摘要
随机共振是一种有效检测微弱信号的非线性方法,对它的研究和实现具有重要的工程应用价值。针对工业现场存在的背景噪声未知的高频微弱信号(不满足绝热近似理论条件)的随机共振检测问题,提出了基于参数补偿的自适应参数诱导随机共振方法,以系统输出信噪比作为适应度函数,将系统势垒与噪声强度大致相等时可产生最佳的随机共振效应作为知识,采用基于知识的粒子群优化算法来并行优化随机共振系统的参数。设计了基于DSP的自适应随机共振检测系统,实现了对信号的实时处理,并通过Modbus Rtu协议将检测结果实时显示在触摸屏上,从而实现微弱信号的检测。
In nonlinear system ,it is of great significance in engineering practice to achieve stochastic resonance ,which is a nonlinear method used for weak signal detection .In view of the high‐frequency weak signal with unknown background noise in industry field , the parameter‐induced adaptive stochastic resonance based on parameter compensation is proposed .The system parameters are opti‐mized by knowledge‐based particle swarm optimization in parallel ,which takes the output signal‐noise‐ratio of system as the fitness function and the property that stochastic resonance system produces the best resonance effect just when the intensity of noise approx‐imately equals the potential barrier as the knowledge .Finally the adaptive stochastic resonance system based on DSP is designed , which can process the signals in real time .And the system can display the detection results in the touch screens in real time ,reali‐zing the weak signal detection successfully and completely .
出处
《国外电子测量技术》
2016年第3期32-36,共5页
Foreign Electronic Measurement Technology
基金
陕西省重点科技创新团队(2013KCT-04)
陕西省自然科学基金(2015JM1039)项目资助
关键词
参数诱导随机共振
知识的粒子群算法
自适应参数优化
DSP
parameter-induced stochastic resonance
knowledge-based particle swarm optimization
the adaptive parame-ter optimization
DSP
