Multi-Excitation Fatigue Testing for Large Full-Scale Wind Turbine Blade

In order to solve the problem of insufficient exciting force of equipment for large full-scale wind turbine blade fatigue testing,the influence of gravity on the performance of excitation equipment and fatigue damage evaluation of the different positions of wind turbine blades are analyzed.With the multi-excitation loading in the horizontal direction,the actuator force of the excitation equipment does not need to overcome the gravity of the dynamic mass,which directly outputs the exciting force of the system vibration.The excitation efficiency of the equipment is 77%higher than that of the vertical load.The gravity moment of the horizontal loading mode is perpendicular to the loading direction.That is,the mean load in the flapwise direction is zero.The weight of excitation equipment could replace the tuning mass on the condition that the self-weight of equipment is reduced by the multi-excitation mode,which helps the excitation equipment play the comprehensive function of excitation equipment and tuning mass.At the same time,the gravity moment in the edgewise direction will be decreased by 17.0%22.5%under the multi-excitation horizontal loading mode.In the vertical loading mode,the gravity moment is the mean load,which only increases fatigue damage accumulation by 15.6%.By comparing the role of gravity in the excitation equipment and fatigue damage evaluation,the multi-excitation horizontal loading mode has more advantage to performance the exciting force than the contribution of gravity to the fatigue damage accumulation in the vertical loading mode.Through the fatigue testing of multi-excitation horizontal loading,the potential of excitation equipment is explored,and the problem of insufficient exciting force in large full-scale wind turbine blade fatigue testing will be solved.

Fine-Grained Action Recognition Based on Temporal Pyramid Excitation Network

Mining more discriminative temporal features to enrich temporal context representation is considered the key to fine-grained action recog-nition.Previous action recognition methods utilize a fixed spatiotemporal window to learn local video representation.However,these methods failed to capture complex motion patterns due to their limited receptive field.To solve the above problems,this paper proposes a lightweight Temporal Pyramid Excitation(TPE)module to capture the short,medium,and long-term temporal context.In this method,Temporal Pyramid(TP)module can effectively expand the temporal receptive field of the network by using the multi-temporal kernel decomposition without significantly increasing the computational cost.In addition,the Multi Excitation module can emphasize temporal importance to enhance the temporal feature representation learning.TPE can be integrated into ResNet50,and building a compact video learning framework-TPENet.Extensive validation experiments on several challenging benchmark(Something-Something V1,Something-Something V2,UCF-101,and HMDB51)datasets demonstrate that our method achieves a preferable balance between computation and accuracy.

Meyer-Neldel Rule in Plasma Polythiophene Thin Films

In polymers, the electronic activation energy depends on the fragmentation, crosslinking, dopants, moisture and in general on the structure-environment interaction. This has a special importance in plasma polymers because fragmentation and crosslinking are usually higher than in other polymers. In this work, DC electrical conductivity of polythiophene thin films prepared by plasma (pPTh) was studied using the Meyer-Neldel (MN) rule to calculate the characteristic MN energy and temperature as a function of moisture and metallic dopants. The experimental data for pPTh synthesized in different conditions indicated that EM = 32 meV and TM = 373 K, suggesting a thermally activated conduction mechanism;however, in polymer-metal matrices with metal concentration higher than the percolation threshold, the conduction mechanism is different causing that the MN rule was only partially fulfilled. The congruence of the experimental data with the multiexcitation entropy model is discussed.