Based On The The Hht Drosophila Wings Song Feature Extraction And Classification Study

Insect's sound is the important media that can connect with outside environment in their life activities, which contains rich biological significance. Fruit fly is a kind of insect that has more serious harm for agricultural product, mainly damages vegetables, stem and leaves of various plants. Fruit fly's sound can reflect species-specificity, especially for some allied species, outer morphological characteristics are extremely similar, using characteristics of their sound can distinguish them. Also fruit fly's sound can be used to trap drosophila pests and experimental study for scientific workers. Therefore, the research of fruit fly's sound has great practical value.For the study of fruit fly's sound, most researchers analyzed the courtship song of drosophila and most analyses focused on the time domain of sound. The paper uses fruit fly's wing vibration sound as research object, proposes that uses Hilbert-Huang Transform (HHT), a new method of time-frequency localization analysis, to analyze time-frequency characteristics of wing vibration sound of fruit fly of two different strains in the same species. Then, it uses BP neural network to classify two strains of fruit fly's wing vibration sound. The method of the paper can provide scientific basis for further researches of fruit fly's sound and other insects'sound. The study of paper mainly includes following aspects:(1) The paper simply summarizes the relationship of human life and insects, insects'sound mechanism, type and function of the sound, and significance of sound research, mainly introduces the fruit fly's sound of this paper, analyzes harms of fruit fly to various fruits and vegetables, and describes the current state of fruit fly's sound research at home and abroad.(2) The paper deeply studies the fundamental principles of Hilbert-Huang Transform, clarifies the mathematic definitions of Hilbert transform, instantaneous frequency and intrinsic mode function, gives the specific steps and flow chart of empirical mode decomposition, analyzes the Hilbert spectrum and marginal spectrum, and illustrates the entire process of the Hilbert-Huang transform in more detail with examples of simulation signal and actual signal. In addition, the paper introduces application of the method in biomedical, geophysics and other fields, which fully explains the advantages of the method in signal processing.(3) The paper proposes that applies Hilbert-Huang transform in feature analysis and extraction of fruit fly's wing vibration sound. Because amplitude spectrum energy of each intrinsic mode function is different after EMD, the paper extracts ratios of each intrinsic mode function and signal total energy of two stains of fruit fly's sound. Because the energy distribution in Hilbert spectrum of fruit fly's wing vibration sound is different, the paper extracts the relative energy of HH spectrum and time-frequency entropy. Because the amplitude distribution of marginal spectrum in different frequency band is different, the paper extracts the amplitude characteristics of marginal spectrum of fruit fly's wing vibration sound.(4) The paper uses BP neural network to classify two strains of fruit fly's wing vibration sound. Firstly, it briefly introduces development process of artificial neural network, and analyzes the basic principle and parameter selection of BP neural network in detail. Then, the paper takes features extracted by Hilbert-Huang transform as input vector of BP neural network, classifies two strains of fruit fly's wing vibration sound, and the recognition result can reach over 86%, which explains the feasibility and effectiveness of the method.