The piecewise logistic map (PLM) is an improved version of logistic map, which is specifically designed for cryptographic application. However, the probability density distribution of PLM is not uniform. To overcome this shortage, a parameter-coupled piecewise logistic map (PCPLM) is presented. Using the PCPLM as a basic unit, we construct a four-dimensional chaotic model, which has even probability density distribution. The four-dimensional chaotic model based on PCPLMs also has a parallel structure, which is beneficial to enhancing the running efficiency. Finally, a novel pseudorandom number generator (PRNG) is presented based on this four-dimensional chaotic model. The security analysis and simulation tests on the proposed PRNG are performed. The results both confirm that the proposed PRNG is secure and efficient. Therefore, it can be used as a candidate for data security.
Aiming at the problems of poor timeliness and poor monitoring accuracy of domestic forklift working condition monitoring, a multi-sensor online monitoring method for forklift condition is proposed. Analyze the relevant factors that affect the status of the forklift truck, optimize the structure of the forklift truck condition monitoring platform, design the main control algorithm for forklift truck condition monitoring, and obtain the loading status and monitoring parameters of the forklift in the warehouse in real time. Status online monitoring. In order to verify the monitoring performance of this method, a comparative experiment is designed. The results show that the method in this paper can effectively shorten the monitoring delay and improve the detection accuracy, which is of great significance for the realization of network, intelligence and modularization of electric forklifts.
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