Vibration Monitoring Research Articles

Identification and separation of coupled vibration sources in multi-rotor gas turbines under time-varying speed conditions

Vibration sources in multi-rotor gas turbines under time-varying speed conditions are strongly coupled in the time–frequency domain, which prevents further mining of dynamic information from measured signals. Hence, a novel scheme of vibration source identification and separation is proposed to obtain individual source information. Firstly, the order and resonance components are identified by order analysis, and precise order numbers are further determined by computed order tracking. Then, in four typical vibration source coupling scenarios, the performances of Vold-Kalman filter (VKF), several typical adaptive mode decomposition methods and derivative methods are comparatively studied using Jeffcott rotor simulation system. Finally, the optimal source separation based on VKF and variational mode decomposition/extraction (VMD/VME) is determined. Furthermore, the settings of VKF filter bandwidth are studied quantitatively, and the effects of VMD and VME penalty factors are analyzed. In conclusion, the proposed scheme effectively identifies and accurately separates vibration sources from the test bed and gas turbine datasets, which provides important evidences for vibration monitoring and control as well as vibration transmission analysis of gas turbines.

Effects of Vibration on Adjacent Pipelines under Blasting Excavation

Exploring a pipeline’s response to blast vibration during tunnel excavation is critical for ensuring the safety of the pipeline. In this paper, the vibration monitoring and numerical simulation methods are used to evaluate the dynamic response of ground soil and pipelines to blasts. The attenuation law of peak particle velocity (PPV) and the distribution characteristics of peak effective stress (PES) in pipe sections under different working conditions are studied. The following findings are recorded: (1) A three-dimensional model considering in situ stress is established, and it is found the triangular equivalent load simulation blast effect method used in this paper can effectively reflect the impact of blasting on pipelines. The simulation error is controlled at 7.69%. (2) The ground PPV of each monitoring point decays continuously with the increase in horizontal and axial distance, and the cavity enlargement effect is exhibited above the excavation area. The oncoming blast side PPV of the pipe section is more significant than that behind the blast side. (3) When the blast vibration is transmitted to the pipe, there are differences in the PPV and PES distribution characteristics across the pipe cross-section. The PPV is greater in the lower part of the pipe section, while the PES value is greater in the upper part of the pipe section. The maximum PES of 1.53 MPa is significantly lower than the safety threshold (≤4.6 MPa) at the hazardous-section-monitoring point. (4) A pipeline PPV prediction model is proposed to guide subsequent blasting program development. An empirical formula for the safety criterion applicable to this study is proposed for the scientific implementation of safety assessments for subsequent construction. This safety evaluation framework can be used as a reference for similar projects.

Multi-Vib

Vibration measurement is vital for fault diagnosis of structures (e.g., machines and civil structures). Different structure components undergo distinct vibration patterns, which jointly determine the structure's health condition, thus demanding simultaneous multi-point vibration monitoring. Existing solutions deploy multiple accelerometers along with their power supplies or laser vibrometers on the monitored object to measure multi-point vibration, which is inconvenient and costly. Cameras provide a less expensive solution while heavily relying on good lighting conditions. To overcome these limitations, we propose a cost-effective and passive system, called Multi-Vib, for precise multi-point vibration monitoring. Multi-Vib is implemented using a single mmWave radar to remotely and separately sense the vibration displacement of multiple points via signal reflection. However, simultaneously detecting and monitoring multiple points on a single object is a daunting task. This is because most radar signals are scattered away from vibration points due to their tilted locations and shapes by nature, causing an extremely weak reflected signal to the radar. To solve this issue, we dedicatedly design a physical marker placed on the target point, which can force the direction of the reflected signal towards the radar and significantly increase the reflected signal strength. Another practical issue is that the reflected signal from each point endures interferences and noises from the surroundings. Thus, we develop a series of effective signal processing methods to denoise the signal for accurate vibration frequency and displacement estimation. Extensive experimental results show that the average errors in multi-point vibration frequency and displacement estimation are around 0.16Hz and 14μm, respectively.

