Non-contact Vibration Research Articles

Sliding mode predictive vibration control of a piezoelectric flexible plate

A non-contact vibration measurement and control system for a piezoelectric-patched flexible cantilever plate is presented, using laser displacement sensors. Two laser displacement sensors are utilized to detect the deflection information of the two corners of the end of the flexible board, due to its high measurement accuracy for the small amplitude residual vibration. The vibrations of the first bending and torsional mode of the flexible plate can be extracted from the combined information. To achieve a desirable performance for the active vibration control, a kind of sliding mode predictive control strategy is developed to damp the vibration quickly. Simulation of the controller on bending and torsional vibration is conducted, based on the model built with finite element method. Furthermore, a piezoelectric flexible cantilever plate experimental setup is constructed. Experiments are conducted. The results of simulation and experiment both demonstrate the effectiveness of presented control scheme, compared with proportional and derivative control; the sliding mode predictive control can attenuate the vibration more quickly, particularly for the small amplitude residual vibration.

Experimental investigation on defrosting of a cold flat plate via ultrasonic vibration under natural convection

The present experimental study examines the effect of ultrasonic vibration on the frost formation under a free convective environment. A stainless steel SS ANSI 316 flat surface is tested under 12–24 °C dry bulb temperature and 58–84% relative humidity. The experiments are conducted with direct contact and non-contact high-frequency ultrasonic source having continuous or intermittent vibrations. The ultrasonic transducer contains 28 ± 0.5 kHz resonance frequency. It is found that increasing the relative humidity will increase the frost thickness and influences the frost property. Imposing ultrasonic vibration under high relative humidity and low ambient temperature increases the droplets' circularity with comparatively sparse distribution. Test results indicate that non-contact vibration has no effect on the frost formation. Intensive intermittent contact vibration is the most effective way to suppress frost growth. Compared to continuous contact vibration, either it is applied after each an hour or after every 30 min as an intensive continuous, intensive intermittent contact vibration shows a reduction in frost thickness as much as 24%. In addition, the ultrasonic vibration should be applied after the supersaturation stage since ultrasonic vibration enhances the supercooled process.

Non-Contact Vibration Detection Software and Hardware Design with Image Processing Method to Reveal Substantial Changes in Structures and Systems

Many types of equipment are used for vibration detection in buildings and systems. However, these systems have their own problems. In this article, a combined software and hardware system is designed for the solution of these problems. The system has been designed with the Motion Magnification Analysis (MMA) method, which stands out in the literature studies. C # language and .NET environment have been used as software. The Accord library was used for the image processing process. These libraries were also used for the analysis of subspaces and components of the image. During the study, three new algorithms that have not been applied in the past and not in the literature have been developed. The first of these is the derivative of the method known as Color Magnification, which analyzes the color space. The second is the derivative of the Motion Magnification method, which magnifies the vibration to the visible level. And the third one is the Frequency Determination algorithm, which enables frequency measurement. With this solution, it is provided to make an analysis of the images taken with devices with relatively slow cameras such as mobile phones/tablets as well as fast cameras. All results were compared with a touchable vibration analyzer for benchmarking and showed that the proposed method was successful.

New Applications of Laser Vibrometry

The possibility of using lasers for non-contact vibration measurements has been known since the mid-60s. This work describes the development of some applied areas: the use of laser vibrometry in near-field acoustic holography, verification of numerical models of vibrations of complex structures, and vibration flaw detection.

Non-Contact Fault Diagnosis of Bearings in Machine Learning Environment

Timely detection of faults in bearings can save time, efforts and maintenance costs of rotating equipments. To avoid the physical connection of vibration pickup to the machine tool, a non-contact type vibration pickup has been designed and developed in this study to acquire the vibration data for bearing health monitoring under load and speed variation. Fault diagnosis has been accomplished using a Hilbert transform for denoising the signal. The dimensionality of the extracted features was reduced using Principal Component Analysis (PCA) and thereafter the selected features were ranked in order of relevance using the Sequential Floating Forward Selection (SFFS) method for reducing the number of input features and finding the most optimal feature set. Finally, these selected features have been passed to Support Vector Machines (SVM) and Artificial Neural Networks (ANN) for identifying and further classifying the various bearing defects. A comparative analysis of the effectiveness of SVM and ANN has been carried out. The results reveal that the vibration signatures obtained from developed non-contact sensor (NCS) compare well with the accelerometer data obtained under the same conditions. Classification accuracy achieved by the developed NCS with other sensors reported in the literature compares very well. The proposed strategy can be used for automatic recognition of machine faults which will help in providing early warnings to avoid unwanted and unplanned system shutdowns due to failure of the bearings.

