The Key Technology Research On Oil Sludge Tank Cleaning And Treatment System

The oil tank cleaning task consists of two processes which is dangerous and arduous.There are many problems in traditional manual cleaning methods and the various existing mechanized as well as the automated tank cleaning system.Therefore,it is necessary to develop another advanced automated tank cleaning system.It is an automatic closed cleaning system with the characteristics of energy-saving,emission reduction and without people into the tank.In view of the existing problems,research work is carried out as follows:1)First of all,starting from the harm of oil tank bottom sludge,its basic characteristics and the cleaning process index are analyzed;the present research status,the tank cleaning system problems,and developing trend as well as key technology both at home and in abroad are also analyzed;according to the above research,current situation and research on the key technology of oil tank cleaning robot is briefly reviewed.2)The general design requirement is put forward.The physical connection relation is constructed between all the components and the general structure which is composed of cleaning system,resource processing system and integrated control system.The operating principle of each subsystem is also analyzed.The design idea and its performance index on the key component of the oil sludge tank cleaning robot have been put forward.The characteristics of its structure have been studied respectively from body,walking unit,cleaning unit as well as sensing unit.Finally,the on-board oil sludge tank model and its internal layout are preliminary designed.3)The design of the nozzle is the core technology of cleaning effect.In order to facilitate the self-excited pulsed nozzle design and manufacture,the self-excited pulsed nozzle model is established to solve the problems of complex design model,undetermined boundary conditions,constrain condition by experience.An adaptive particle swarm optimization algorithm is advanced which take the force output as the maximum optimization objective and the structure parameters of nozzle model is optimized.The more accurate constraint condition of self-excited nozzle is concluded and the problem of the self-excited nozzle design and manufacture of uneasy qualitative representation boundary conditions has been solved.4)In order to solve the problem of the impact of pulse water jet vibration on overturning stability of the robot,the stable cone method applied under the robot’s static state,cleaning disc brush rotating,walking and pulse water jet cleaning,the overturning stability of the robot is analyzed on the basis of the analysis of oil tank cleaning robot working environment.To the two latter more unstable motion states,simulation analysis is carried out with ASAMS software.The simulation results are consistent with the the design parameters of the robot.5)On the basis of contrastive analysis graphic,Monte Carlomethod and simulation method used to solve the robot working space,the optimization method of working space for oil tank cleaning robot has been put forward.In view of the fact of flat vertical oil tank bottom,an adaptive variable steps,variable crowed degree factor and variable vision domain adaptive article fish swarm algorithm(AAFSA)is advanced to design a kind of two-dimension path planning algorithm for mobile oil tank cleaning robot.For the practical problem of curved horizontal oil tank bottom,a three-dimension space robot path planning method is advanced based on adaptive ant colony(AACS).And combined with the experiment,the effectiveness of the two algorithms is verified.6)A pure physical treatment process for dealing with oil sludge is put forward and the effect to the oil tank cleaning by the process parameters from ultrasonic intensity,ultrasonic time,ultrasonic temperature,oil viscosity,centrifugal rotational speed and centrifugal time on the oil tank sludge has been analyzed.And several process parameters influence and effect are analyzed by combining orthogonal experiment with normalization.7)In the light of centrifuge,the key equipment of the sludge treatment process,the optimization mathematical model of the entrifuge parameters is founded based on the APSO-RBF neural network.The optimal controller is established to adjust the centrifuge operating parameter by taking advantage of adaptive particle swarm optimization technology and neural network technology and the problem of centrifuge operating parameter optimization is solved.