Vibration Velocity Signal Research Articles

Experimental investigation on characteristics of cavitation-induced vibration on the runner of a bulb turbine

Cavitation may result in reduced efficiency, increased noise and vibration and weight loss of a hydraulic turbine when local pressure is lower than the vaporization pressure. In this paper, a synchronous test system including high-speed camera and Laser Doppler Vibrometer (LDV) is established to analyze characteristics of cavitation-induced vibration on the runner of a bulb turbine under different cavitation states. The results show that the peak-to-peak and Root Mean Square (RMS) values of vibration velocities on the turbine runner both increase with the severity of cavitation, but the growth rate is remarkably different which strongly depends on the cavitation state. The runner vibration velocity holds a normal distribution for all cavitation states, and the variance of the normal distribution increases gradually with the severity of cavitation. The increase of cavitation level is accompanied by frequency band migration of vibration signals. In the state of complete cavitation, the local energy extreme of the medium-high frequency component of the runner vibration velocity signal migrates to the low frequency region, resulting in an obvious increase in the energy of the low frequency region.

Propagation Characteristics of Seismic Waves in Shallow Sea Sedimentary Layers

Zhao, S.; Gu, D.; Guo, C.; Wang, X., and Zhang, J., 2023. Propagation characteristics of seismic waves in shallow sea sedimentary layers. Journal of Coastal Research, 39(1), 32–44. Charlotte (North Carolina), ISSN 0749-0208. To explore new techniques for detecting and identifying targets in water, the propagation characteristics of seismic waves in shallow sea were deeply studied. Wave theory and staggered grid finite difference method were employed to analyze the propagation characteristics of seismic waves in a layer of underwater medium with a sedimentary layer. The results show that a Scholte wave is prone to disperse in an underwater medium with a sedimentary layer. The sediment thickness and acoustic parameters have great influence on the propagation characteristics of seismic waves. Moreover, the seismic wave signals were mainly concentrated below 20 Hz by collecting the vibration velocity of underwater interface. Furthermore, Scholte wave signals in underwater experiments were determined by utilizing four filtering methods and Scholte polarization characteristics, and the Butterworth filtering method can better preserve the integrity of vibration velocity signal. The theoretical, numerical, and experimental polarization characteristic results are basically consistent, which indicate that Scholte wave can be well extracted by the method of polarization characteristics.

Research on the effect of tooth root defects on the motor-multistage gear transmission system

In this paper, a coupled dynamic model is proposed for a motor and a multistage gears system of a coal mining machine with tooth root defects. The model effectively simulates the influence of the tooth root cracks on the vibration signals in a multistage gears system when the cracks occur in the planetary subsystem and fixed-shaft gear train subsystem. Comparing the Kurtosis and Crest factor indicators of planetary gear dynamic force and vibration velocity signals, the former is more sensitive to tooth root faults and more suitable as a dynamic indicator for evaluating the effect of tooth root defects on the planetary gear system. The electromechanical system is simulated by coupling the dynamic model of three-phase asynchronous motor and gear system, and the effect of gear tooth faults with different crack depths on the dynamic characteristics of motor-multistage gear system is explored. The results show that the motor current signature analysis (MCSA) can be applied to the detection of gear tooth faults in the transmission system. This method greatly reduces the workload of signal acquisition and spectrum analysis, and can be used as an effective supplement to the traditional vibration signal detection technology.

Ball Bearing Fault Diagnosis Using Recurrence Analysis

This paper presents the problem of rolling bearing fault diagnosis based on vibration velocity signal. For this purpose, recurrence plots and quantification methods are used for nonlinear signals. First, faults in the form of a small scratch are intentionally introduced by the electron-discharge machining method in the outer and inner rings of a bearing and a rolling ball. Then, the rolling bearings are tested on the special laboratory system, and acceleration signals are measured. Detailed time-dependent recurrence methodology shows some interesting results, and several of the recurrence indicators such as determinism, entropy, laminarity, trapping time and averaged diagonal line can be utilized for fault detection.

