Research On Working Conditions Adaptive Intelligent Construction System Of Large Full Section Ballast Cleaning Machine

After long period operation of the ballast bed,the ballast will be broken and pulverized,as a result,the drainage capacity of the track is reduced,causing diseases such as compaction,mud slushing,etc.,and overhaul work are required periodically to restore ballast bed performance.The full-section ballast cleaning machine is one of the main equipment in the maintenance of the ballast bed.The 13^th Five-Year Development Plan of China Railway emphasizes that modernization,intelligence and greenness are the development direction of track maintenance machinery.However,the full-section ballast cleaning machine still stops at the stage of manual operation following experience,resulting in cleaning output lower than the design value under harsh working conditions,which is difficult to meet the demand for railway maintenance after railway speed increase and railway network expansion.To solve the above problems,based on working conditions identification and dynamic distribution of engines power,a working conditions adaptive intelligent construction system was designed in this paper to improve the cleaning output under harsh working conditions.The main research contents of this paper are as follows:Firstly,the power characteristics of each working device of the ballast cleaning machine under different working conditions was analyzed,and the working conditions adaptive intelligent construction system based on power autonomous dynamic distribution was proposed.The principles and methods of engines power dynamic distribution and the workflow of the intelligent construction system was determined.And then,the selection of hydraulic components of the construction system and the design of hydraulic schematics was completed.Secondly,a double closed-loop working conditions adaptive control strategy was designed,which the global condition adaptive control is outer loop and local condition adaptive is inner loop.The global working condition adaptive outer loop control strategy based on working conditions identification and working device power decision library was designed.Aiming at the shortcomings of the global working conditions adaptive control when the local working condition changes abruptly,a single neural PID controller with self-learning capability was adopted to realize the adaptive inner loop control of the local working conditions.Thirdly,the mathematic models of pump displacement changing mechanism was established,and a fuzzy adaptive PID controller based on reference model was designed,and the simulation model of excavation device with severe shock load and large inertia was established in AMESim,and the analysis of the controller is carried out through the co-simulation of AMESim and Simulink.The result shows that the controller can effectively reduce the shock load on the working device during the dynamic distribution of engines power,improve the operating life of the hydraulic components and the safety of the ballast cleaning work.Finally,the co-simulation model of the working conditions adaptive intelligent construction system is established in AMESim and Simulink,which the hydraulic system load was simulated by using the experimental data to modify the load theoretical calculation and the simulation model of diesel engine is established by fitting the characteristic curve.The working conditions adaptive intelligent construction system was simulated under different working conditions,and the results show that the construction system has strong adaptability to the working conditions,and responds quickly when local working condition changes abruptly.The cleaning output reached the design value under the harsh working conditions,which fully exerts the potential of the ballast cleaning machine.