A Comprehensive 3-Steps Methodology for Vibration-Based Fault Detection,Diagnosis and Localization in Rotating Machines

In any industry,it is the requirement to know whether the machine is healthy or not to operate machine further.If the machine is not healthy then what is the fault in the machine and then finally its location.The paper is proposing a 3-Steps methodology for the machine fault diagnosis to meet the industrial requirements to aid the maintenance activity.The Step-1 identifies whether machine is healthy or faulty,then Step-2 detect the type of defect and finally its location in Step-3.This method is extended further from the earlier study on the 2-Steps method for the rotor defects only to the 3-Steps methodology to both rotor and bearing defects.The method uses the optimised vibration parameters and a simple Artificial Neural Network(ANN)-based Machine Learning(ML)model from the earlier studies.The model is initially developed,tested and validated on an experimental rotating rig operating at a speed above 1st critical speed.The proposed method and model are then further validated at 2 different operating speeds,one below 1st critical speed and other above 2nd critical speed.The machine dynamics are expected to be significantly different at these speeds.This highlights the robustness of the proposed 3-Steps method.

The Advantages of Using Rotating Machines with Profiled Rotors

In order to achieve a lower consumed energy, the performance of a new type of rotating volumetric pump with two profiled rotors (variant I) which is compared with a centrifugal pump (variant II) is presented. The analysis regarding the same flow rate of transported liquid and the same pressure increases points out the conduct of the system at the variation of the key operating parameters. The actual driving power of the rotating volumetric pump is higher stating that is more advantageous in operation. The effective efficiency of the system is improved due to the original constructive solution.

Trend Prediction Method Based on the Largest Lyapunov Exponent for Large Rotating Machine Equipments

In order to predict electromechanical equipments＇ nonlinear and non-stationary condition effectively, max Lyapunov exponent is introduced to the fault trend prediction of large rotating mechanical equipments based on chaos theory. The predict method of chaos time series and two methods of proposing f and F are dis- cussed. The arithmetic of max prediction time of chaos time series is provided. Aiming at the key part of large rotating mechanical equipments-bearing, used this prediction method the simulation experiment is carried out. The result shows that this method has excellent performance for condition trend prediction.

Control of seismic and operational vibrations of rotating machines using semi-active mounts

A dual isolation problem for rotating machines consists of isolation of housing structures from the machine vibrations and protection of machines during an earthquake to maintain their functionality. Desirable characteristics of machine mounts for the above two purposes can differ significantly due to difference in nature of the excitation and performance criteria in the two situations. In this paper, relevant response quantities are identified that may be used to quantify performance and simplified models of rotating machines are presented using which these relevant response quantities may be calculated. Using random vibration approach with a stationary excitation, it is shown that significant improvement in seismic performance is achievable by proper mount design. Results of shaking table experiments performed with a realistic setup using a centrifugal pump are presented. It is concluded that a solution to this dual isolation problem lies in a semi-active mount capable switching its properties from ‘operation-optimum’ to ‘seismic-optimum’ at the onset of a seismic event.

On-line Condition Monitoring and Diagnostic Network System for Rotating Machine Set

Several industrial computers and a server are combined to set up the on-line monitoring and diagnostic system of turbo-generator sets. The main function of the system is to monitor machine sets' running condition. Through analyzing running data, technicians can detect whether there exist faults and where they occur. To share and transmit the dynamic information of the turbo-generator sets, a distributed network system is introduced. NetWare network operating system is used in the LAN (Local Area Network) system. The LAN is extended to realize the sharing of data and remote transmission of information. Furthermore, functions of monitoring and diagnostic clients are listed.

Active Vibration Control of Rotating Machines with Active Machine Foot Mounts on Soft Foundations Based on a 3D-Model

The paper presents a simplified 3D-model for active vibration control of rotating machines with active machine foot mounts on soft foundations, considering static and moment unbalance. After the model is mathematical described in the time domain, it is transferred into the Fourier domain, where the frequencies response functions regarding bearing housing vibrations, foundation vibrations and actuator forces are derived. Afterwards, the mathematical coherences are described in the Laplace domain and a worst case procedure is presented to analyze the vibration stability. For special controller structures in combination with certain feedback strategies, a calculation method is shown, where the controller parameters can be directly implemented into the stiffness matrix, damping matrix and mass matrix. Additionally a numerical example is presented, where the vibration stability and the frequency response functions are analyzed.