Vibration Quantity Share of Multiple Faults with Similar Frequency Spectrum Characteristics in Rotational Machinery

Characteristics of the vibrations of rotational systems with misalignment and rotating looseness are well known and they are used for fault detection in the rotating machinery. For the better understanding and easier decision make in the fault removing process it is necessary to know how severe each fault is. Lack of procedures for quantification of this faults in rotational machinery is evident. In this paper is investigated the possibility for use of multiple regression analysis for determination of quantity of faults in vibration velocity signal. An experimental motor – coupling – rotor system is created and produced. These systems have capability of changing the values of misalignment and rotational looseness. Measurement of vibrational quantities were conducted on these systems by using piezoelectrical accelerometers for different combinations of fault values. All measurements were stored and processed digitally. All measurements have shown the presence of the main characteristics of introduced faults. It is confirmed that it is not possible to use RMS (root mean square) of vibration velocity, since there is a lot of other factors which has significant impact on the vibration quantity.

ADOPTION OF VIBRATION OF FUZZY PARTIAL FRACTIONAL-ORDER EQUATION IN MONITORING OF NOISE BIG DATA UNDER INFINITE IMPULSE RESPONSE DIGITAL FILTER ALGORITHM

In order to study the application of fuzzy partial fractional-order equation based on infinite impulse response (IIR) digital filter in noise big data monitoring, in this study, first, the noise level is calculated through IIR filter to obtain the sound signal sequence after C weight and A weight; the weight equivalent continuous sound level of C, A, and Z is calculated. Then, the vibration condition of fuzzy partial fractional-order equation is studied; the vibration acceleration signal is converted into the vibration velocity and displacement signal; the corresponding effective values are calculated according to the root mean square (RMS), and the noise monitoring platform is designed from hardware and software aspects. Finally, the calibrated sound level value is compared with the standard signal value generated by the digital signal generator; the sequence of sound signal after weight of the original signal, the actual acceleration signal, velocity signal, and displacement signal are calculated; the acceleration signal, velocity signal, and theoretical signal values are compared at different frequencies. The results show that the error between the calculated and calibrated sound level and the standard signal value is very small, and the results of weight counting of C and A are good and meet the requirement of calculation; the error between the measured value of actual acceleration, velocity, and displacement signal and the theoretical value is small, which can realize the accurate acquisition of vibration signal; the error between the actual measured value and the theoretical value of acceleration and velocity at different frequencies is small, about 1% and 10%, respectively. Therefore, the fuzzy partial fractional-order equation based on IIR digital filter can effectively monitor the big noise data.

An Experimental Approach on Beating in Vibration Due to Rotational Unbalance

This paper proposes a study in theoretical and experimental terms focused on the vibration beating phenomenon produced in particular circumstances: the addition of vibrations generated by two rotating unbalanced shafts placed inside a lathe headstock, with a flat friction belt transmission between the shafts. The study was done on a simple computer-assisted experimental setup for absolute vibration velocity signal acquisition, signal processing and simulation. The input signal is generated by a horizontal geophone as the sensor, placed on a headstock. By numerical integration (using an original antiderivative calculus and signal correction method) a vibration velocity signal was converted into a vibration displacement signal. In this way, an absolute velocity vibration sensor was transformed into an absolute displacement vibration sensor. An important accomplishment in the evolution of the resultant vibration frequency (or combination frequency as well) of the beating vibration displacement signal was revealed by numerical simulation, which was fully confirmed by experiments. In opposition to some previously reported research results, it was discovered that the combination frequency is slightly variable (tens of millihertz variation over the full frequency range) and it has a periodic pattern. This pattern has negative or positive peaks (depending on the relationship of amplitudes and frequencies of vibrations involved in the beating) placed systematically in the nodes of the beating phenomena. Some other achievements on issues involved in the beating phenomenon description were also accomplished. A study on a simulated signal proves the high theoretical accuracy of the method used for combination frequency measurement, with less than 3 microhertz full frequency range error. Furthermore, a study on the experimental determination of the dynamic amplification factor of the combination vibration (5.824) due to the resonant behaviour of the headstock and lathe on its foundation was performed, based on computer-aided analysis (curve fitting) of the free damped response. These achievements ensure a better approach on vibration beating phenomenon and dynamic balancing conditions and requirements.

