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.

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.

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.

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.

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 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%.

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.

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.