一类基于非侵入式家用电器监测系统的设计与实现
Design and Implementation of a Non Intrusive Household Appliance Monitoring System

本文研究提出了一类基于非侵入式家用电器监测系统的设计与实现，概述了非侵入式家用电器监测系统的六个模块，包含采集数据模块、预处理数据模块、GPRS数据传输模块，存储数据模块，云端算法识别模块，智能显示模块。分别对各个模块的设计和实现来分析，其中算法识别模块在遗传算法的基础之上进行了算法改进，采用了量子遗传算法并选择了交叉熵函数作为适应度函数来实现，使得非侵入式家庭电器识别系统的精确度更高，算法识别放在云端来实现，在计算速度上也会有很大的提高，不仅能够存储非常丰富的样本数据库，稳定性更高，并且适用范围也更广。
This paper studies and proposes the design and implementation of a non-invasive household appliance monitoring system, and summarizes six modules of the non-invasive household appliance monitoring system, including acquisition data module, preprocessing data module, GPRS transmission module, data storage module, cloud algorithm recognition module, and intelligent display module. The design and implementation of each module are analyzed respectively. The algorithm identification module is improved on the basis of the genetic algorithm. The quantum genetic algorithm is adopted and the cross entropy function is selected as the fitness function to achieve, it make the non-invasive home appliance identification system more accurate and, the algorithm recognition is implemented in the cloud, and the computing speed will also be greatly improved. It can not only store a very rich sample database, but also has higher stability and wider application scope.