Tower crane is a kind of hoisting machinery widely used for construction and hydropower construction, which plays a non-substitutable role. But it often happens to accidents causing heavy loss. The paper firstly made use of fishbone diagram for accident causes of tower crane on qualitative analysis, then mainly making use of the analytic hierarchy process on quantitative analysis.Through the combination of the fishbone diagram and the analytic hierarchy process,the major accident causes of tower crane were found, classified and analyzed. It provided a theoretical support and reference for reducing accidents of tower crane and improving engineering efficiency and quality.

Wind turbine gearbox is subjected to different sorts of failures, which lead to the increasement of the cost. A approach to fault diagnosis of wind turbine gearbox based on empirical mode decomposition (EMD) and teager kaiser energy operator (TKEO) is presented. Firstly, the original vibration signal is decomposed into a number of intrinsic mode functions (IMFs) using EMD. Then the IMF containing fault information is analyzed with TKEO, The experimental results show that EMD and TKEO can be used to effectively diagnose faults of wind turbine gearbox.

NC machine tools are generally thought to be with a high degree of automation, high precision, high reliability and high efficiency characteristics. But because of the inherent flaws of the machine mechanical structure, such as screw wear, assembly errors or repeated positioning error, the machining accuracy may reduce. Therefore, this paper describes a self-compensating system design FPGA-based NC machine tools. Using Programmable devices(FPGA) and Hardware description language(VHDL) to achieve self-compensation system controller development, Position measurement from absolute encoder in real-timing, Comprehensive building of NC machine tools since compensation control system.

it is very necessary for electricity market operation to accurate forecasting monthly electricity consumption, influencing factors of electricity consumption, there are non-linear and strong correlation, taking into account the cyclical trend of the monthly electricity consumption, this paper raises a monthly electricity consumption forecast model based on kernel partial least squares and exponential smoothing regression. The forecast model is the first to use kernel partial least squares regression methods to predict the annual electricity consumption, and then combined with exponential smoothing obtained monthly electricity accounts for the proportion of electricity consumption throughout the year for each month of the year to be measured power consumption . Instance analysis and calculation results show that the method has higher prediction accuracy, good practicality and feasibility.

When working, tower crane is affected by natural environment and is subjected to complex various loads. So it is not very easy to analyze its dynamic performance at system level. Some researchers have done some work as to simulation and analysis of tower crane, in order to study its dynamic performance. While much of their work based on grid body model but not flexible body model. This paper used SolidWorks and ADAMS to build the virtual prototype of a tower crane based on ADAMS flexible body. After the co-simulation, which joined ADAMS with SolidWorks, force of the connection between tower crane base and the strengthened section of the crane was recorded and analyzed. And so was the acceleration of the tower crane’s lifting rig. Succeeding in the application of Virtual Prototyping Technology based on ADAMS flexible body, this study can be used to direct the work, operation and fault diagnosis of tower crane, and lay a basis for further studies.