Electronic control hydraulic impactor based on pressure feedback
The impact energy of the traditional hydraulic impactor can be regulated manually between the second and the third grade, and its impact frequency can not be adjusted independently. Also, they have to stop working for adjustment. In order to alter this situation, a new hydraulic impactor DBS500, which controlled by micro-electronic system, has been designed and its functions are showed as following: The impact energy can reach 500 joules and its impact frequency also realizes regulation from 0 to 8Hz steplessly. It can estimate the work object's nature by piston's rebound behavior. It can self-regulate the impact energy and frequency according to the object's nature, so that can improve the working efficiency and adapt the power of the loader.
Dynamics of One-Way Hydraulic Impact System with Two Piston Stop Tools
The mathematical model of the one-way hydraulic positive-displacement system with two piston stop tools includes the design variables of the system and its interaction with rock mass, namely, dry friction in the impact facility body–piston couple, pressure losses in the hydraulic system branches and piston velocity recovery factor. The dynamic similarity criteria, which are dimensionless analogs of the listed characteristics, are determined. The numerical calculation is performed, the influence of the similarity criteria on the dynamics and integral characteristics of the test system is analyzed, and the main behavioral patterns are revealed. It is found that these criteria influence the shape of the domains of the single impact travel and back run, two-impact and multi-impact limit cycles. It is possible to reduce the difference between the system characteristics in the impact travel and back run by means of changing the piston coordinates such that the valve stations are changed.
Adaptive neuro-fuzzy control of systems with time delay
The authors present an adaptive fuzzy logic controller, which learns about the dynamic of the system under control from an online neural network (NN) identification algorithm. The identification is based on the estimation of parameters of a First-Order-Plus-Dead-Time (FOPDT) model. The outputs of the NN are three parameters: gain, apparent time delay and the dominant time constant. By combining this algorithm with a fuzzy logic controller with rotating rule-table, an adaptive controller is obtained which, with very little a priori knowledge, can compensate systems with time delay. The simplicity and feasibility of the scheme for time delay control provides a new approach for a variety of control applications. Simulation results are included to demonstrate the adaptive property of the proposed scheme.