BackgroundA 7.0-magnitude earthquake hit Lushan County in China’s Sichuan province on April 20, 2013, resulting in 196 deaths and 11,470 injured. This study was designed to analyze the characteristics of the injuries and the treatment of the seismic victims.MethodsAfter the earthquake, an epidemiological survey of injured patients was conducted by the Health Department of Sichuan Province. Epidemiological survey tools included paper-and-pencil questionnaires and a data management system based on the Access Database. Questionnaires were completed based on the medical records of inpatients with earthquake-related injuries. Outpatients or non-seismic injured inpatients were excluded. A total of 2010 patients from 140 hospitals were included.ResultsThe most common type of injuries involved bone fractures (58.3%). Children younger than 10 years of age suffered fewer fractures and chest injuries, but more skin and soft -tissue injuries. Patients older than 80 years were more likely to suffer hip and thigh fractures, pelvis fractures, and chest injuries, whereas adult patients suffered more ankle and foot fractures. A total of 207 cases of calcaneal fracture were due to high falling injuries related to extreme panic. The most common type of infection in hospitalized patients was pulmonary infections. A total of 70.5% patients had limb dysfunction, and 60.1% of this group received rehabilitation. Most patients received rehabilitation within 1 week, and the median duration of rehabilitation was 3 weeks. The cause of death of all seven hospitalized patients who died was severe traumatic brain injuries; five of this group died within 24 h after the earthquake.ConclusionsInjuries varied as a function of the age of the victim. As more injuries were indirectly caused by the Lushan earthquake, disaster education is urgently needed to avoid secondary injuries.

To mitigate the large demand for safflower picking labour and the low efficiency of manual picking, a safflower picking robot that is based on a parallel manipulator is designed. The whole robot mainly consists of a walking device, parallel manipulator device, vision device, picking device, filament collection device, control system, and motor drive system. The forward and inverse kinematics analysis of the parallel manipulator is analysed via a geometric method, the kinematics model is established, and the computational analysis of the parallel manipulator working speed is based on the Jacobi matrix. For driving angle errors of 0.001~0.005°, the moving platform's motion accuracy is 0.2174-0.9387 mm, which meets the position accuracy requirements of the test stage. Based on MATLAB software, the Monte Carlo method is employed to solve the working space of the parallel manipulator, which is approximately an equilateral triangle with a side length of 0.35 m, which satisfies the safflower growth space picking conditions. The prototype is constructed, and safflower picking experiments are carried out under laboratory conditions. The average picking period of each flower bulb was 16 s, and the average net picking rate of the filaments was 87.91%. The experimental results verified the applicability of the safflower picking robot.

At this stage, safflower picking is mostly performed manually or semi-manually, the picking method is antiquated and the picking precision is low. In this experimental study, a new attitude tilt levelling system was designed for a safflower-picking robot, which has created a solid foundation for the realization of future safflower-picking machine automation. The mobile platform was simplified as a four-point support, and an automatic levelling control system was designed based on the multi-sensor data collected by a multi-inclination sensor, a multi-pressure sensor, and a displacement sensor. The error range of the levelling of the mobile platform was obtained by MATLAB simulation analysis, the relationship between the inclination of the mobile platform and the displacement of the levelling mechanism was analyzed by coordinate transformation, and the maximum levelling range of the levelling mechanism was analyzed. On this basis, an automatic levelling control system was designed. Finally, the safflower-picking mobile platform was tested, and we concluded that the levelling control system can adjust the inclination angle of the mobile platform to within 0.2° and the levelling time to within 7 s. The design of the automatic levelling control system fills the gap in the field of safflower picking and adopts multi-sensor fusion. Compared with other methods, the collected inclination data is more accurate, the levelling accuracy higher, and the levelling time shorter. The final results show that this experimental study provides a strong basis for the realization of the full-mechanical automation of safflower picking.

This paper discusses the design of a safflower picking robot control system and focuses on a navigation control subsystem based on multisensor fusion. A navigation subsystem, an identification and positioning subsystem, a picking subsystem, and a levelling subsystem are designed. The hardware and software of the navigation subsystem are designed in detail, and a multisensor fusion positioning method based on extended Kalman fusion technology is proposed. The accuracy and stability levels of different combined navigation methods are compared. To test the effectiveness and accuracy of the proposed method, an outdoor test is carried out. The test results show that the outdoor fusion positioning accuracy of the robot is less than 8 cm, and when the satellite signal is lost, the navigation control subsystem can still provide high positioning accuracy. The final positioning result obtained using the integrated positioning method of the wheel odometer + IMU + DGNSS is approximately 52% higher than that of the odometer, approximately 29% higher than that of the wheel odometer + IMU, and approximately 11% higher than that of the IMU + DGNSS.

HIGHLIGHTSA load and bale density monitoring and control system for a wheeled self-propelled square baler is proposed.A hydraulic circuit and weighing device are designed, and a bale density control model is established on this basis.The relationships among the main parameters affecting the operation of the control system are determined.The control system improved the automation and reliability of the square baler machine as a low-cost solution.Abstract. This study investigated baler load monitoring and automatic adjustment of bale density. A load monitoring and bale density adjustment system was developed for a wheeled self-propelled square baler. To realize the proposed system, a hydraulic circuit and a weighing device were designed, a bale density control program was developed, and a bale density control model was established. Bench tests were performed to obtain the relationships among the feed quantity of the baler, the load of the hydraulic cylinder on the compression chamber sidewall, the bale density, the piston’s compression force, the bale weight, and the degree of bale compression. The relationships among the operating parameters provided basic data for baler load monitoring and intelligent control of bale density. Field tests showed that when the bale density threshold was set at 5 kg m-3 and the allowable deviation was 2 kg m-3, the coarse adjustment time was less than 5 s, and the adjustment deviation of the bale density was within 5% as a whole, while most of the deviations were within 3%. The results demonstrate that the proposed control system can realize automatic adjustment of bale density according to user requirements within the allowable range. In addition, the proposed system can ensure stable operation and provide a reference for optimization and intelligent control of balers. Keywords: Bale density, Feeding load, Monitoring and control system, Square baler.