Measuring of rotating shafts angular deformation by means of ultrasonic vibration meter

The task of measuring of rotating shafts angular deformation by means of ultrasonic vibration meter is considered in the article. Measurement of vibration parameters of rotating objects is an urgent task in the technical diagnostics of electromechanical units, turbines, drilling rigs and metal-cutting machines subject to vibration disturbances. The measured vibration parameters of rotating shafts include their angular deformation and torques arising from torsional vibrations of shafting of machines in the stationary and mobile objects. Timely monitoring of the torsional vibrations of the shafting and other factors of vibration disturbances by the frequency of shaft beats makes it possible to identify defects at an early stage and eliminate breakdowns that threaten the life and safety of personnel. It was found out that the reflected acoustic signal phase measurement relative to the reference one incident onto the investigated shaft surface can be carried out with error at 0.6 % at velocities not more than 0.5 m/s. This article is intended for mechanical engineers involved in the development and operation of rotating machines of stationary and mobile objects.

A Novel GB-SAR System Based on TD-MIMO for High-Precision Bridge Vibration Monitoring

Ground-based synthetic aperture radar (GB-SAR) is a highly effective technique that is widely used in landslide and bridge deformation monitoring. GB-SAR based on multiple input multiple output (MIMO) technology can achieve high accuracy and real-time detection performance. In this paper, a novel method is proposed to design transmitting and receiving array elements, which increases the minimum spacing of the antenna by sacrificing several equivalent phase centers. In MIMO arrays, the minimum antenna spacing in the azimuth direction is doubled, which increases the variety of antenna options for this design. To improve the accuracy of the system, a new method is proposed to estimate channel phase errors, amplitude errors, and position errors. The position error is decomposed into three directions with one compensated by the phase error and two estimated by the strong point. Finally, we validate the accuracy of the system and our error estimation method through simulations and experiments. The results prove that the GB-SAR system performs well in bridge deformation and vibration monitoring with the proposed method.

Application and Comparison of Non-Contact Vibration Monitoring Methods for Concrete Railway Sleepers

This paper describes the non-contact vibration monitoring of prestressed reinforced concrete railway sleepers. The monitoring was carried out using physical measuring equipment consisting of a seismograph and geophones, a robotic total station (RTS) and scanning laser Doppler vibrometry (SLDV) equipment. Measurements of the dynamic response of sleepers to the dynamic loading induced by the running of train sets provides data that give an insight into the actual state of the sleeper structure at the moment when it is most stressed. The main objective of the study was to identify the most appropriate form of monitoring to monitor events related to the occurrence of cracks in the rail sill, which can also be caused by the impact of vibration. As is well-known, monitoring the dynamic response of railway sleepers is very important for the sustainable management and maintenance of railway lines. The vibration analysis was carried out in the field on the Ormož–Ptuj section of the railway line, in Velika Nedelja and in the laboratory of the UM FGPA, where the vibration was simulated using a hydraulic kit with a static and pulsed force of 100 kN. Several cycles of measurement were carried out and the results were compared with the results of the field monitoring. The vibration parameters measured for the concrete sleepers are necessary to develop a realistic dynamic model of the railway line, which will be able to predict its response to impact loads and the possible occurrence of damage, as has recently been observed for concrete sleepers in several European Union countries.

Research on recognition algorithm of impact vibration based on HOG feature of time–frequency spectrum

The time–frequency spectrum of the vibration signal obtained based on the time–frequency transformation algorithm can fully reflect the energy distribution at any time–frequency coordinate. But this characteristic is not easy to be insight and generalized by the human eye, especially in the era of big data, in the face of massive data and rapid processing. During the research, we found that this information can be clearly expressed in the histogram of oriented gradient (HOG) feature of the time–frequency spectrum. Therefore, the time–frequency spectrum support vector machine classifier based on the HOG feature of the vibration signal has considerable feasibility. This article had conducted in-depth research on this idea, determined the advantages of wavelet time–frequency spectrum for signal recognition, and further selected wavelet basis and kernel function. A comprehensive test of the HOG parameters had finally achieved a good recognition effect. The comprehensive recognition accuracy of the algorithm for the impact and vibration signals collected in this paper was stable at about 96%. The research results will be applied to the future smart city vibration monitoring system. On the other hand, it may provide a new idea to improve the accuracy of the current battlefield target recognition system.

