论文部分内容阅读
人参栽培中常见的病害有立枯病、人参软腐病、黑斑病、红皮病等,虫害如蛴螨、蝼蛄、金针虫等,通过对病虫害进行激光光谱特征检测,实现病虫害的识别和防治。传统方法采用离散希尔伯特激光光谱特征检测方法,当病虫害的光谱特征受到杂波干扰时,检测识别概率不高。提出一种基于Hilbert-Huang时频谱分析的人参栽培病虫害的激光光谱特征检测方法。构建了人参栽培病虫害的激光光谱的信号模型,采用二阶格型陷波器对激光光谱信号波束进行降噪滤波,采用Hilbert-Huang时频谱分析方法,对降噪滤波输出的激光光谱信号进行谱分析和自适应波束形成,实现了光谱特征检测和识别。仿真结果表明,该方法具有较好的病虫害光谱特征分类识别性能,对病虫害的特征识别的波束形成聚焦性能较好,提高了准确检测识别概率,性能优越。
Common diseases in ginseng cultivation are blight, ginseng soft rot disease, black spot disease and erythroderma disease. Pests such as scabies, scabies and golden needleworms are detected by laser spectroscopy to realize the recognition of pests and diseases. Prevention and treatment. The traditional method uses the discrete Hilbert laser spectral feature detection method, when the spectral characteristics of pests and diseases are clutter interference, the detection and recognition probability is not high. A detection method of laser spectral characteristics of cultivated pests and diseases of ginseng based on Hilbert-Huang time-frequency analysis was proposed. The signal model of the laser spectrum of ginseng cultivated pests and diseases was constructed. The second-order lattice notch filter was used to filter the laser spectrum signal. The Hilbert-Huang time-frequency spectrum analysis method was used to analyze the spectrum of the laser spectrum signal Analysis and adaptive beamforming, to achieve spectral feature detection and identification. The simulation results show that this method has good performance of classification and recognition of spectral features of pests and diseases, better performance of beamforming focusing on feature recognition of pests and diseases, and improved detection accuracy and superior performance.