Orthogonal On-Rotor Sensing Vibrations for Condition Monitoring of Rotating Machines

Thanks to the fast development of micro-electro-mechanical systems(MEMS)technologies,MEMS accelerometers show great potentialities for machine condition monitoring.To overcome the problems of a poor signal to noise ratio(SNR),complicated modulation,and high costs of vibration measurement and computation using conventional integrated electronics piezoelectric accelerometers,a triaxialMEMS accelerometer-based on-rotor sensing(ORS)technology was developed in this study.With wireless data transmission capability,the ORS unit can be mounted on a rotating rotor to obtain both rotational and transverse dynamics of the rotor with a high SNR.The orthogonal outputs lead to a construction method of analytic signals in the time domain,which is versatile in fault detection and diagnosis of rotating machines.Two case studies based on an induction motor were carried out,which demonstrated that incipient bearing defect and half-broken rotor bar can be effectively diagnosed by the proposed measurement and analysis methods.Comparatively,vibration signals from translational on-casing accelerometers are less capable of detecting such faults.This demonstrates the superiority of the ORS vibrations in fault detection of rotating machines.

Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation

The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source domain.However,in engineering scenarios,achieving such high-quality label annotation is difficult and expensive.The incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled samples.To overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three parts.First,a residual network with dual classifiers is to learn features from cross-domain samples.Second,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source domain.With the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised learning.Third,the adaptation trajectories are designed for sample distributions across domains.This ensures that the target domain samples are only adapted with the pure-labeled samples.The LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related machines.The results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.

Pulsed field magnetization of multiple bulks used as field pole of a high-temperature superconducting rotating machine

An array of three GdBa_(2)Cu_(3)O_(7‐δ)bulk high‐temperature superconductors(HTS)that mimic the field pole of a high‐power superconducting motor had been magnetized by pulsed field magnetization(PFM)while cooled by liquid nitrogen.The bulk array was magnetized by a passive PFM technique using three vortex‐type coils placed over each individual bulk and connected in series.The trapped magnetic flux density distribution was comparable to the distribution obtained with more traditional quasi‐static magnetization such as field‐cooling.This suggests that the use of PFM technique on arrays of HTS bulks is possible.PFM has also been performed using each coil individually,to magnetize each bulk sequentially.The magnetization sequences showed a maximum reduction of the peak trapped magnetic flux density of 12%due to the demagnetization effect of the magnetization sequence,while the trapped magnetization distribution was improved.

Partial Discharge Measurement of OCP-Tapes in Rotating Electrical Machines

Nowadays, PD （partial discharge） measurements are a crucial part of the preventive maintenance of electrical equipment within high voltage engineering. Especially for electrical machines, both the supplier and the user are interested in the results of PD measurements. However, PDs hardly represent the cause of the failure, more likely they are claimed as the outcome of a failure. This paper deals with the insulation of a 6 kV electrical machine, whereas PD measurements were carried out at a single stator from wound coils. During manufacturing, these coils were equipped with different materials for the OCP （outer corona protection）. Using different PD measurement systems and different bandwidths, investigations of the PD behavior of the coils were carried out. Additionally, the surface resistivity of the corona protection was determined. As a result, conclusions for the correlations between the resistance of the OCP as well as the PD behavior are stated. Furthermore, the influence of using different measurement systems, different measuring circuits, and different bandwidths is shown.

