining a rail vibration signal in the vertical direction (i.e., vibration component) with a speckle noise signal of an LDV placed on a moving platform (i.e., noise component). The reason to use a synthetic signal was to know the vibration and noise components separately. This allowed for the examination of IN’s behavior, which showed that IN manifests itself as artificial peaks as well as high-frequency noise in the proximity of artificial peaks (i.e., artificial fluctuations). Accordingly, the proposed filter was designed to detect and replace both artificial peaks and fluctuations. Qualitative and quantitative evaluations of the filtered synthetic signal showed that the proposed filter exhibited good performance in mitigating the IN.

Band gap generation in cantilever beams through periodic material removal

Traditional methods for generating band gaps in beams usually involve adding periodic elements like tuned mass dampers or masses, or applying complex geometrical changes. This research suggests a subtraction-based method achieved by removing material in the thickness direction through straightforward machining operations, thus forming periodic cells. The numerical studies start with band gap analysis, using periodic theory to assess different periodic cell configurations. This is followed by numerical and experimental studies on cantilever beams, each containing a set number of these periodic cells. Non-contact vibration measurements are conducted on one plain and six machined aluminum beams using a multipoint laser vibrometer and an automated impact hammer. The experimental findings corroborate the band gaps predicted by the numerical model, confirming the effectiveness of this approach. The study notes that the optimal periodicity of the cells and the contrast in thickness vary with the beam’s dimensions, and that the thickness contrast markedly affects the quantity, width, and intensity of the resulting band gaps. These results indicate that (1) periodic material removal in beam-like structures allows improved vibration reduction while mass is reduced, and (2) manufacturing can play a key role in vibration control in simple structures.

Statistical blade tip timing measurement, Part II: High-order cumulant architecture

Blade tip timing (BTT) is a potential non-contact vibration measurement technique for rotating blades owing to its high efficiency and long service life. However, probe layout design and vibration parameter identification are critical challenges in BTT due to its inherent undersampling. To address this issue, we have proposed the concept of statistical BTT measurement which promotes efficient layouts and parameter identification methods by shifting the recovery target from the signal to itself to its statistics. In the first paper of series papers, we have developed covariance architecture for BTT measurement and signal post-processing. In this second part of series papers, we set out to develop BTT measurement from a higher-order statistic perspective. Specifically, we find that the 2qth-order cumulant retains the vibration information (frequency and amplitude) of the signal itself and it can be recovered at lower sampling rates than what is prescribed by the covariance architecture. On this basis, we propose a higher-order cumulant architecture for BTT measurement, which contains two aspects: higher-order difference layout (HODL) and higher-order cumulant-based parameter identifications. HODL is a special family of layouts that physically guarantee the availability of consecutive higher-order cumulant estimations and thus leads to a satisfactory parameter identification. To facilitate application, a series of concrete HODLs are provided for users, including a four-level nested layout and its enhanced version, and optimal fourth-order difference layout. The quantitative comparison in the simulations and experiments shows the effectiveness of the proposed higher-order cumulant architecture. Compared with the architectures developed from covariance and signal itself perspective, the proposed higher-order cumulant architecture is not only more robust to noise but also further reduces the number of required probes.

Blind power spectrum reconstruction for multi-sinusoid signals with generative multicoset sampling

As the target frequency increases, the Nyquist rate is hard to reach due to hardware limitations. Alternatives to high-rate sampling have attracted considerable research interest. Compressed covariance sensing based on multicoset sampling (MCS) is a prevalent sub-Nyquist sampling strategy for blind power spectrum reconstruction. However, it requires the sampling pattern of MCS to be a minimal sparse ruler. In this paper, a generative multicoset sampling (GMCS) is proposed to minimize the number of cosets. In the sampling stage, a minimal MCS, delay coprime scheme is proposed to ensure the recoverability of the power spectrum. In the recovery stage, a new function, i.e., multifold correlation is constructed for blind power spectrum reconstruction. We prove that the power spectrum of a multi-sinusoid signal (MSS) can be estimated by its multifold correlation and the sample density of multifold correlation can be increased by correlation operations. Owing to multifold correlation, GMCS can generate virtual cosets satisfying the sparse ruler criterion through only two physical cosets and then efficiently recover the power spectrum by least-squares estimation. Moreover, we demonstrate the feasibility of GMCS for linear frequency modulation (LFM) signals. Finally, the effectiveness of GMCS are verified by numerical simulations and blade tip timing experiments (a non-contact vibration measurement). By reducing the average sampling rate and hardware complexity, GMCS opens new avenues for blind sampling and power spectrum reconstruction.

