Milling cutter baffle body vertical milling head housing parallel reed roller lower body displacement sensor profiling instrument structure schematic diagram using the profiling instrument has the following problems: a. The contoured workpiece profile busbar requirements are not changed much. The ribs of the wheel profile acquisition signal are not the processed ribs, but the adjacent rib busbar profile values, which affect the machining accuracy. b. The mechanical contact of the roller is greatly affected by the on-site milling of metal shavings, and there is often a jittery instability. When using the X and Y axes of the double milling head to work simultaneously, an indexing axis A is used. Since the metal chips that are milled naturally flow down with the coolant, no matter what direction the Z axis rotates, there is always a metal chip downstream. Waiting for profiling to the unformed profile, in this case, the operator is required to clean the surface to be processed continuously. On the one hand, the labor intensity is large, and more importantly, the beating of the roller affects the machining accuracy. .
In order to solve the above technical problems of using the contoured wheel to simulate the shape and improve the machining accuracy of the part, we propose to use the method of laser pre-scanning to measure the profile of the part to realize the contouring. According to the thrust chamber cooling slot processing scheme, the laser acquisition system is equipped with a high-precision laser linear sensor, equipped with a high-performance computer, and a multi-function standard acquisition card to form a data sampling hardware system. When the laser linear sensor is sampled, it is installed on the milling cutter (no milling cutter), and the spindle is fixed without rotation. The sampling program is designed according to the theoretical mathematical model of the thrust chamber cooling channel, and the Z, X (Y) axis linear displacement and A-axis indexing sampling motion are performed by the numerical control system. Under the synchronous control of the numerical control system and the computer automatic sampling software, the sample points on the outer wall of the nozzle are scanned and sampled, and the limited sample points are input into the computer through the acquisition card, and then output to the numerical control machine for numerical control milling.
Conclusion Based on the study of BA and other network evolution models, this paper proposes a new network evolution model for the characteristics of real complex networks. The model has the following characteristics: the number of newly introduced nodes and networks in each time step obeys logarithmic growth, which is similar to the growth characteristics of many networks (such as the Internet and the World Wide Web) in real life, and can better describe the actual complexity. The way the network grows. On the basis of retaining the original BA network priority connection on the connection mode, a random connection method is introduced, which shows some random factors in the network generation process, which can better reflect the actual network connection process.
The simulation results show that the degree distribution of the network is more uniform in the new network generated. For the scale-free network, robustness and fragility are one of its fundamental characteristics. Contrary to the exponential or Poisson distribution. Random network. Since the new network is somewhere in between, the new network model becomes more flexible when considering more network features. However, in the actual complex network, the choice of the local world is complex and diverse. In addition to the randomly selected cases, evolutionary characteristics such as gradual attenuation, adaptive competition and distance priority can be reflected as some special local worlds. Therefore, the new network has yet to be further studied.
(Finish)
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