Numerical-Analytical Method for Magnetic Field Computation in Rotational Electric Machines

A numerical-analytical method is applied for the two-dimensional magnetic field computation in rotational electric machines in this paper. The analytical expressions for air gap magnetic field are derived. The pole pairs in the expressions are taken into account so that the solution region can be reduced within one periodic range. The numerical and analytical magnetic field equations are linked with equal vector magnetic potential boundary conditions. The magnetic field of a brushless permanent magnet machine is computed by the proposed method. The result is compared to that obtained by finite element method so as to validate the correction of the method.

A Study on the Levitation Control of the Multi-degrees-of-Freedom Rotational Machine Supported by Magnetic Bearings Using Flux Feedback

This paper deals with an open-loop characteristic of a magnetically levitated system including flux feedback. In order to design a controller to obtain a good disturbance rejection and to be insensitive to parameter variations, it might be useful to employ a flux feedback loop. The air gap flux which can be sensed by a proper sensor has linear relationship with respect to the change of the current and the air gap. This linear property decreases the inherent nonlinearity of the magnetic suspension system that is caused by the coupling between the electrical actuator and the mechanical plant. Simulation results achieved from a multi-degree-of-freedom numerical model show that the flux feedback loop makes an improvement of the performance of the magnetic suspension system against the load variations.

State Estimation for Sound and Vibration Emitted from a Machine Based on Sound Measurement Under Existenceof Background Noise

Many studies on the diagnosis for machines have become important recently because of increased use of various complex industrial systems.The correlation information between sound and vibration is very important for machine diagnosis.Usually,vibration pickups are attached directly to the machine in order to measure vibration data.However,in some cases,the sensors can not be attached directly on highly precise devices.In this study,a method to estimate the fluctuation of sound and vibration is proposed based on the measurement data of sound emitted from the machine under existence of background noise.The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor.

A laser shaft alignment system with dual PSDs

Shaft alignment is an important technique during installation and maintenance of a rotating machine. A high-precision laser alignment system has been designed with dual PSDs (Position Sensing Detector) to change traditional manual way of shaft alignment and to make the measurement easier and more accurate. The system is comprised of two small measuring units (laser transmitter and detector) and a PDA (Personal Digital Assistant) with measurement software. The laser alignment system with dual PSDs was improved on a single PSD system, and yields higher measurement accuracy than the previous design, and has been successful for designing and implements actual shaft alignment. In the system, the range of offset measurement is ±4 mm, and the resolution is 1.5 μm, with accuracy being less than 2 μm.

A Novel Method Based on UNET for Bearing Fault Diagnosis

Reliability of rotating machines is highly dependent on the smooth rolling of bearings.Thus,it is very essential for reliable operation of rotating machines to monitor the working condition of bearings using suitable fault diagnosis and condition monitoring approach.In the recent past,Deep Learning(DL)has become applicable in condition monitoring of rotating machines owing to its performance.This paper proposes a novel bearing fault diagnosis method based on the processing and analysis of the vibration images.The proposed method is the UNET model that is a recent development in DL models.The model is applied to the 2D vibration images obtained by transforming normalized amplitudes of the time-series vibration data samples into the corresponding vibration images.The UNET model performs pixel-level feature learning using the vibration images owing to its unique architecture.The results demonstrate that the model can perform dense predictions without any loss of label information,generally caused by the sliding window labelling method.The comparative analysis with other DL models confirmed the superiority of the UNET model which has achieved maximum accuracy of 98.91%and F1-Score of 99%.

Influence of Temperature Probes Installation on the Salient Pole to Temperature Measurement

Accurate and reliable information about the temperature of the synchronous generators excitation winding hot spot is necessary to determine the dynamic limit caused by excitation winding overheating in the PQ diagram. For good estimation of a position and the hot spot temperature it is decided to mount 19 temperature probes on one pole of the 6-pole, 400 kVA. 50 llz synchronous generator. Due to a large number of the probes and because the probes should be glued with the metal epoxy it was assumed that mounting of the probes will disrupt the temperature field of the excitation winding. To get the answer to this question the excitation winding resistance was measured betbre and after mounting the probes, in a hot and a cold state. Temperature rise can be estimated if the resistance ratio in the hot and the cold state is known. The paper also addresses the analysis of the measurement accuracy. The result shows that, there is no significant influence on the temperature when mounting the 19 temperature probes which covered 10% of the pole excitation winding surface.