Improved non-contact vibration measurement via acceleration-based blade tip timing

The conventional displacement-blade tip timing (D-BTT) measurements often rely on Once-Per-Revolution (OPR) sensors to compute expected or theoretical time of arrival (TOA) based on rotational speed. However, integrating OPR sensors within the confined space of aero-engines presents challenges, and estimating theoretical TOA introduces computational errors, particularly for low-amplitude, high-frequency blade vibrations. This paper presents the Acceleration-based Blade Tip Timing (A-BTT) method as a solution. Building upon A-BTT, the acquisition of blade tip vibration acceleration serves not only to capture rapid changes in vibration but also to offer richer data for precise measurement of high-frequency blade vibrations. With only three blade tip timing sensors recording actual TOA without an OPR sensor, A-BTT eliminates the need for estimating expected TOA, thus mitigating calculation errors. Furthermore, by analyzing the relationship between maximum blade tip vibration acceleration and displacement during synchronous blade vibration, vibration parameters, such as natural frequency, can be directly identified without prior information such as engine orders. Simulation and experimental results validate the efficacy of the A-BTT method, demonstrating its successful application to specific aero-engine compressor rotor blades.

Numerical simulation and experimental analysis of foreign object impact on aero-engine fan rotor blade

The detection and identification of fan rotor foreign object impact events during the working process of aero-engines are crucial to the safety and security of aircraft flight. Through the numerical simulation method based on finite element and the foreign object impact test platform to simulate the process of real engine impact by foreign objects, the rule of fan rotor blade foreign object impact and the monitoring and identification method were studied. Meanwhile, aiming at the problems of high difficulty and low accuracy in identifying the impact of foreign objects on the fan by the airborne parameters and added vibration parameters, the non-contact vibration measurement method based on blade tip timing was used to obtain the blade vibration displacement under different fan speed, foreign matter mass and impact velocity. The numerical simulation and experimental results show that the change trend of the vibration displacement of the rotor tip of the fan is consistent with that of the numerical simulation. And with the increase of the foreign object projectile mass, the vibration displacement of the blade tip caused by the impact of the foreign object on the fan blade increases. In addition, the impact velocity of the foreign object has little effect on the vibration displacement of the blade tips after impact. Furthermore, the vibration displacement of the blade tip caused by the impact of foreign objects first increases and then decreases with increasing speed.

An optimal sparse sensing approach for scanning point selection and response reconstruction in full-field structural vibration testing

Non-contact vibration measurements, such as 3D scanning laser Doppler vibrometry (3D SLDV), are becoming more prevalent in testing next-generation lightweight aerospace structures. This approach reduces the impact of attached sensors and improves measurement reliability. Acquiring precise measurement data for the whole area is feasible, albeit it would demand a considerable amount of time and storage space for testing. The concept of compressed sensing has been recently approved as an effective way to exploit signal sparsity and achieve full response reconstruction with very few measurements. The objective of this work is to enhance the efficiency of non-contact vibration testing by utilizing the state-of-the-art compressive sensing approach. In contrast to conventional sensor placement methods that rely on effective independence, modal kinetic energy, or modal assurance criterion matrix as targets, this paper proposes a novel sensor placement methodology from the perspective of dynamic response reconstruction. The scanning points are chosen with a minimal number to reduce testing time and are well-placed such that full-field vibration responses of the test structure can be reconstructed accurately. This allows for the spatially-detailed vibration responses to be obtained efficiently and accurately with optimal sparse sensing placement and effective response reconstruction through ℓ1 algorithm. Two case studies will be presented in this work to demonstrate and validate the methodology. The first case study is focused on a simplified cantilever beam using the numerical data from the FE analysis to demonstrate the methodology. The second case study is focused on using 3D SLDV experimental testing data from a full-scale industrial fan blade. Based on the results, it is evident that the proposed approach can significantly decrease the scanning points required for a full-field dynamic response reconstruction during full-field vibration testing.