CNN-LSTM deep learning architecture for computer vision-based modal frequency detection

The conventional modal analysis involves physically-attached wired or wireless sensors for vibration measurement of structures. However, this method has certain disadvantages, owing to the sensor’s weight and its low spatial resolution, which limits the analysis precision or the high cost of optical vibration sensors. Besides, the sensor installation and calibration in itself is a time consuming and labor-intensive process. Non-contact computer vision-based vibration measurement techniques can address the shortcomings mentioned above. In this paper, we introduce CNN-LSTM (Convolutional Neural Network, Long Short-Term Memory) deep learning based approach that can serve as a backbone for computer vision-based vibration measurement techniques. The key idea is to use each pixel of an image taken from an off the shelf camera, encapsulating the Spatio-temporal information, like a sensor to capture the modal frequencies of a vibrating structure. Non-contact “pixel-sensor” does not alter the system’s dynamics and is relatively low-cost, agile, and provides measurements with very high spatial resolution. Our computer vision-based deep learning model takes the video of a vibrating structure as input and outputs the fundamental modal frequencies. We demonstrate, using reliable empirical results, that “pixel-sensor” is more efficient, autonomous, and accurate. Robustness of the deep learning model has been put to the test by using specimens of a variety of materials, and varying dimensions and results have shown high levels of sensing accuracy.

Acoustic-Excitation Optical Coherence Vibrometer for Real-Time Microstructure Vibration Measurement and Modal Analysis

An acoustic-excitation optical coherence vibrometer (AE-OCV) is proposed for noncontact microstructure vibration measurement and modal analysis. The vibration dynamic parameters of the microstructure can be captured with a subnanometer displacement resolution by the proposed AE-OCV using spectral wavelength calibration algorithm and spectral center correction method. The natural frequency of the microstructure could also be obtained by the developed noncontact AE-OCV system using the swept-frequency acoustic excitation method. Furthermore, a home-made spectrometer based on a high-speed linear camera could provide the system with a frequency measurement range of 0–50 kHz. The developed AE-OCV has an excellent performance in microstructures vibration measurement and modal analysis, especially for high-frequency and nanoscale vibration measurements. It is of great significance to the design of the microelectromechanical system (MEMS), such as the noncontact dynamic measurement of cantilevered beams in atomic force microscopy.

Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor

To further improve the precision and efficiency of structural health monitoring technology and the theory of large-scale structures, full-field non-contact structural geometry morphology monitoring is expected to be a breakthrough technology in structural safety state monitoring and digital twins, owing to its economic, credible, high frequency, and holographic advantages. This study validates a proposed holographic visual sensor and algorithms in a computer-vision-based full-field non-contact displacement and vibration measurement. Using an automatic camera patrol experimental device, original segmental dynamic and static video monitoring data of a model bridge under various damage/activities were collected. According to the temporal and spatial characteristics of the series data, the holographic geometric morphology tracking algorithm was introduced. Additionally, the feature points set of the structural holography geometry and the holography feature contours were established. Experimental results show that the holographic visual sensor and the proposed algorithms can extract an accurate holographic full-field displacement signal, and factually and sensitively accomplish vibration measurement, while accurately reflecting the real change in structural properties under various damage/action conditions. The proposed method can serve as a foundation for further research on digital twins for large-scale structures, structural condition assessment, and intelligent damage identification.

Remote diagnostics of vibrations of dynamic objects by Doppler microwave sensors

This paper describes a promising method for non-contact vibration diagnostics based on the use of Doppler microwave sensors. In this case, active irradiation of the object with electromagnetic waves and the allocation of phase changes using two-channel quadrature processing of the received reflected signal are used. The modes of further fine analysis of the resulting signal using spectral or wavelet transformations depending on the nature of the active vibration are considered. The advantages of this non-contact and remote vibration analysis method for the study of complex dynamic objects are described. The convenience of the method for machine learning and use in intelligent systems of non-destructive continuous monitoring of the state of these objects by vibration is noted.

Experimental Study on the Cable Tension Based on Non-Contact Dynamic Deflection Equipment

For the contact and wired measurement technology of cable tension, the factors of complicated bridge site conditions, data acquisition and transmission, wave data processing and sensor contact should be considered in practical application, which affect seriously the measure result accuracy, work efficiency and the measure feasibility. In order to improve the limitation of the existing cable tension measurement technology, the feasibility and key factors of non-contact dynamic deflection measurement technology is studied. A cable specimen with length of 12m was designed and made, and the steel strand is used in it, and the non-contact vibration testing device is used. The frequency and tension of the cable and the strain of steel strands are analyzed, and the results show that the effect of measure target position on the fundamental frequency of the cable is obviously little, and the tension of the subsequent steel strand can decrease the tension strain of the stretched steel strand, that is, the tension of the stretched steel strand is reduced. Furthermore, the maximum difference between calculated and measured tension of the cable is about 17.7% during loading stage. When the unloaded cable tension is less than 20.6%, the difference between calculated and measured tension is less than 10.0%. It can be seen that the tension and tension loss of the cable can be accurately estimated by using the non-contact dynamic deflection technology, and it can improve the work efficiency and the measure feasibility due to the less measure targets and larger data transmission distance.