Torsional vibration feature extraction method from lateral vibrations based on decomposed forward and backward whirl motions

The high-speed turbomachinery rotor-bearing system faces potential torsional vibration problems due to its large span, flexible structure, and the wildly use of variable frequency drive systems. In this paper, a method based on the Hilbert technique to extract weak torsional vibration signals from measured lateral vibration signals is proposed, and the forward whirl signal is constructed to make full use of the information contained in lateral vibration signals. Furthermore, it was found that the forward whirl signal has better stability and stronger anti-noise ability after comparing the utilization of horizontal, vertical, forward, and backward vibration signals applied to the proposed method to extract the torsional vibration signal from simulated vibration responses of a rotor system. Numerical simulation and experimental results indicate that the method can detect torsional vibration signals accurately, with a high resolution in frequency estimation. This method enables additional monitoring of torsional vibrations for machines without dedicated torsional vibration testers and provides a convenient way to measure torsional vibrations in engineering applications.

Dynamic performance verification of the Rędziński Bridge using portable camera-based vibration monitoring systems

The assessment of dynamic performance of large-scale bridges typically relies on the deployment of wired instrumentation systems requiring direct contact with the tested structures. This can obstruct their operation and create unnecessary risks to the involved personnel and equipment. These problems can be readily avoided by using non-contact instrumentation systems. However, the cost of off-the-shelf commercial products often prevents their wide adoption in engineering practice. To this end, the dynamic performance of the biggest one-pylon cable-stayed bridge in Poland is investigated based on data from a consumer-grade digital camera and open access image-processing algorithms. The quality of these data is benchmarked against data obtained from conventional wired accelerometers and a high-end commercial optical motion capture system. Operational modal analysis is conducted to extract modal damping, which has a potential to serve as an indicator of structural health. The dynamic properties of the bridge are evaluated against the results obtained during a proof loading exercise undertaken prior to the bridge opening. It is shown that a vibration monitoring system based on consumer-grade digital camera can indeed provide an economically viable alternative to monitoring the complex time-evolving dynamic behaviour patterns of large-scale bridges.

Design and Implementation of a vibration monitor protecting the cable from external destruction

Underground cable is one of the main components of urban power supply systems. However, it is often damaged by large machinery in the process of urban road construction. To protect the underground cable, this paper proposes a novel design of a smart vibration device based on a complex embedded system, including the STM32 control chip, vibration sensors, NB-IoT communication module, and charging module. Through vibration signal detection of the excavator and other large-scale mechanical behavior, the vibration device can indicate the direction where the damage is occurring, and send out a warning message to the operation center. Finally, some experiments for vibration monitoring devices are conducted to verify their effectiveness and future application potential prospects.

Highly Efficient Fault Diagnosis of Rotating Machinery Under Time-Varying Speeds Using LSISMM and Small Infrared Thermal Images

The existing fault diagnosis methods of rotating machinery constructed with both shallow learning and deep learning models are mostly based on vibration analysis under steady rotating speed. However, the rotating speed frequently changes to meet practical engineering needs. The shallow learning models largely depend on domain experience of feature extraction, and training a deep learning model requires large samples and a long time. In addition, vibration monitoring has the shortcomings of contact measurement, small coverage, and noise interference. To address these problems, this article proposes a new fault diagnosis method with the least square interactive support matrix machine (LSISMM) and infrared thermal images. In this method, a novel matrix-form classifier called LSISMM is constructed under the concept of nonparallel interactive hyperplanes to fully leverage the structure information of infrared thermal images. To improve the computation efficiency, a new least square loss constraint is designed for LSISMM. Besides, we derive an effective solution framework based on the alternating direction method of the multiplier (ADMM) framework. The constructed LSISMM is directly used to analyze the collected thermal images of rotating machinery under time-varying speeds. Experiment results demonstrate that the proposed method is superior to state-of-the-art methods in terms of diagnosis accuracy and efficiency, especially under small thermal image samples.