Coupling the force analysis technique and full-field vibration measurements for the identification of a time-space-varying sound pressure loading on a membrane

This work is grounded on the force analysis technique, an identification method that directly uses a structure's equation of motion to formulate an inverse problem, explicitly identifying the force causing the structure's motion. Prior research employing this technique has been predominantly conducted in the frequency domain and was limited to stationary, mechanical excitations using physical sensor arrays such as accelerometers. The objective of this research was mostly quantitative (amplitude, location), while the proposed approach is rather qualitative identification. Indeed and by combining the force analysis technique with full-field and non-contact vibration measurements conducted on a system, here a membrane, this communication describes a proof-of-concept for the identification of a time-space-varying sound pressure loading. A compact and tonal sound source is used to draw freehand shapes against the membrane surface, and the objective is to follow/reconstruct the trajectory followed by this source. Results are provided for different drawn shapes or letters, and the effect of mechanical or calculation parameters on the reconstructed information is studied. Finally, potential research directions are discussed and fed by preliminary measurements on a percussion instrument.

Space-time reconstruction of a moving acoustic loading on a membrane by coupling the force analysis technique and full-field non-contact vibration measurements

Identifying acoustical and mechanical loadings on structures is a common problem in acoustics and vibration analysis and stationary loadings are mostly considered on plate-like structures. This work describes a proof of concept for reconstructing the trajectory of an acoustic source moving in front of a membrane. Compared with works focusing on precisely identifying a loading’s amplitude at a given location, the objective is to reconstruct the loading’s trajectory–Qualitative loading identification is sought rather than quantitative. The force analysis technique is used to recover a space-time varying loading on a structure, starting from time-resolved full-field non-contact vibration measurements conducted on a circular membrane. At the same time, a compact and tonal sound source is used to draw freehand shapes in front of the membrane. The loading trajectory, therefore, contains information that was “acoustically written”. Simple hand gestures that correspond to the drawing of a Greek letter (Σ), a capital letter (P), two shapes (♡, ⋆), and a 3-letter word (net) are recovered using the proposed procedure. The effect of various parameters on the reconstructed information is studied. Perspectives in terms of possible research areas and applications are finally discussed. These perspectives include, for example, the use of membranes to help reconstruct complex and space-time-varying loadings or even applications in musical acoustics on membranophones.

A target-free vision-based method for out-of-plane vibration measurement using projection speckle and camera self-calibration technology

In recent decades, computer vision-based methods have been introduced into engineering structures to provide full-field, non-contact vibration measurement. However, the vision-based vibration measurement method is challenging to measure the targetless structures. This paper proposed a target-free out-of-plane vibration measurement method using projection speckle and camera self-calibration technology. In this method, the camera extrinsic parameter estimation result based on the direct method is used as the initial value in the proposed method. Then, a nonlinear inequality constraint on the extrinsic parameters is established regarding the epipolar condition to minimize the reprojection error. Furthermore, the projection relationship between the projection speckle displacement and the actual displacement of the structure is studied so that the deviation of the out-of-plane vibration displacement is corrected. In the experimental verification, 3D reconstruction and rigid translation experiments are designed, respectively. The results show that the self-calibration accuracy of the binocular camera proposed in this paper is notably improved compared with the existing methods. At the same time, the deviation correction effect of the vibration displacement is significant. Finally, the typical flat plate structure and composite wing structure are taken as vibration measurement cases to demonstrate that the proposed approach is reliable and accurate in measuring the dynamic responses of engineering structures.

A LOW-Cost Multi-Frequency Testing Platform for Non-Contact Vibration Measurement

A LOW-Cost Multi-Frequency Testing Platform for Non-Contact Vibration Measurement

Bridge-bearing disengagement identification based on flexibility matrix diagonal matrix change rate: an indoor physical simulation experiment

