Research Of Intelligent Compaction Control And Intelligent Fault Diagnosis For Vibratory Roller

In the robot technology Priority , which is in the field of the advanced manufacturing and automation technology under the National High Technology Research and Development Program of China (863 Program), airmada intelligentized engineering machinery is identified as one of 4 Subject areas. Airmada intelligentized fundamental is the single machine intelligence. The intelligentized technologies of vibratory road roller are researched in this paper from the three aspects: intelligent compaction control, intelligent fault diagnosis and intelligent human-machine interaction so as to do beneficial exploration and pioneering work for the research and development of the airmada engineering machinery. Research results of this paper are as follows:1. On the basis of introducing the vibratory compaction mechanism , impacts of the vibratory road roller's main working parameters on compacting effect are analysed by building the dynamic model of vibratory road roller. The ultimate composition of intelligent compaction control system of vibratory road roller is given.Therefore, the theoretical basis is laid for the research and design of intelligent compaction control system of vibratory road roller.2. On the basis of analyzing the function and requirement of intelligent compaction control system of vibratory road roller, the general design planning is presented based on CANbus and special purpose PLC. The hardware lectotype and design of the intelligent control system are accoplished.3. On the basis of test in the laboratory and on site, technique improvement planning of compaction degree measuring instrument is made an offer. Some key technology dificulties are solved about calibration of compaction degree measuring instrument during use and connection with the controller. Compaction degree on-line detection is realized.4. A kind of structure of fuzzy neural network for compaction control of road roller is put forward by connecting fuzzy system with artificial neural network in this paper, which consists of the fuzzification layer, fuzzy inference layer and clarification layer and is used. Self-adjusting of fuzzy neural network parameters are settled by learning algorithms of compensated fuzzy neural network. Fuzzy control...