Scale model test study of influence of joints on blasting vibration attenuation

Ground vibrations are an integral part of the process of rock blasting. The analysis of blasting vibration attenuation is the basis for a blasting risk assessment. To study the influence of rock joints on the blasting vibration attenuation, an autoclaved aerated concrete block was used as a similar material of rock in model tests of blasting vibration propagation. The attenuation process of the blasting vibration was physically simulated. The attenuation behaviors of the blasting vibrations in different directions to joint strike were fitted. Additionally, a positive correlation between the attenuation parameters and the directions was obtained. Furthermore, the Hilbert–Huang transform (HHT) based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was used to analyze the vibration velocity signals. The characteristics and variation of the energy distribution were studied in the time–frequency domain. The results showed that the energy amplitude decreased as the propagation distance increased. The energy distribution gradually evolved from concentrated to discrete in the frequency domain. The low-frequency components were always present in the velocity signals at each measurement point, but the high-frequency components constantly changed due to the reflection and transmission of the waves after encountering the joint surfaces. The results of this study provide a reference for the prediction and control of the blasting vibration effect in jointed rock masses.

Research on Shaking Table Test of Earthquake Simulation Based on Hybrid Integration Algorithm

Aiming at the problem of poor accuracy of acceleration waveform reproduction during the shaking table test of earthquake simulation, a hybrid integration algorithm based on seismic acceleration signal is proposed to control the trend term error. The low-frequency attenuation integral algorithm in the frequency domain is used to integrate the original seismic acceleration signal once to obtain the vibration velocity signal, then, the polynomial fitting integration algorithm is introduced to integrate of the vibration velocity signal once in the time domain to obtain the vibration displacement signal. Through these two integrals, the sensitivity of low frequency band during frequency domain integration and the accumulation of small errors in time domain are reduced. Finally, the hybrid integration algorithm is used to perform seismic wave reproduction experiments on the seismic simulation shaker and good results are obtained, which proves that the hybrid integration calculation has high practical value and practical significance in improving the accuracy of the vibration table waveform reproduction.

Study of dynamic response of High-Rise buildings under blasting earthquake considering model simplifying

Based on the blasting engineering of the subway tunnel, the overall dynamic response of the 28-story frame-shear-wall structure is studied by field test and numerical analysis. Field test is the blasting vibration monitoring and operational mode analysis (OMA). OMA used Ibrahim Time Domain method to extract the modal frequencies, the modal damping ratio of the structure, provided the basis for further analysis of the vibration response laws. The structure is simplified into a mass-spring-damper model. Based on the modal parameters extracted from the AVT, fixed the stiffness matrix and the damping matrix of the mass-spring-damper model, and set up the dynamic differential equation. So the modal parameters and frequency-response-functions of the building bending vibration can be calculated. SIMULINK dynamic simulation model was established based on the dynamic differential equation of the mass-spring-damper model. Based on the blasting vibration velocity signal, the overall vibration response law of high-rise buildings under tunnel blasting seismic is analyzed. The following conclusions are drawn: 1. Under the blasting vibration of the subway tunnel, the vibration response velocity of high-rise buildings presents: vertical vibration is the largest, lengthways vibration velocity is the second, and transverse vibration velocity is the smallest. However, the vertical vibration velocity peak and tangential vibration velocity peak at the higher floors is not much different. 2. On the higher floors, the velocity peaks fluctuated with floor increasing, and fluctuation is interrelated with the dominant mode. The peak value of vibration velocities distribution shows this correlation; 3, To simplify the high-rise building to be the mass-spring-damper model and set up the mathematical model of dynamic reaction. Then, the Simulink simulation model was established for simulation calculation. This method can adequately predict the response of the structure under blasting vibration.

Vibration Characteristics Analysis of Composite Double‐Layer Explosive Vessel Shell Subjected to Explosion Loading

Explosive vessels are vulnerable to shock wave impacts during operation processing. It is necessary to explore the vessel’s vibration characteristics. In this paper, acceleration sensors were adopted to collect vibration acceleration signals at the inner and outer surfaces of the composite double‐layer explosive vessel under explosive loading. Then, the effective vibration velocity curve can be obtained by fitting polynomials to eliminate the acceleration integral trend. Thereafter, Hilbert‐Huang Transform (HHT) was applied to analyze the time‐frequency distribution of vibration velocity signals. The results showed that the special “steel plate–buffer interlayer–steel plate” structure can effectively attenuate the explosion vibration effect, and the frequency distribution range of vibration signal at the inner surface was wider than that at the outer surface, and furthermore the main vibration frequency was close to the natural frequency at the inner surface. Meanwhile, vibration amplitude and the main vibration frequency decreased obviously compared with the outer surface, and the vibration time of 0–200 Hz low‐order frequency was shortened. The above researches closely linked the energy distribution with frequency of vibration signals and provided valuable reference for safer protection and vibration reduction design of explosive vessel.