The disengagement of bridge bearings is a pervasive issue encountered in the realm of bridges, which can potentially lead to changes in operational circumstances, diminished longevity, and compromised traffic safety. The current methods employed for detecting such disconnections primarily rely on force sensors, cameras, and acceleration sensors. However, their practical implementation on-site and effectiveness in accurately identifying disengagement require enhancement. To address the challenges associated with the installation and layout of conventional contact sensors, as well as the potential introduction of additional mass, a sophisticated “bridge-bearing disconnection detection system” has been devised. This innovative system is based on laser Doppler vibrometer technology, which eliminates the need for physical contact. The feasibility of employing non-contact laser Doppler vibration measurement technology in the detection of bridge-bearing disconnection has been successfully verified within the framework of this study. Furthermore, a comprehensive analysis of the sensitivity of key dynamic parameters, specifically natural frequencies and vibration modes, to bridge-bearing disengagement has been conducted. The verification process included evaluating the identification effectiveness of regularized combined absolute changes in vibration modes and flexibility matrix diagonal matrix change rate (FDMCR) under diverse working conditions simulating complete disconnection. This assessment involved using both finite element analysis and empirical measurements. The findings unequivocally demonstrate that the disconnection of bridge bearings results in a reduction in the natural frequencies for each mode order, with an observed cumulative effect. In addition, it is noteworthy that the vibration mode indices typically exhibit greater sensitivity toward the disconnection of outer bearings. By contrast, FDMCR demonstrates commendable positioning capabilities and exceptional noise resistance in identifying bridge-bearing disengagement. The empirical insights gleaned from these research findings hold significant value in terms of on-site identification of bridge-bearing disengagement, ultimately contributing to the preservation of bridges’ long-term operational integrity.

Efficient Modal Identification and Optimal Sensor Placement via Dynamic DIC Measurement and Feature-Based Data Compression

Full-field non-contact vibration measurements provide a rich dataset for analysing structural dynamics. However, implementing the identification algorithm directly using high-spatial resolution data can be computationally expensive in modal identification. To address this challenge, performing identification in a shape-preserving but lower-dimensional feature space is more feasible. The full-field mode shapes can then be reconstructed from the identified feature mode shapes. This paper discusses two approaches, namely data-dependent and data-independent, for constructing the feature spaces. The applications of these approaches to modal identification on a curved plate are studied, and their performance is compared. In a case study involving a curved plate, it was found that a spatial data compression ratio as low as 1% could be achieved without compromising the integrity of the shape features essential for a full-field modal. Furthermore, the paper explores the optimal point-wise sensor placement using the feature space. It presents an alternative, data-driven method for optimal sensor placement that eliminates the need for a normal model, which is typically required in conventional approaches. Combining a small number of point-wise sensors with the constructed feature space can accurately reconstruct the full-field response. This approach demonstrates a two-step structural health monitoring (SHM) preparation process: offline full-field identification of the structure and the recommended point-wise sensor placement for online long-term monitoring.

Non-contact heart vibration measurement using computer vision-based seismocardiography

Seismocardiography (SCG) is the noninvasive measurement of local vibrations of the chest wall produced by the mechanical activity of the heart and has shown promise in providing clinical information for certain cardiovascular diseases including heart failure and ischemia. Conventionally, SCG signals are recorded by placing an accelerometer on the chest. In this paper, we propose a novel contactless SCG measurement method to extract them from chest videos recorded by a smartphone. Our pipeline consists of computer vision methods including the Lucas–Kanade template tracking to track an artificial target attached to the chest, and then estimate the SCG signals from the tracked displacements. We evaluated our pipeline on 14 healthy subjects by comparing the vision-based SCG^mathrm{{v}} estimations with the gold-standard SCG^mathrm{{g}} measured simultaneously using accelerometers attached to the chest. The similarity between SCG^mathrm{{g}} and SCG^mathrm{{v}} was measured in the time and frequency domains using the Pearson correlation coefficient, a similarity index based on dynamic time warping (DTW), and wavelet coherence. The average DTW-based similarity index between the signals was 0.94 and 0.95 in the right-to-left and head-to-foot directions, respectively. Furthermore, SCG^mathrm{{v}} signals were utilized to estimate the heart rate, and these results were compared to the gold-standard heart rate obtained from ECG signals. The findings indicated a good agreement between the estimated heart rate values and the gold-standard measurements (bias = 0.649 beats/min). In conclusion, this work shows promise in developing a low-cost and widely available method for remote monitoring of cardiovascular activity using smartphone videos.