Degradation of PAI/PEI Enamel under High Temperature (Up to 400°C)

This work deals with the understanding of the degradation of the primary insulation (PEI/PAI) of rotating machines working temporarily under high-temperature. The main domain of application of these motors is the smoke extraction either from tunnels or underground parking when a fire occurs. In such a critical situation, the internal temperature of the motor winding may reach temperatures up to 400°C. Under such very high thermal stresses, the behaviour of the electrical insulation is not well understood. This work proposes an analysis of the decomposition gases under very high temperatures and the corresponding degradation pathway. A simple method is proposed to identify whether the insulation of such motors has been strongly damaged during the working time at very high temperatures, thus allowing estimating if it can still continue to operate.

Optimal Design of Novel Electromagnetic-Ring Active Balancing Actuator with Radial Excitation

Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the efficiency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during the operational process,different types of active balancing actuators have been designed and widely applied in actual production.However,the existing electromagnetic-ring active balancing actuator is designed based on an axial excitation structure which can cause structural instability and has low electromagnetic driving efficiency.In this paper,a novel radial excitation structure and the working principle of an electromagnetic-ring active balancing actuator with a combined driving strategy are presented in detail.Then,based on a finite element model,the performance parameters of the actuator are analyzed,and reasonable design parameters are obtained.Self-locking torque measurements and comparative static and dynamic experiments are performed to validate the self-locking torque and driving efficiency of the actuator.The results indicate that this novel active balancing actuator has sufficient self-locking torque,achieves normal step rotation at 2000 r/min,and reduces the driving voltage by 12.5%.The proposed novel balancing actuator using radial excitation and a combination of permanent magnets and soft-iron blocks has improved electromagnetic efficiency and a more stable and compact structure.

Analysis of Unbalances Forces Using Methods of Identification and Finite Elements

The study of damage in rotating machineries is of fundamental interest in the fields of machine and structure design. A rotating system, supported by bearings and under some dynamic conditions, can generate a variety of problems that are encountered in many different types of rotating machines. One of these problems is the unbalance due to non-homogeneous mass distribution along the shaft. One of the techniques which are widespread today is the identification of parameters and excitation forces that may well followed by monitoring the evolution and change of possible variations of these parameters. Although several methods for the identification of unbalance excitation force are available in the literature, none of them can be considered unrestricted to be applied for all rotating systems. In this study, two methodologies to identify unknown excitations, such as unbalance, have been proposed. This project refers to the analysis of unbalanced forces from displacement parameters and speed by using methods of identification by Fourier series and Legendre polynomials together with the finite element method, state observers in reasons of the problem of absence of signs of rotational displacement, bandpass filter were used to noise suppression of the data collected from the experimental part, Quasi-Newton method to minimize a function in which the bearing stiffness and its damping are unknowns, and also the experimental verification of the methodology, using for this system owned by a rotary mechanical vibrations of the Department of Mechanical Engineering of Faculty of Engineering, campus of llha Solteira.

Review:Partial discharge diagnostics in wind turbine insulation

The purpose of this paper is to review work undertaken on partial discharges and their influence on the insulation of wind turbines. No matter whether partial discharges can be considered as the main cause of deterioration of the insulation material, the initial cause of failure or not but an indication of the material degradation, there is no doubt that they are intimately linked to the aging of machine insulation. Material degradation can be detected by non-destructive techniques (e.g., partial discharge measurements, change of tan δ) or by destructive techniques, such as by cutting small pieces of the insulating material and by putting them under the scrutiny of the scanning electron microscope (SEM). Wind generators are a modern subject of research, especially in view of the growing demands of electric energy worldwide and the problems facing the environment all over the globe. Wind turbines are a novel field of research regarding partial discharge diagnostics since they are subjected to a variety of aging factors, which are different from conventional turbines. In this respect, particular attention should be paid to the multi-factor stressing of insulation and their consequences on the partial discharges.