Active Vibratory Noise Control Using Phase Lag Address Shifting
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Solution Overview
Problem
Existing active vibratory noise control systems face challenges in efficiently canceling noise at rapid vehicle accelerations due to high processing loads and inadequate signal transfer characteristics modeling, leading to increased costs and reduced noise control capabilities.
Innovation Solution
An active vibratory noise control apparatus that generates reference signals using waveform data storage and corrective data storage to reduce processing requirements, eliminating the need for FIR filters and convolutional calculations, allowing for effective noise cancellation with an inexpensive microcomputer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If FIR filter with convolutional calculations is used to model signal transfer characteristics, then noise control capability is improved, but processing load increases and device cost increases
Solution Approach 1:
The patent extracts only the essential phase characteristic information from the complex signal transfer characteristics by using corrective values (phase lag angles) instead of full FIR filter convolutional calculations. This allows the system to model the critical phase relationships between reference wave and error signal without requiring computationally intensive FIR filter operations, thereby reducing processing load while maintaining noise control capability.
Solution Approach 2:
The patent changes the representation of signal transfer characteristics from time-domain convolutional parameters (FIR filter coefficients) to frequency-domain phase parameters (corrective values representing phase lag angles). This parameter transformation enables the system to capture the essential phase relationships needed for adaptive notch filter operation with significantly reduced computational complexity, as phase angles can be processed with simple trigonometric functions rather than convolutional sums.
2Reliability
If FIR filter with convolutional calculations is used to model signal transfer characteristics, then noise control capability is improved, but device cost increases
Solution Approach 1:
The patent extracts only the essential phase characteristic information from the complex signal transfer characteristics by using corrective values (phase lag angles) instead of full FIR filter convolutional calculations. This allows the system to model the critical phase relationships between reference wave and error signal without requiring computationally intensive FIR filter operations, thereby reducing processing load while maintaining noise control capability.
Solution Approach 2:
The patent replaces the complex mechanical computation system (FIR filter convolutional calculations requiring high-performance DSP) with a simplified mathematical approach using phase angle parameters and trigonometric functions. This substitution enables the use of lower-cost microcomputers while achieving the same noise control objectives, as the simplified mathematics can be implemented with standard microprocessor instructions rather than requiring specialized DSP hardware.
3Reliability
If sampling frequency and number of FIR filter taps are increased to cancel noise at rapid accelerations, then noise control capability is improved, but processing load increases
Solution Approach 1:
The patent changes the representation of signal transfer characteristics from time-domain convolutional parameters (FIR filter coefficients) to frequency-domain phase parameters (corrective values representing phase lag angles). This parameter transformation enables the system to capture the essential phase relationships needed for adaptive notch filter operation with significantly reduced computational complexity, as phase angles can be processed with simple trigonometric functions rather than convolutional sums.
Solution Approach 2:
The patent applies partial action by focusing computational resources only on calculating the phase angle corrective values and applying them through simple address shifting in the waveform storage, rather than performing complete convolutional calculations. This selective computation approach provides sufficient noise control at rapid accelerations without the excessive processing load that would result from full FIR filter implementation.
4Reliability
If adaptive notch filters with corrected reference signals are used, then noise control capability is improved, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing the corrective values (phase lag angles) in a lookup table associated with the waveform data storage. During operation, the system simply retrieves the appropriate corrective value based on the reference wave frequency and applies it through address shifting, rather than performing complex real-time calculations. This preliminary preparation significantly reduces the computational complexity during actual noise cancellation operations.
Solution Approach 2:
The patent introduces corrective values as an intermediary element that mediates between the reference wave signal and the adaptive notch filter. These corrective values encapsulate the phase characteristic information and enable the system to adjust the reference signal phase without requiring direct complex manipulation of the signal itself. This intermediary approach simplifies the overall system architecture by separating the phase correction function from the main signal processing path.
Data Source
AI summary
A cosine wave over one period is stored as waveform data in a memory, and address shift values based on a phase lag in transfer characteristics from a speaker to a microphone are stored in a memory. An address shift value is read from the memory by referring to the frequency, and waveform data are read from the memory at addresses that are produced by shifting the addresses from which the reference cosine wave signal and the reference sine wave signal are read, by the address shift value. The read waveform data are used as a first reference signal and a second reference signal, which are applied to adaptive notch filters, to suppress vibratory noise.