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Acoustic Emission (AE) signal has been used pervasively in the extraction of fault feature and the location of damage. The precision of the extraction and location is determined by the propagation characteristics of AE signal in different structures. In this paper, the propagation characteristics of AE wave in the point contact sphere under continuous and transient AE signal is analyzed; a series of experiments under different condition are conducted; based on wave propagation theory, a simulation model is built using the software of ANSYS LS-DYNA. The results of experiments and simulation models reveal that the propagation characteristics-attenuation, frequency features-of AE signal can be manifested clearly in the experiments and are simulated correctly by the simulation model.

Spalling of the races or rolling elements is one of the most common faults in rolling element bearings. Exact estimation of the spall size is helpful to the life prediction for rolling element bearings. In this paper, the dual-impulsive phenomenon in the response of a spalled rolling element bearing is investigated experimentally, where the acoustic emission signals are utilized. A new method is proposed to estimate the spall size by extracting the envelope of harmonics of the ball passing frequency on the outer race from the squared envelope spectrum. Compared with the cepstrum analysis, the proposed procedure shows more powerful anti-noise ability in the fault size evaluation.

Tooth breakage is a typical failure form of wind-turbine planetary gear transmission system, it is important to study the influence of tooth breakage on vibration characteristics of planetary gear transmission system. In this paper, considering the tooth breakage defect, a lumped parameter vibration model of a planetary gear system with time-periodic mesh stiffness is established. Effects of the length and width of tooth breakage on meshing stiffness and dynamic response are discussed in detail. The relation between characteristic frequency of the tooth breakage fault and rotating speeds is pointed out. Several statistical indicators are utilized to show the influence of two parameters (length of planet tooth breakage and input speed) on the dynamic response of the system. Experiments are carried out to verify the simulation results. These results would be useful for fault diagnosis of wind turbine transmission system at different operation conditions.

In this paper, the vibration characteristics of the rotating thin circular cylindrical shell subjected to the radial excitation are presented. Based on the Love’s shell theory, the governing equation of the rotating thin circular cylindrical shell is derived by using the Hamilton’s principle. Then, the amplitude-frequency responses for traveling wave vibration of the circular cylindrical shell are investigated. The results indicate that there exists the traveling wave vibration for the rotating thin circular cylindrical shell, namely: the forward wave and the backward wave. The effects of the damping and excitation on the amplitude-frequency response are analyzed.

The disc-drum type rotors are commonly used in large gas turbine engines. In this paper, the dynamic characteristics of single stage disc-drum structure are studied based on the finite element model, where the connecting bolts are modeled using solid elements and the frictional contact at the joint interface is accommodated. In order to evaluate the nonlinearity resulting from the bolted joints, a finite element (FE) model fixing the disc and drum together is also established, and the simulation results based on the two models are compared. The effects of the bolt preload and the rotating speed on the dynamic characteristics of the disc-drum structure are also discussed. The works proposed in this paper help to enhance the understanding of the dynamics of the disc-drum type rotor.

Periodic impulses in vibration signals and its repeating frequency are the key indicators for diagnosing the localized damage of rolling element bearings. A new method, so called time-wavelet energy spectrum, is proposed to extract the characteristic frequency of faulty elements. It is applied to analyzing the vibration signals of bearings under normal and faulty (with damage on outer race, inner race and ball respectively) statuses. The analysis results show that the time-wavelet energy spectrum is effective in extracting the repeating frequency of periodic impulses. It can not only extract the relatively significant fault feature of outer race damage, but also can extract the weaker fault features of inner race and ball damage.

Fractal dimension reflects the complexity of dynamic systems, and contains the health status information of machinery. The experimental vibration signals of a gearbox with different gear crack size are analyzed using correlation dimension, and it is found that the correlation dimension increases monotonically with the increasing crack level. This is consistent with the nature of a nonlinear dynamic system: the more severe the fault, the more complicated the dynamic system, and accordingly the larger the fractal dimension. Correlation dimension has potential to assess gear localized damage.

The steam turbine is the principal mover in the field of electric power generation. It is very important and necessary to monitor and evaluate the running conditions and diagnose the faults of the steam turbine for the safe and normal running of the electric power plant. Fault diagnosis of the steam turbine is a complicated process and requires high level of the expertise. In order to significantly reduce the cost consumed in the fault diagnosis, increase the consistency of diagnosing decision-making, and better utilize the turbine’s management information resource, in this paper, an integrated Web-based expert system of the fault diagnosis for general purpose has been developed for the steam turbine of a power station. Moreover, it can be regarded as an advisory tool to those field engineers having much technical experience and as a training tool to less-experienced personnel who need guidance and advice. This paper describes a research project aiming to develop a web-based intelligent diagnostic system for the steam turbine, and discusses the process of the fault diagnosis and the issues involved in developing the system. The paper also includes several practical issues related to the architectures of the intelligent web-based applications. The system is built on a three-tier architecture, including the following components: knowledge base, inference engine, knowledge administration interface, user interface, knowledge administration, and integrated database. The diagnostic system employs heuristic rules to diagnose the steam turbine faults.

Based on pattern spectrum entropy and proximal support vector machine (PSVM), a motor rolling bearing fault diagnosis method is proposed in this paper. It is very difficult to filter the fault vibration signals from the strong noise background because the roller bearing fault diagnosis is a problem of multi-class classification of inner ring fault, outer ring fault and ball fault. Firstly, vibration signals are processed by the pattern spectrum. Secondly, the morphological pattern spectrum entropy, and pattern spectrum values are utilized to identify the fault features of input parameters of PSVM classifiers. The experiment results demonstrate that the pattern spectrum quantifies various aspects of the shape-size content of a signal, and PSVM costs a little time and has better efficiency than the standard SVM.

