Application of adaptive local iterative filtering and approximate entropy to vibration signal denoising of hydropower unit

In actual field testing environments of hydropower unit, unit vibration signals are often contaminated with noise. In order to obtain the real vibration signal, a vibration signal de-noising method of hydropower unit based on adaptive local iterative filtering (ALIF) and approximate entropy is presented. For the proposed method, the ALIF method is used to decompose vibration signal into several stable components. The approximate entropy of each component is calculated. According to a preset threshold value of approximate entropy, the eligible components are retained to achieve the noise cancellation of hydropower unit’s vibration signals. The ALIF-based method and the wavelet denoising method is compared by simulation signal and real signal. The root mean square error (RMSE), partial correlation index and signal to noise ratio (SNR) are used to evaluate the noise reduction ability of two methods. The results show that compared to the classical wavelet denoising method, the noise canceling ability of this proposed method has improved in some extent. It can more effectively suppress the noise of hydropower unit’s vibration signals. The denoised vibration signals are used to synthesize the shaft orbits of hydropower unit. This can effectively identify the rotor shaft orbit graphics and the operation state of hydropower unit

Transient stability of a hydro-turbine governing system with different tailrace tunnels

This paper focuses on the transient stability of a hydro-turbine governing system with three kinds of tailrace tunnels. As the transfer coefficients change with operation conditions, the dynamic transfer coefficients which can describe the transient characteristics of the hydro-turbine governing system are introduced. Then, the transient stability of the hydro-turbine governing system is analysed. The global bifurcation diagrams for the three kinds of tailrace tunnels are respectively presented to investigate the effects of the tailrace tunnels on the stability of the hydro-turbine governing system. Theoretical analysis which proves the validity of simulation results is provided to explain the effects of the flow inertia and water level fluctuation. The influence of the tailrace tunnel gradient on the transient stability is also studied. More importantly, these methods and research results provide theoretical guidance for the arrangement of the tailrace tunnel and the operation of the hydropower station

Geo-locating Drivers: A Study of Sensitive Data Leakage in Ride-Hailing Services.

Increasingly, mobile application-based ride-hailing services have become a very popular means of transportation. Due to the handling of business logic, these services also contain a wealth of privacy-sensitive information such as GPS locations, car plates, driver licenses, and payment data. Unlike many of the mobile applications in which there is only one type of users, ride-hailing services face two types of users: riders and drivers. While most of the efforts had focused on the rider’s privacy, unfortunately, we notice little has been done to protect drivers. To raise the awareness of the privacy issues with drivers, in this paper we perform the first systematic study of the drivers’ sensitive data leakage in ride-hailing services. More specifically, we select 20 popular ride-hailing apps including Uber and Lyft and focus on one particular feature, namely the nearby cars feature. Surprisingly, our experimental results show that largescale data harvesting of drivers is possible for all of the ridehailing services we studied. In particular, attackers can determine with high-precision the driver’s privacy-sensitive information including mostly visited address (e.g., home) and daily driving behaviors. Meanwhile, attackers can also infer sensitive information about the business operations and performances of ride-hailing services such as the number of rides, utilization of cars, and presence on the territory. In addition to presenting the attacks, we also shed light on the countermeasures the service providers could take to protect the driver’s sensitive information

Shaft orbit identification for rotating machinery based on statistical fuzzy vector chain code and support vector machine

Shaft orbit is a significant diagnosis criterion, and its identification plays an important role in the fault diagnosis of large rotating machinery. The main difficulty of shaft orbit identification is how to extract the shape features automatically and effectively. Therefore, in this paper, a novel method named statistical fuzzy vector chain code (SFVCC) is proposed for the feature extraction of shaft orbit, which has such advantages as invariance, simple calculation and high separability. Furthermore, taking the extracted feature vectors as input, support vector machine (SVM) is utilized to identify various kinds of shaft orbits for rotating machinery. Comparative experiments are implemented, the results reveal that, compared with previous methods, the proposed method can identify the shaft orbit more effectively and efficiently with satisfactory accuracy

Shaft orbit identification for rotating machinery based on statistical fuzzy vector chain code and support vector machine

Shaft orbit is a significant diagnosis criterion, and its identification plays an important role in the fault diagnosis of large rotating machinery. The main difficulty of shaft orbit identification is how to extract the shape features automatically and effectively. Therefore, in this paper, a novel method named statistical fuzzy vector chain code (SFVCC) is proposed for the feature extraction of shaft orbit, which has such advantages as invariance, simple calculation and high separability. Furthermore, taking the extracted feature vectors as input, support vector machine (SVM) is utilized to identify various kinds of shaft orbits for rotating machinery. Comparative experiments are implemented, the results reveal that, compared with previous methods, the proposed method can identify the shaft orbit more effectively and efficiently with satisfactory accuracy

Electromagnetic Vibration Simulation of a 250-MW Large Hydropower Generator with Rotor Eccentricity and Rotor Deformation

The electromagnetic vibration caused by electromagnetic force on the stator has threatened large hydro generators operating safely and stably. At the Zhexi hydropower station, the hydro generator was beset by electromagnetic vibration for a long time. Therefore, the paper provided a new method to help to find the vibration source and detect the hydro generator fault, through the combination of simulation and experiments. In this paper, the 3D stator pack structure model and the 2D hydro generator electromagnetic models under rotor eccentricity and rotor ellipse deformation conditions were built. Then, electromagnetism simulations were conducted to study the characteristics of the electromagnetic flux and electromagnetic force under different conditions by using the finite element method (FEM). Lastly, the vibration testing experiments and harmonic response simulations of stator frame were performed to present the characteristics of vibration distribution in frequency conditions. The simulation results were compared with the generator measured data to try to find out the main vibration source and guide the overhaul

Dynamic Characteristics and Successive Start-Up Control Strategy Optimization of Pumped Storage Units under Low-Head Extreme Conditions

With inherent ‘S’ characteristics and the one-tunnel-with-two-units arrangement of the pump-turbine, hydraulic transient changes in the successive start-up process are complex, and the optimal control is difficult. This paper aims to study the dynamic characteristics and successive start-up control strategy optimization of two hydraulic couplings pumped storage units (PSUs) under low-head extreme conditions. Firstly, an accurate model of two hydraulic coupling PSUs’ successive start-up is established. Based on this model, the influence of the interval time of successive start-up on the dynamic characteristics of PSUs is carried out. It is shown that the change of the interval time of the successive start-up (ΔT) of the two PSUs has a significant impact on the dynamic response stability of the low-head start-up. If ΔT is more than 40 s, the hydraulic oscillation and speed fluctuation of the PSUs deteriorate. Secondly, with the different controller parameters for the two PSUs, a novel multi-objective optimization scheme with fractional order PID controller (FOPID) is proposed to figure out the best control scheme for the successive start-up. Furthermore, selecting the sum of the rise time (Tr) of the rotating speed of two PSUs and the sum of the integral time absolute error (ITAE) of two PSUs is the objective. Meanwhile, the optimization scheme of PID with different parameters (PIDDP) is used to compare and verify the optimization method proposed in this paper. The results for this extreme condition indicate that FOPID has more significant advantages in optimizing the instability of the successive start-up process, with the better Pareto front, and the optimized scheme has a more stable dynamic transition process of flow, water hammer pressure, and rotational speed