Improvement and possibilities of application of calibration methods for optoelectronic vibration displacement sensor

The characteristics of non-contact sensors for measuring displacements, deformations, and vibration parameters using processes of various physical nature are compared. Within the framework of the diffuse-mirror reflection model, the efficiency of using optocouplers for developing non-contact vibration displacement sensors is substantiated. The urgent tasks of research and development of sensors using near infrared radiation reflected from the surface of the controlled object are formulated. The research technique based on modern algorithms and means of digital processing of vibrosignals is given. The difficulties of studying the metrological characteristics of sensors in a wide dynamic and frequency ranges using electrodynamic vibration stands are considered. The results of a full-scale study of the basic metrological characteristics of a prototype optoelectronic sensor providing measurements of displacements with an amplitude of up to 5 mm in the frequency range from 0 to 3 kHz are presented. The results of analysis of the amplitude-frequency characteristics of the sensor in the range from 5 Hz to 3 kHz, obtained using two disks made on a 3D printer, are presented. The advantages and disadvantages of non-contact sensors based on infrared optocouplers are given.

Phase-Based Noncontact Vibration Measurement of High-Speed Magnetically Suspended Rotor

Video-based measurement, as one of the most common noncontact measurement methods for industrial inspection, has been developed rapidly. Digital video cameras offer the benefit of low cost, high automation, and are capable to make the simultaneous full-field measurement. This article focuses on studying the microvibrational signal extraction for high-speed rotating machinery with digital cameras. An improved phase-based motion extraction and learning-based video magnification are proposed for measuring the microvibration with high frequency and small amplitude. The phase-based motion extraction is improved by directly transforming the phase variations into the displacement without the computation of phase gradient. Furthermore, the learning-based motion magnification is utilized to amplify and qualitatively measure the microvibration in specified frequency bands. The phase-based motion extraction is a quantitative measurement, while the learning-based video magnification is a qualitative measurement. Experimental results for microvibration measurement rising from a magnetically suspended motor system validate the effectiveness of the proposed method.

An Effective Accuracy Evaluation Method for LFMCW Radar Displacement Monitoring With Phasor Statistical Analysis

Non-contact displacement and vibration monitoring based on microwave interferometry is an emerging and promising technique in structural health monitoring. This paper focuses on the measurement accuracy evaluation requirements for linear frequency-modulated continuous-wave (LFMCW) radar displacement monitoring in practical applications, and presents an effective accuracy evaluation method based on phasor statistical analysis (PSA). The basic idea of the proposed method is that the phase evolution estimation error (i.e., corresponding to displacement measurement error) can be quantitatively evaluated and calculated by using the relative error statistic of the phasor amplitude tracking result across multiple sweeps. The accuracy evaluation problem and the specific procedures of the proposed PSA method are described. In addition, the detailed mathematical analysis and geometric interpretation regarding three main interference (i.e., noise, static clutter and adjacent clutter) scenarios are provided for the validation. A series of simulations and experiments are carried out to demonstrate the performance of our proposed method, which has low computational complexity, high applicability and good user friendliness.

Non-contact vibration monitoring of rotating wind turbines using a semi-autonomous UAV

With the recent demands for more efficient clean renewable energy sources, wind turbines are designed that have large rotor blade diameters. These large-sized wind turbines need to be periodically monitored to prevent catastrophic failures. This paper aims to develop a practice for obtaining the vibration characteristics of wind turbine blades that can be eventually used for structural health monitoring of these structures. This monitoring technique needs to be robust and non-contact to prevent any interference with the operation of the wind turbine. In this work, a digital image correlation (DIC) system installed on a drone is used as a sensing technique to obtain the dynamic characteristics of rotating wind turbine blades. The DIC uses a stereo-camera system to record the deflections of the blades and provides non-contact measurements. The unmanned aerial vehicle (UAV) enables on-site robust measurements. Furthermore, a dynamic stitching technique is used after DIC measurement to obtain vibration characteristics of the entire blade with high accuracy. The proposed health monitoring technique can be used by engineers for remote structural health monitoring of wind turbines during operation in both offshore and inland wind farms.

