SO SÁNH MÔ HÌNH CHUỖI FOURIER MỞ RỘNG VÀ MẠNG NƠ-RON NHÂN TẠO LIÊN KẾT CHỨC NĂNG CHO HỆ THỐNG KIỂM SOÁT TIẾNG ỒN CHỦ ĐỘNG PHI TUYẾN

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Tác giả: Đình Công Lê

Ngôn ngữ: vie

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Thông tin xuất bản: Tạp chí Khoa học và Công nghệ - Đại học Thái Nguyên, 2023

Mô tả vật lý: tr.29 - 36

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ID: 336983

Thêm vào giỏ Liên kết toàn văn

Đặc điểm của tính phi tuyến trong hệ thống kiểm soát tiếng ồn chủ động ANC (active noise control) là không giống nhau. Do đó, để tăng hiệu quả cho việc giảm tiếng ồn, chúng ta cần phải hiểu được loại của tính phi tuyến trong hệ thống ANC và lựa chọn được mô hình phù hợp. Bài báo này trình bày một so sánh, đánh giá giữa chuỗi Fourier mở rộng EMF (Even Mirror Fourier) và Mạng nơ-ron nhân tạo liên kết chức năng FLANN (Functional links artificial neural networks) cho hệ thống ANC phi tuyến. Bằng cách phân tích cụ thể các ảnh hưởng phi tuyến tồn tại trong đường dẫn sơ cấp (primary path), đường dẫn thứ cấp (secondary path) và nguồn tiếng ồn trong hệ thống ANC, nhiều loại tính phi tuyến, chẳng hạn như phi tuyến có nhớ (memory nonlinearity), phi tuyến không nhớ (memory-less nonlinearity) và tính phi tuyến hỗn loạn (chaotic) đã được thảo luận. Hơn nữa, khả năng mô hình phi tuyến của hàm mở rộng EMF và FLANN cho các loại phi tuyến trong hệ thống ANC đã được phân tích. Các nguyên nhân cũng đã được chỉ ra. Nhiều mô phỏng tính toán trong các kịch bản phi tuyến khác nhau đã được tiến hành để chứng minh cho những phân tích, đánh giá các hệ thống ANC dựa trên mô hình EMF và FLANN.The behavior of nonlinearity in the active noise control (ANC) system is not the same. Therefore, in order to increase the efficiency of noise reduction, we need to understand the type of nonlinearity in the ANC system and choose the appropriate model. This paper presents a comparison and evaluation between the even mirror Fourier series (EMF) and the functional links artificial neural networks (FLANN) for the nonlinear ANC system. By analyzing the nonlinear influences that exist in the primary path, the secondary path, and the noise source in the active noise control system, various types of nonlinearity, such as memory nonlinearity, memory-less nonlinearity, and chaotic nonlinearity has been discussed. Furthermore, the modeling capabilities of the expansion functions based on the EMF and FLANN for the types of nonlinearities have been analyzed. The causes for such behavior have also been pointed out. Many computational simulations in different nonlinear scenarios have been carried out to demonstrate the analysis and evaluation of ANC systems based on the EMF and FLANN models.

1. Đọc trực tuyến

1. Đọc trực tuyến

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