Real time identification of the internal combustion engine combustion parameters based on the vibration velocity signal

Accurate combustion parameters are the foundations of effective closed-loop control of engine combustion process. Some combustion parameters, including the start of combustion, the location of peak pressure, the maximum pressure rise rate and its location, can be identified from the engine block vibration signals. These signals often include non-combustion related contributions, which limit the prompt acquisition of the combustion parameters computationally. The main component in these non-combustion related contributions is considered to be caused by the reciprocating inertia force excitation (RIFE) of engine crank train. A mathematical model is established to describe the response of the RIFE. The parameters of the model are recognized with a pattern recognition algorithm, and the response of the RIFE is predicted and then the related contributions are removed from the measured vibration velocity signals. The combustion parameters are extracted from the feature points of the renovated vibration velocity signals. There are angle deviations between the feature points in the vibration velocity signals and those in the cylinder pressure signals. For the start of combustion, a system bias is adopted to correct the deviation and the error bound of the predicted parameters is within 1.1°. To predict the location of the maximum pressure rise rate and the location of the peak pressure, algorithms based on the proportion of high frequency components in the vibration velocity signals are introduced. Tests results show that the two parameters are able to be predicted within 0.7° and 0.8° error bound respectively. The increase from the knee point preceding the peak value point to the peak value in the vibration velocity signals is used to predict the value of the maximum pressure rise rate. Finally, a monitoring frame work is inferred to realize the combustion parameters prediction. Satisfactory prediction for combustion parameters in successive cycles is achieved, which validates the proposed methods.

Q-factor Tuning and Closed-loop Control for a Resonant Electric Field Micro-Sensor

A method that utilizes vibration velocity signal and differential combs to improve the equivalent Q factor of MEFS is proposed in this study to address charge accumulation on the metal cap surface of an MEMS-based electric field sensor (MEFS) with vacuum package. The MEFS system is characterized by a high degree of nonlinearity, so the averaging method is used to analyze system stability and vibration amplitude. Theoretical and simulation results show that the proposed method is feasible. Experiment results indicate that the larger is the referenced voltage, the larger is the zoom stable vibration amplitude, and the shorter is the transient time. The resulting signal-to-noise ratio is about 92 dB, and the vibration amplitude shows a deviation of 0.2% in 6 min.

Human comfort evaluation criteria for blast planning

To date, blasting vibration safety control standards have focused on minimizing structural damage to the surrounding buildings, and the effects of blasting vibration on people living and working around the blasting site have been overlooked. Blasting vibrations can cause great discomfort and result in lawsuits for compensation. In this paper, the level of discomfort for humans under different blasting vibration levels is classified and investigated. These human responses are quantified by traditional mechanical vibration comfort indicators, such as the vibration dose value and the integrated weighted acceleration. A wavelet transform method is used to analyze the vibration velocity signals and obtain the blasting vibration energy. The evaluation criteria for assessing blasting vibration comfort are presented in a case study. The results have important significance in ensuring blasting safety and maintaining social stability.

Comparison of the vibration sensors used in the estimation of the combustion process in a diesel engine

The vibration signal measured from the cylinder head contains much effective information about the combustion process. The vibration signal can be measured with a vibration displacement sensor, a vibration velocity sensor or a vibration acceleration sensor. In this study the signals measured with the three sensors were compared. The comparison results showed that the vibration displacement measured from the cylinder head is mainly caused by the fixed bracket of the diesel engine, and it is difficult to extract combustion information from the vibration displacement. The vibration velocity signal was compared with the pressure increase rate. The comparison results showed that the two signals have similar trends in the main combustion process. The vibration velocity signal contains much information about combustion. The vibration acceleration signal is hardly influenced by the fixed bracket but contains the vibration response excited by the impact of the opening and closing of the valves and other impact-exciting sources. Based on the results of analyses, it can be concluded that the vibration velocity sensor is the best sensor to estimate the combustion process. The vibration velocity signal was used to estimate the timing of the start of combustion for a two-cylinder homogeneous charge compression ignition engine. The results demonstrated that the accuracy of estimation fulfils the requirement of the application.

