The development of real time data driving multi-axis linkage and synergic movement control system of 3D variable cross-section roll forming machine

The three dimensional variable cross-section roll forming is a kind of new metal forming technol- ogy which combines large forming force, multi-axis linkage movement and space synergic movement, and the sequential synergic movement of the ganged roller group is used to complete the metal sheet forming according to the shape of the complicated and variable forming part data. The control system should meet the demands of quick response to the test requirements of the product part. A new kind of real time data driving multi-axis linkage and synergic movement control strategy of 3D roll forming is put forward in the paper. In the new control strategy, the forming data are automatically generated according to the shape of the parts, and the multi-axis linkage movement together with cooperative motion among the six stands of the 3D roll forming machine is driven by the real-time information, and the control nodes are also driven by the forming data. The new control strategy is applied to a 48 axis 3D roll forming machine developed by our research center, and the control servo period is less than 10ms. A forming experiment of variable cross section part is carried out, and the forming preci- sion is better than ＋ 0.5mm by the control strategy. The result of the experiment proves that the control strategy has significant potentiality for the development of 3D roll forming production line with large scale, multi-axis ganged and svner^ic movement

Spatio-temporal Variations in Plantation Forests'Disturbance and Recovery of Northern Guangdong Province Using Yearly Landsat Time Series Observations(1986-2015)

Forest disturbance plays a vital role in modulating carbon storage,biodiversity and climate change.Yearly Landsat imagery from 1986 to 2015 of a typical plantation region in the northern Guangdong province of southern China was used as a case study.A Landsat time series stack(LTSS) was fed to the vegetation change tracker model(VCT) to map long-term changes in plantation forests' disturbance and recovery,followed by an intensive validation and a continuous 27-yr change analysis on disturbance locations,magnitudes and rates of plantations' disturbance and recovery.And the validation results of the disturbance year maps derived from five randomly identified sample plots with 25 km^2 located at the four corners and the center of the scene showed the majority of the spatial agreement measures ranged from 60% to 83%.A confusion matrix summary of the accuracy measures for all four validation sites in Fogang County showed that the disturbance year maps had an overall accuracy estimate of 71.70%.Forest disturbance rates' change trend was characterized by a decline first,followed by an increase,then giving way to a decline again.An undulated and gentle decreasing trend of disturbance rates from the highest value of 3.95% to the lowest value of 0.76% occurred between 1988 and 2001,disturbance rate of 4.51% in 1994 was a notable anomaly,while after 2001 there was a sharp ascending change,forest disturbance rate spiked in 2007(5.84%).After that,there was a significant decreasing trend up to the lowest value of 1.96% in 2011 and a slight ascending trend from 2011 to 2015(2.59%).Two obvious spikes in post-disturbance recovery rates occurred in 1995(0.26%) and 2008(0.41%).Overall,forest recovery rates were lower than forest disturbance rates.Moreover,forest disturbance and recovery detection based on VCT and the Landsat-based detections of trends in disturbance and recovery(LandT rendr) algorithms in Fogang County have been conducted,with LandT rendr finding mostly much more disturbance than VCT.Overall,disturbances and recoveries in northern Guangdong were triggered mostly by timber needs,policies and decisions of the local governments.This study highlights that a better understanding about plantations' changes would provide a critical foundation for local forest management decisions in the southern China.

Optimum Driving System Design for Dual-Motor Pure Electric Vehicles

A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the architecture of the transmission system,we propose vehicle performance parameters and performance indexes of a pure electric vehicle,a time-sharing driving strategy of dual motors.First,the parameters of the battery,motor,and transmission system are matched.Then,the electric vehicle transmission model is built in Amesim and the control strategy is designed in Simulink.With the optimization goal of improving the vehicle’s dynamic performance and driving range,the optimal parameters are determined through analysis.Finally,the characteristics of the motor are tested on the bench.The results show that the energy-saving potential of the timesharing driven double motor is higher,and the driving mileage of the double motor drive is increased by 4%.

Selection of the Proper Hammer in Pile Driving and Estimation of the Total Driving Time

There are various methods for analyzing pile driving process such as dynamic formulas, wave equation analyses and dynamic measurements. The programs of the two latter methods are relatively expensive to purchase and also require trained engineers to interpret the data it collects. Meanwhile, the use of the site specific empirical formulas based on the real cases of pile driving and output analyses of the wave equation analysis programs can be beneficial. In the current study, pile driving data from three sites in the south of Iran were collected. Using the data of these cases and one-dimensional wave equation analysis program GRLWEAP, couple of experimental formulas which determine the proper range of hammer＇s ID for driving a pile, are proposed. Finally, due to the importance of the time in marine projects, another experimental formula is also proposed for estimation of the total driving time.

Dangerous Driving Behavior Recognition and Prevention Using an Autoregressive Time-Series Model

Time headway is an important index used in characterizing dangerous driving behaviors. This research focuses on the decreasing tendency of time headway and investigates its association with crash occurrence. An autoregressive（AR） time-series model is improved and adopted to describe the dynamic variations of average daily time headway. Based on the model, a simple approach for dangerous driving behavior recognition is proposed with the aim of significantly decreasing headway. The effectivity of the proposed approach is validated by means of empirical data collected from a medium-sized city in northern China. Finally, a practical early-warning strategy focused on both the remaining life and low headway is proposed to remind drivers to pay attention to their driving behaviors and the possible occurrence of crash-related risks.