On-Shaft Wireless Vibration Measurement Unit and Signal Processing Method for Torsional and Lateral Vibration

Microelectromechanical systems accelerometers have opened new possibilities for vibration monitoring of a rotating machinery. They enable mounting accelerometers directly to the rotating component of the machine, e.g., shaft. This enables not only the measurement of a lateral vibration but also a torsional vibration of the machine. This increases the vibration data gathered from the machine by one measurement instrument. This article presents an on-shaft wireless universal measurement unit (UMU) with innovative combination of features, such as a high measurement range and easy mounting. The UMU has a two-sensor configuration where two accelerometers are mounted to the opposite sides of a shaft. This enables to utilize a novel signal processing method to separate torsional and lateral vibration from the data. The signal processing method combines and modifies methods presented in the published literature. The results presented in this article demonstrate that the UMU together with the presented signal processing method can measure frequencies of torsional and lateral vibration accurately. However, the amplitude comparison between the UMU and reference sensors cannot be done adequately because they are measuring either different components of the machine or different physical properties.

Reconstruction of Vehicle-Induced Vibration on Concrete Pavement Using Distributed Fiber Optic

Vibration of concrete pavement contains valuable information in the time, space, and frequency domain, which is beneficial to loading characteristics identification and structural health monitoring. However, these multidimensional features have a significant locality and need to measure effectively. This paper proposes a novel method by using distributed fiber optic to measure the temporal, spatial, and spectral distribution of pavement vibration, as well as reconstruct them into a vibration field for feature analysis. First, a vibration monitoring system with designed units was developed to measure the vibration of concrete pavement. Then reconstruction and analysis methods of the vibration field were proposed to process the one-dimensional measured data. Finally, a series of experiments were conducted to validate the performance of the system and methods under different loading types, speeds, magnitude, and positions. According to the results of the impulse loading test, accelerated pavement test, and traffic loading test, it indicates the system can measure the vibration of concrete pavement with sufficient positioning precision (0.33 m), sampling frequency (2500 Hz), and frequency accuracy (<±1 Hz). Also, based on the data processing method, the vibration field can be reconstructed and analyzed effectively to reflect traffic behaviors like braking and lane change.

Monocular Vision-Based Calibration Method for the Axial and Transverse Sensitivities of Low-Frequency Triaxial Vibration Sensors With the Elliptical Orbit Excitation

The low-frequency triaxial vibration sensors have been gradually applied in many engineering fields of vibration monitoring because they can measure the multidirection vibrations simultaneously. The accurate axial and transverse sensitivities, determined by the calibration method, are the prerequisite for ensuring their measurement accuracy. Currently, the laser interferometry (LI) which is based on a single component or a tricomponent linear shaker is usually applied to calibrate these sensitivities. However, the former has to require the multiple reinstallations of the sensor and the latter cannot avoid the motion coupling caused by the shaker, these inevitably increase the calibration uncertainty. In this article, we investigate a monocular vision (MV)-based two-component shaker calibration method, which determines the axial sensitivity based on the time-spatial synchronization and transverse sensitivity at the elliptical orbit excitation. The MV method is used to measure this excitation, and a plane sensitivity model is presented to describe these sensitivities. This investigated method can simultaneously reduce the uncertainties caused by the reinstallations and motion coupling to improve the calibration accuracy. Experimental results compared with the LI and Earth's gravitation method demonstrate that the investigated method obtains the satisfactory accuracies both in axial sensitivity magnitude and phase as well as transverse sensitivity magnitude and direction calibration.

Fault Diagnosis of Two Rotor System

Abstract: Misalignment and unbalance are the most probably common cause of machine vibration. Vibration monitoring is a useful technique for application to rotating machinery and provides valuable information regarding symptoms of machinery failure which may avoid costly breakdown. Understanding and practicing the fundamentals of rotating shaft parameter is the firststep in reducing unwanted vibration. Experimental studies were performed on two rotor dynamic test apparatus to predict the vibration spectrum for different faults. The experimental test rig was designed and tested for misalignment and unbalance condition. The rotor shaft accelerations were measured at 1000 rpm speed using four channel vibration FFT (Fast Fourier Transform) analyzer. The experimental frequency spectra were obtained for misalignment and unbalanced condition leading to reliable diagnostic information.