Active Vibration Isolation Using a Voice Coil Actuator with Absolute Velocity Feedback Control

This paper describes the active vibration isolation using a voice coil actuator with absolute velocity feedback control for highly sensitive instruments (e.g., atomic force microscopes) which suffer from building vibration. Compared with traditional isolators, the main advantage of the proposed isolation system is that it produces no isolator resonance. The absolute vibration velocity signal is acquired from an accelerator and processed through an integrator, and is then input to the controller as a feedback signal. The controller output signal then drives the voice coil actuator to produce a sky-hook damper force. In practice, the phase response of the integrator at low frequencies (2~6 Hz) deviates from 90 degree which is the exact phase difference between the vibration velocity and acceleration. Therefore, an adaptive filter is used to compensate for the phase error. Analysis of this active vibration isolation system and comparison of model predictions to experimental results indicate that the proposed method significantly reduces transmissibility at resonance without incurring increased transmissibility at higher frequencies.

Fault Diagnosis System of Rotating Machinery Vibration Signal

A high demand has been presented in the measuring and diagnosis of vibration signal of rotating machinery, which can reflect the running state information of rotating machinery equipment. This paper designs a new type of fault diagnosis system of rotating machinery vibration signal, which can measure the vibration acceleration and velocity signals accurately, and analyze the vibration severity and frequency division amplitude spectrum of vibration signal. Experiment showed that our system can diagnose typical mechanical fault.

Comparative study of the nonlinear behavior of fatigued and intact samples of metallic alloys

A method and an experimental setup to study the nonlinear behavior of fatigued and intact metal samples under high-frequency stresses has been developed and tested. The method is based on the measurement of the vibration velocity of stepped bar samples flexurally and/or extensionally vibrating at resonance. The vibration velocity signal, picked up by a laser vibrometer, is automatically acquired and analyzed by classical fast Fourier transform (FFT) methods for different excitation levels. The experimental setup was designed in such a way that it can be used for fatiguing and for testing the material samples. The tests have been done with samples of titanium and aluminium alloys. Results before and after fatigue crack nucleation are compared. A strongly nonlinear, nonclassical behavior is observed for fatigued samples. Theoretical interpretations of the different nonlinear behavior of standing waves in fatigued and intact samples are explored, and the results of the models are qualitatively compared with the experimental data. The models' approach provides an interpretation about the origin of nonlinearity in fatigued samples.

Classification of washing machines vibration signals using discrete wavelet analysis for feature extraction

Wavelets provide a powerful tool for nonstationary signal analysis. In vibration monitoring, the occurrence of occasional transient disturbances makes the recorded signal nonstationary, especially during the start-up of an engine. Through the wavelet analysis, transients can be decomposed into a series of wavelet components, each of which is a time-domain signal that covers a specific octave frequency band. Disturbances of small extent (duration) are amplified relative to the rest of the signal when projected to similar size wavelet bases and, thus, they can be easily detected in the corresponding frequency band. This paper presents a new method for extracting features in the wavelet domain and uses them for classification of washing machines vibration transient signals. The discrete wavelet transform (DWT), in conjunction with statistical digital signal processing techniques, is used for feature extraction. The Karhunen Loeve transform (KLT) is used for feature reduction and decorrelation of the feature vectors. The Euclidean, Mahalanobis, and Bayesian distance classifiers, the learning vector quantization (LVQ) classifier, and the fuzzy gradient classifier are used for classification of the resulting feature space. Classification results are illustrated and compared for the rising part of vibration velocity signals of a variety of real washing machines with various defects.

Intelligent on-line quality control of washing machines using discrete wavelet analysis features and likelihood classification

This paper presents a method for extracting features in the wavelet domain from the vibration velocity signals of washing machines, focusing on the transient (non-stationary) part of the signal. These features are then used for classification of the state (acceptable-faulty) of the machine. The performance of this feature set is compared to features obtained through standard Fourier analysis of the steady-state (stationary) part of the vibration signal. Minimum distance Bayes classifiers are used for classification purposes. Measurements from a variety of defective/non-defective washing machines taken in the laboratory as well as from the production line are used to illustrate the applicability of the proposed method.