The acoustic emission signals of rolling bearing with different type of defects are de-noised and illustrated by the continuous wavelet transform and scalogram. Morlet wavelet function is selected and the wavelet parameters are optimized based on the principle of minimal wavelet entropy. The soft-threshold de-noising is used to filter the wavelet transform coefficients. The de-noised signals obtained by reconstructing the wavelet coefficients show the obvious impulsive features. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the real AE signal from the defective rolling bearing in experimental test rig. The results indicate that the proposed method is useful and efficient for signal purification and features extraction.

An experimental setup of rotor-bearing system is installed and vibration characteristics of the system with pedestal looseness are investigated. The pretightening bolt between the bearing house and pedestal is adjusted to simulate the pedestal looseness fault. The vibration waveforms, spectra and orbits are used to analyze the nonlinear response of the system with pedestal looseness. Different parameters, including speed, looseness gap, imbalance mass and disk position are changed to observe the nonlinear vibration characteristics. The experiments show that the system motion generally contains the 1/2X fractional harmonic component and multiple harmonic components such as 2X, 3X, etc. Under some special conditions, the pedestal looseness occurs intermittently, that is, occurs in some periods and doesn’t in other periods.

The cyclic autocorrelation function is used with regard to the cyclostationarity of gear vibrations in order to extract the modulation features of gearbox vibration signals, and to detect localized gear damage. The properties of the amplitude and frequency modulated signals in the cyclic frequency domain are summarized in order to investigate the differences between the modulation features of normal and faulty gearbox vibration signals. Gear tooth spalling is detected by the presence of many sidebands in a zero-lag time-slice of the cyclic autocorrelation function, thereby indicating an increase in the degree of modulation effect. The damage source is located by the spacing of the sidebands.

The upper and lower bound estimation of natural frequencies for intelligent truss structure with uncertain-but-bounded parameters is studied in this paper. Firstly, following the finite element method, the expressions of the interval stiffness and interval mass matrix of piezoelectric intelligent truss structures are derived directly from the interval parameters. Then, based on the matrix perturbation and interval extension theory, an interval parameter perturbation method is proposed for solving the upper and lower bound of natural frequencies. Finally, a 16-bar planar intelligent truss structure is used as an example to illustrate the applicability and validity of the presented method, and some useful conclusions are obtained.

In this paper, a method is presented to facilitate the computation of dynamic properties of non-uniform beams with any number of cracks. Based on the Frobenius method, an analytical solution of vibration equation of non-uniform beams is obtained. In combination with the line spring model of crack, the transfer matrices for non-uniform beam element and crack are established respectively. Then the global transfer matrix can be simply formulated, from which the frequency equation in the form of 2×2 determinant is derived. Due to the decrease in the determinant order as compared with previously developed procedures, significant savings in the computational task would be achieved by the present method.

The steam turboset is the key equipment of the electric power system. Thus, it is very important and necessary to monitor and diagnose the running condition and the faults of the steam turboset for the safe and normal running of the electric power system. In this paper, the Internet/Intranet based remote condition monitoring and fault diagnosis scheme is proposed. The corresponding technique and methods are discussed in detail. And a real application system is developed for the 300MW steam turboset. In this scheme, the system is built on the Internet/Intranet and the Client/Server construction and Web/Server model are adopted. The proposed scheme can guarantee real-time data acquisition and on-line condition analysis simultaneously. And especially, the remote condition monitoring and fault diagnosis can be implemented effectively. The developed system has been installed in a power plant of China. And the plant has obtained great economic benefits from it.

The rubbing fault is a very serious and frequent malfunction in rotating machinery, and the determination of the rubbing location is very important in actual fault diagnosis. In this paper, a method based on genetic algorithms to detect the rubbing location is presented. The finite element model of the rubbing rotor is established with the rubbing location, the stator stiffness, the clearance between stator and rotor, the damping coefficient and the friction coefficient as the fault parameters, and the rubbing location determination is transferred into the parameter identification problem. The genetic algorithm is then utilized to search the solution. Using genetic algorithms avoids some of the weaknesses of traditional parameter identification methods such as local minimum problem in nonlinear system identification. The experimental results suggest that the rubbing location can be effectively determined when the rubbing occurs.

From data collected by an online condition monitoring and fault diagnosis system, a higher pad temperature at the upper guide bearing in a pumped storage power generator unit installed in Guangdong province(GPSPS), China, was found. And also a relatively intensive shaft vibration occurred at the lower guide bearing. By calculating the Reynolds equation and viscosity-temperature equation of the lubricant, a curve between the pre-load coefficient and the increment of pad temperature is obtained, which shows that the larger, the pre-load coefficient, the bigger, the increment of pad temperature. For a practical unit in GPSPS, by employing Transfer matrix method and Wilson-θ method to analyze shaft vibration at different pre-load coefficients of the whole bearing or pad pair bearings, the results show that the larger the pre-load coefficient is, the smaller the vibration amplitude is, the shorter the time for vibration to become steady is. And an uneven pre-load coefficient of the pad pair bearings will cause shaft orbit from a circle to an ellipse whose long axes is at the direction of the pad pair with the lowest pre-load coefficient. Finally, reasons of higher pad temperature of the upper guide bearing and larger shaft vibration at the lower guide bearing are due to the inconsistent relation of bearing assembling clearance or pre-load coefficient of the upper and lower guide bearing, and also due to the too small, uneven pre-load coefficient of pad pair bearings. After a scheme for adjusting the bearing clearance is given, data measured show that the analysis and simulation methods are correct and the adjustment scheme to the assembling clearance of the upper and lower guide bearings is feasible and can be used to guide the field maintenance conveniently.