International Journal of Rotating Machinery

Performance feature extraction is the primary problem in equipment performance degradation assessment. To handle the problem of high-dimensional performance characterization and complexity of calculating the performance indicators in flexible material roll-to-roll processing, this paper proposes a PCA method for extracting the degradation characteristic of roll shaft. Based on the analysis of the performance influencing factors of flexible material roll-to-roll processing roller, a principal component analysis extraction model was constructed. The original feature parameter matrix composed of 10-dimensional feature parameters such as time domain, frequency domain, and time-frequency domain vibration signal of the roll shaft was established; then, we obtained a new feature parameter matrix by normalizing the original feature parameter matrix. The correlation measure between every two parameters in the matrix was used as the eigenvalue to establish the covariance matrix of the performance degradation feature parameters. The Jacobi iteration method was introduced to derive the algorithm for solving eigenvalue and eigenvector of the covariance matrix. Finally, using the eigenvalue cumulative contribution rate as the screening rule, we linearly weighted and fused the eigenvectors and derived the feature principal component matrix of the processing roller vibration signal. Experiments showed that the initially obtained, 10-dimensional features of the processing rollers’ vibration signals, such as average, root mean square, kurtosis index, centroid frequency, root mean square of frequency, standard deviation of frequency, and energy of the intrinsic mode function component, can be expressed by 3-dimensional principal components , and . The vibration signal features reduction dimension was realized, and , and contain 98.9% of the original vibration signal data, further illustrating that the method has high precision in feature parameters’ extraction and the advantage of eliminating the correlation between feature parameters and reducing the workload selecting feature parameters.

With the development of high-speed crafts, new propulsion systems are introduced into the marine industry. One of the new propulsion systems is linear jet which is similar to pump jet and has a rotor, a stator, and a duct. The main difference between this system and pump jet is the placement of linear jet system under the hull body and inside a tunnel. Since this system, like a water jet, is inside the tunnel, the design idea of this system is a combination of a water jet and pump jet. In this paper, hydrodynamic performance of linear jet propulsion system is numerically investigated. To this end, the OpenFOAM software is utilized and RANS steady equations are solved using a - turbulent model. The linear jet geometry is produced by assembling a Kaplan rotor, stator with a NACA 5505 cross section, and a decelerating duct. The results of numerical solution in the form of thrust, torque coefficient, and efficiency are compared with available experimental data for a ducted propeller, and good agreement is displayed. Subsequently, the hydrodynamic parameters are computed in two conditions: with a stator and without a stator. By comparing the results, it is observed that the total thrust coefficient of the propulsion system with a stator at all advance ratios increases by at least 40%. It is further observed that addition of a stator also improves its efficiency.

Online monitoring of high-speed rotating blades has always been a hot topic. Of the various methods, the blade tip timing (BTT) technique, based on eddy current sensors, is considered to be the most promising. However, BTT signals are easily influenced by various factors, which means that the accurate extraction of BTT signals remains a challenge. To try to solve this problem, the causes of measurement error were analyzed. The three main reasons for the error were established: the variation in blade tip clearance, the interference of background noise, and the asymmetry of the blade tip shape. Further, pertinent improvement methods were proposed, and a compensation method was proposed for the errors caused by the variation of tip clearance. A new denoising and shaping algorithm based on ensemble empirical mode decomposition (EEMD) was introduced for the errors caused by background noise. Additionally, an optimal installation position of the sensor was also proposed for the errors caused by the asymmetry of the blade tip shape. Finally, simulations and experiments were used to demonstrate the improved methodology. The results show that the measurement error on vibration amplitude and vibration frequency using the proposed method is less than 2.89% and 0.17%, respectively, which is much lower than the traditional method (24.44% and 0.39%, respectively).

To determine the process of icing on the rotating machinery, an icing experiment on a rotating airfoil blade was carried out in this paper. First, an icing wind tunnel was fabricated, and its conditional parameters were calibrated. The calibration results showed that the performance of this icing wind tunnel was reliable and stable. The experimental temperature was -15°C, and the MVD was 50 μm. Then, an icing experiment on the rotating blade with the NACA0018 airfoil was carried out. The characteristics of icing, including icing distribution, growth rate of icing, and thickness of the ice layer, were defined and quantitatively analyzed under different tip speed ratios and setting angles. The results show that the type of icing changes from rime ice to glaze ice with an increase in the tip speed ratio. The dimensionless icing area and dimensionless thickness of the ice layer both increase with an increase in the icing time. The growth rate of icing increases rapidly at the initial icing stage and then decreases dramatically under each tip speed ratio condition.

Bearing fault signal analysis is an important means of bearing fault diagnosis. To effectively eliminate noise in a fault signal, an adaptive multiscale combined morphological filter is proposed based on the theory of mathematical morphology. Both simulation and experimental results show that the adaptive multiscale combined morphological filter can remove noise more thoroughly and retain details of the fault signal better than the dual-tree complex wavelet filter, traditional morphological filter, adaptive singular value decomposition method (ASVD), and improved switching Kalman filter (ISKF). The adaptive multiscale combined morphological filter considers both positive and negative impulses in the signal; therefore, it has strong adaptability to complex noise in the environment, making it an effective new method for bearing fault diagnosis.

This paper describes the method of preparing strong hydrophobic polypyrrole (PPy) on wind turbine blades. The water contact angle of strong hydrophobic PPy coatings was 127.2°. The strong hydrophobic PPy coatings exhibited excellent anti-icing properties. The maximum icing weight of strong hydrophobic PPy coating blade was almost 0.10 g while the maximum icing weight of no coating blade was found to be 26.13 g. The maximum icing thickness of a strong hydrophobic PPy coating blade was only 1.08 mm. The current research will provide a better technique to create anti-icing coatings on wind turbine blades and other outdoor equipment.