A New Optical Sensing Device for Real-Time Noncontact Vibration Measurement Considering Light Field Variation

Vibration measurement is essential for vibration monitoring and control. Non-contact vibration measurement is more applicable in practice than the contact measuring manner, but the non-contact methods usually pose a high requirement on the light field environment. To solve this issue, a new binocular vision method is proposed to enable non-contact vibration measurement with different light fields. In this new method, the multi-target objects in the same image are firstly recognized by a YOLOv5 model to generate the bounding boxes; meanwhile, a depth image is generated through the binocular vision and kept synchronized with the target image. Then, based on each bounding box and its corresponding depth image, an optimal depth value decision algorithm is developed to determine the three-dimensional (3D) real-time coordinates of each object. As a result, the vibration of multi-target objects can be measured simultaneously. An experimental test system was built to evaluate the performance of the proposed method in indoor and outdoor light fields. The tests demonstrate accurate vibration measuring results and the proposed non-contact method is able to detect very low frequency vibrations.

회전 중 블레이드 진동 비접촉 측정기술 기반 저압터빈 블레이드 진동특성 분석

회전 중 블레이드 진동 비접촉 측정기술 기반 저압터빈 블레이드 진동특성 분석

Noncontact vibration measurement using three spatial-frequency shifting coherent digital holography.

A new digital coherent holographic system that works as a spatial-frequency shifter for measuring three-dimensional (3D) vibration of an object is proposed. The spatial-frequency shifter is constructed by a system of three mirrors inclined with different small angles to shift the object wave to three different frequencies in the spatial-frequency domain. By applying the Fourier transform method and appropriate filters to the hologram recorded by the camera of the system, a three-phase set of object waves corresponding to three shifted frequencies was obtained. From the relation between the phases and the relative position of the object, the position of each point on the surface of the object along the x, y, and z directions was extracted from each hologram. The same process was repeatedly applied to a series of holograms recorded by a fast camera, allowing the 3D vibration of the object to be precisely observed.

Position sensitive detector based non-contact vibration measurement with laser triangulation method utilizing Gabor Transform for noise reduction

Measurement of vibration without having contact with the target is crucial for many applications. However, real time vibration signals are frequently mixed with various levels of dynamic noises. In this research, a non-contact type vibration measurement system based on laser triangulation method is proposed by using a PSD (Position sensitive detector) and here a single axis Brüel and Kjaer piezoelectric accelerometer is used to validate the experimental results. The primary goal of this measurement system is to develop a Gabor Transform based signal denoising technique, in order to eliminate noise from the real-time vibration data. Furthermore, PSD platform vibration, which might cause unanticipated inaccuracies in the detected vibration data, has also been eliminated by utilizing a self-vibration compensation approach using an ADXL-345 three-axis accelerometer. The self-vibration compensated vibration measurement technique has been designed using an NI (national instruments) cRIO (CompactRIO) 9074 real-time FPGA (field programmable gate array) based embedded controller. Consequently, a Gabor Transform and Expansion-based Signal Processing Technique is designed using NI cRIO-9074 real time platform to reduce external noise from the self-vibration compensated vibration data. It has been observed that the implementation of Gabor Transform has improved the performance of the system in term of enhancing the SNR (Signal-to-noise ratio).

Full-Field Visual Vibration Measurement of Rotating Machine Under Complex Conditions via Unsupervised Retinex Model

Vision-based measurement, as the most common non-contact vibration measurement method, has received increasing attention and development in recent years. However, it is still highly dependent on the shooting environment and data quality, and is difficult to apply to complex mechanical structures. This article focuses on the full-field extraction of micro-vibration signals of high-speed rotating machinery under complex conditions. A novel visual vibration measurement scheme is proposed, called the texture-perception motion estimation frame (TPME). First, an unsupervised image decomposition model called the texture-perception network (TPNet) is designed to linearly separate the image reflection layer and illumination layer. The high-frequency texture features of the reflection layer can strengthen the data representation ability. Using it alone for phase-based micro-motion extraction (PME) can not only expand the measurement range and accuracy but also ensure measurement robustness under complex luminance changes. Furthermore, we evaluate the computational cost of this approach, which achieves significant measurement improvements with a very low computational overhead. Experiments on three different rotor platforms demonstrate the effectiveness of TPME.