Computational Sciences Center, Federal University of Rio Grande-FURG, Rio Grande, RS 96230-000, Brazil.
South Rio Grande do Sul Federal Institute-IFSUL, Pelotas, RS 96015-360, Brazil.
Sensors (Basel). 2019 Mar 12;19(5):1254. doi: 10.3390/s19051254.
Fruit flies (Diptera: Tephritidae) cause losses to world fruit growing. For a fast and effective control of the pest, it is necessary to identify the species and their populations. Thus, we developed an infrared optoelectronic sensor using phototransistors to capture the signal of the partial occlusion of the infrared light caused by the beating of the fly wings. Laboratory experiments were conducted using the sensor to capture the wing beat signal of and . The captured signals were used to obtain the characteristics of the flies' wing beats frequency and for a production of a dataset made available as one of the results of this work. For the passage detection, we developed the algorithm of detection of events of passage (PEDA) that uses the root mean square (RMS) value of a sliding window applied to the signal compared to a threshold value. We developed the algorithm of detection of events of passage (CAEC) that uses the techniques of autocorrelation and Fourier transform for the extraction of the characteristics of the wings' beat signal. The results demonstrate that it is possible to use the sensor for the development of an intelligent trap with detection and classification in real time for and using the wing beat frequency obtained by the developed sensor.
实蝇（双翅目：瘿蚊科）对世界水果生产造成损失。为了快速有效地控制这种害虫，有必要识别其物种及其种群。因此，我们开发了一种使用光电晶体管的红外光电传感器，以捕捉由苍蝇翅膀拍打引起的红外光部分遮挡的信号。使用该传感器在实验室中进行了实验，以捕获 和 的翅膀拍打信号。捕获的信号用于获得苍蝇翅膀拍打频率的特征，并生成了数据集，这是本工作的结果之一。对于通道检测，我们开发了事件通过检测算法（PEDA），该算法使用应用于信号的滑动窗口的均方根（RMS）值与阈值进行比较。我们开发了事件通过检测算法（CAEC），该算法使用自相关和傅里叶变换技术来提取翅膀拍打信号的特征。结果表明，使用该传感器通过开发的传感器获得的翅膀拍打频率，可以为 和 开发具有实时检测和分类功能的智能陷阱。