Design and experiment of a noncontact electromagnetic vibration isolator with controllable stiffness

Isolating low-frequency vibration in current satellites that has a negative effect on the performance of precise payloads has increasing demand. In this work, a simplified model of a noncontact electromagnetic isolator for low-frequency vibration, which has a controllable stiffness with a minimum of zero, is proposed. Starting with the designing process of the vibration isolator, a series of ground-based experiments are carried out to verify the controllable stiffness. Two typical operating scenarios, the vibration isolation and rapid maneuver modes, are experimentally demonstrated. The experimental results indicate that the stiffness has a practically proportional relationship with the input current and the proposed design works well for both of the operation modes.

Quantitative diagnosis method of beam defects based on laser Doppler non-contact random vibration measurement

The beam structure is prone to defect damage during its use, and the rapid quantitative diagnosis of the beam structure can detect the defects of the beam in real time and quantitatively. In this article, the method of obtaining the vibration time-domain signal under random excitation of beam structure is proposed by using random vibration excitation and Laser Doppler principle. Based on this, the defect quantitative identification algorithm of beam structure is proposed based on fast Fourier, continuous wavelet transform and convolutional neural network. The random vibration of different parts of steel beams with artificial defects is measured by Laser Doppler method. The experimental results show that the defect size of the beam structure can be effectively identified only by the random vibration signal of the finite point. The method is expected to help to develop an online real-time assessment instrument for beam structure defects in service state.

Support vector machines based non-contact fault diagnosis system for bearings

Bearing defects have been accepted as one of the major causes of failure in rotating machinery. It is important to identify and diagnose the failure behavior of bearings for the reliable operation of equipment. In this paper, a low-cost non-contact vibration sensor has been developed for detecting the faults in bearings. The supervised learning method, support vector machine (SVM), has been employed as a tool to validate the effectiveness of the developed sensor. Experimental vibration data collected for different bearing defects under various loading and running conditions have been analyzed to develop a system for diagnosing the faults for machine health monitoring. Fault diagnosis has been accomplished using discrete wavelet transform for denoising the signal. Mahalanobis distance criteria has been employed for selecting the strongest feature on the extracted relevant features. Finally, these selected features have been passed to the SVM classifier for identifying and classifying the various bearing defects. The results reveal that the vibration signatures obtained from developed non-contact sensor compare well with the accelerometer data obtained under the same conditions. A developed sensor is a promising tool for detecting the bearing damage and identifying its class. SVM results have established the effectiveness of the developed non-contact sensor as a vibration measuring instrument which makes the developed sensor a cost-effective tool for the condition monitoring of rotating machines.

Field Testing of Wind Turbine Towers with Contact and Noncontact Vibration Measurement Methods

AbstractWind turbine tower vibration parameters are critical for design and maintenance of wind farms. In this paper, measurement campaigns of two in-service 65-m tall wind turbine towers are inves...

Vibration Control of Hemispherical Shells with Light-Activated Shape Memory Polymers

Light-activated shape memory polymer (LaSMP) is a novel actuator with dynamic Young’s modulus and strain when exposed to ultraviolet lights, which can be used in noncontact vibration control. This study focuses on the vibration control effect of LaSMP patches on hemispherical shells with free boundaries. An LaSMP strain variation model is presented with experimental verifications. Based on the strain model, the control forces of LaSMP patches on hemispherical shells are introduced. The FEM method is used to obtain natural frequencies of the free hemispherical shell by solid modeling in ANSYS and proved by comparing numerical results with analytical and experimental results. Using the modal expansion method, the LaSMP vibration control of hemispheres is investigated, and independent modal responses are presented and evaluated. The results indicate that LaSMP patch can control vibrations of hemispherical shells by reducing vibration amplitudes. And the control effect is better for low modal vibration, as the LaSMP-induced strain is relatively smaller. By establishing the relationship between LaSMP actuator forces and modal amplitude reduction, this study offers an analytical tool and procedure for future LaSMP application to vibration controls of flexible structures.

Non-contact low-frequency vibration rapid measurement based on hue-height mapping

A non-contact vibration measurement system based on camera-projector system and hue-height mapping is proposed. The CCD camera acquires the color deformed fringes with red (R) green (G) blue (B) channels, which is modulated by a vibrating loudspeaker, with the aim to demodulate the information of vibrations. In order to avoid the crosstalk between RGB channels, the sampling frames from RGB space are converted to hue (H) saturation (S) intensity (I) space. By using hue information, height value of each pixel point at different sampling frames can be restored, so as to obtain the vibration curve of the loudspeaker. The experiments compare the vibrations of different frequencies at several Hertz, and different amplitudes lower than millimeter degree. The results show that this optical image system can detect low-frequency vibrations with high accurate amplitudes, and meet the basic industrial measurement requirements.