Modal analysis is the vital prerequisite of the full-scale fatigue test of the wind turbine blade. In order to resolve the difficulty in solving the characteristic equation of the transfer matrix method in modal analysis, a method of solving the characteristic equation based on particle swarm optimization is proposed. Firstly, the beam model is used to simplify and discrete the blade along the spanwise of the blade. A concept of average bending stiffness is used for the elasticity assignment with beam segment, and the blade kinematics model is established. Subsequently, a designed particle swarm optimization is used to solve the characteristic equation. Finally, the proposed method is verified by modal analysis of an MW-scale blade. On this basis, the effect of the mass and position of the counterweight on the mode shape is investigated. The results indicate that the proposed method can provide a theoretical reference for the fatigue test technology of wind turbine blades.

Wire arc additive manufacturing (WAAM) has been investigated to deposit large-scale metal parts due to its high deposition efficiency and low material cost. However, in the process of automatically manufacturing the high-quality metal parts by WAAM, several problems about the heat build-up, the deposit-path optimization, and the stability of the process parameters need to be well addressed. To overcome these issues, a new WAAM method based on the double electrode micro plasma arc welding (DE-MPAW) was designed. The circuit principles of different metal-transfer models in the DE-MPAW deposition process were analyzed theoretically. The effects between the parameters, wire feed rate and torch stand-off distance, in the process of WAAM were investigated experimentally. In addition, a real-time DE-MPAW control system was developed to optimize and stabilize the deposition process by self-adaptively changing the wire feed rate and torch stand-off distance. Finally, a series of tests were performed to evaluate the control system’s performance. The results show that the capability against interferences in the process of WAAM has been enhanced by this self-adaptive adjustment system. Further, the deposition paths about the metal part’s layer heights in WAAM are simplified. Finally, the appearance of the WAAM-deposited metal layers is also improved with the use of the control system.

In order to obtain the probabilistic stress-fatigue life curve of materials with small samples, a small sample P-S-N curve fitting method is proposed. This method is based on the premise that Weibull distribution can be applied to fatigue test data the method first uses the sample mean fitting to obtain the median S-N curve. Secondly, constructs the random variable function based on the Weibull distribution characteristics, in addition, the sample median is used as the initial value of iteration to perform perturbation optimization to determine the shape parameter a and the scale parameter β of Weibull distribution. The fitting of P-S-N curve is realized. Taking the fatigue data of aluminum alloy 2425-T3 as an example, the results show that the intercept relative error and slope error are less than 0.5% by comparing the fitting results of the proposed method with those of the traditional method, and the intercept error between the proposed method and the traditional method is less than 1.5% and the slope error is small when designing three groups of small sample fitting schemes (7-7-7-7, 5-5-5, 3-3-3) at 3.0%. The proposed method can obtain high-precision P-S-N curve fitting results in the case of small samples, which have a certain significance for engineering applications.

No abstract

Wire arc additive manufacturing (WAAM) has been investigated to deposit large-scale metal parts due to its high deposition efficiency and low material cost. However, in the process of automatically manufacturing the high-quality metal parts by WAAM, several problems about the heat build-up, the deposit-path optimization, and the stability of the process parameters need to be well addressed. To overcome these issues, a new WAAM method based on the double electrode micro plasma arc welding (DE-MPAW) was designed. The circuit principles of different metal-transfer models in the DE-MPAW deposition process were analyzed theoretically. The effects between the parameters, wire feed rate and torch stand-off distance, in the process of WAAM were investigated experimentally. In addition, a real-time DE-MPAW control system was developed to optimize and stabilize the deposition process by self-adaptively changing the wire feed rate and torch stand-off distance . Finally, a series of tests were performed to evaluate the control system’s performance . The results show that the capability against interferences in the process of WAAM has been enhanced by this self-adaptive adjustment system. Further, the deposition paths about the metal part’s layer heights in WAAM are simplified. Finally, the appearance of the WAAM-deposited metal layers is also improved with the use of the control system.