Real-time cutting tool condition assessment and stochastic tool life predictive models for tool reliability estimation by in-process cutting tool vibration monitoring

Real-time cutting tool condition assessment and stochastic tool life predictive models for tool reliability estimation by in-process cutting tool vibration monitoring

Vibration effect and ocean environmental impact of blasting excavation in a subsea tunnel

Drill-blast method is one of the important methods in the current subsea tunnel excavation construction. Controlling the vibration effect during blasting construction and its impact on the marine environment has been a key topic in the construction of subsea tunnels. This paper takes the Xiamen subsea tunnel excavation and blasting project as the background, combines blast vibration monitoring in the tunnel and underwater sound pressure testing in seawater, analyzes the attenuation law of subsea tunnel blast vibration propagation along the rockmass, studies of the characteristics of shock waves formed in water following the propagation of blast stress waves to seawater. Based on the dynamic finite element numerical calculation, the impact of blasting vibration effect of mainline tunnel on the adjacent built service tunnel structure and the characteristics of shock wave pressure distribution in water excited by blasting vibration are analyzed. Considering the influence of the burial depth of tunnel blasting source, a mathematical prediction model of the attenuation law of underwater sound pressure in water caused by subsea tunnel blasting is established. Based on the pressure control standard of marine organism safety, the control range of marine organism safety under the influence of subsea tunnel blasting is proposed.

Vibration Monitoring and Semisupervised Multivariate Invertible Deep Probabilistic Learning for Gearbox Faults Identification

The identification of faults for gearbox plays a significant role in maintaining high reliability of industrial equipment. Multivariate invertible deep probabilistic learning (MIDPL), as a generative model, assesses the distribution characteristics of the hidden condition using observations. It is a high-dimensional-to-high-dimensional transformation and is limited by poor classification performance. In this article, semisupervised MIDPL (S-MIDPL) fault identification method is proposed to overcome the drawback of MIDPL. First, the dimension of the observation is reduced. Second, supervised learning is performed based on the reduced dimension to improve the classification performance. Fault identification validations on a gearbox test bench and wind turbine gearbox are conducted to investigate the effectiveness of the proposed method. Comparisons with other state-of-the-art classification methods have also been conducted. The results indicate that S-MIDPL has a significant advantage over MIDPL and a variational inference-based semisupervised approach.

Real-Time Virtual Sensing for Dynamic Vibration of Flexible Structure via Fiber Bragg Grating Sensors

Real-time monitoring of the dynamic vibrations of beam-type structures indicates important implications in aerospace engineering applications, in which the additional sensing information about vibration parameters, including displacements, rotational angles, angular rates, as well as accelerations, facilitates the improvement of the system’s safety. This article proposed a virtual sensing method with the usage of fiber Bragg grating (FBG) strain sensors to directly estimate the vibration parameters from the measured strains. The algebraic relationships of displacement–strain and rotation–strain on the sensor’s installing points as well as the boundary points are obtained based on the Birkhoff interpolation method, and meanwhile, the explicit expressions on angular rates and accelerations are derived. Furthermore, a tracking differentiator is used to recover the strain signals and their first- and second-order derivatives from the noisy measurements in order to real-time estimate the angular rates and accelerations of the vibrating beam. Differing from the classical modal-based method, complex modal decomposition is not required in the proposed method. The comparison of numerical simulation results reveals that the proposed method has advantages over the modal-based method in accuracy and efficiency. Furthermore, the laboratory experiments indicate that the proposed method is effective for real-time estimating vibration parameters from the noisy measured strains.

Effects of Blasting Vibrations on an Arch in the Jiaohuayu Tunnel Described by Energy Response Spectrum Analysis

The vibrations caused by tunnel blasting strongly affects the construction safety and progress of the tunnel itself. The arch vibration attenuation law, structural energy response, and safety criterion were systematically investigated using blasting vibration monitoring in the Jiaohuayu Tunnel. The peak particle velocity (PPV) at the vault was always larger than that at the arch waist and was greater than that at the sidewall, regardless of the direction. The arch waist was where the initial lining had the highest risk of damage. Existing safety criteria can be supplemented and improved using the maximum instantaneous input energy to measure the first passage damage, the hysteretic energy consumption to measure the cumulative damage, and the input-hysteretic energy criterion to judge the structural failure. The energy threshold of the first passage damage of the initial lining structure was 200 J, and the plastic cumulative damage was 3000 J of the test section. This study is important when evaluating the safety of a tunnel’s initial lining structure.