ANC Headphone USB Auto-Calibration for Faster Gain Tuning
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Solution Overview
Problem
Existing active noise cancelling headphones require manual calibration, which is time-consuming and inefficient, limiting their ability to effectively reduce noise across all frequency bands and hindering mass production efficiency.
Innovation Solution
A headphone system with an auto-calibration method that uses a first gain amplifier, active noise cancelling module, measure circuit, calibration control circuit, and USB driving circuit to progressively adjust gain values based on noise-reducing numerical values measured during calibration, eliminating the need for manual adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration method is used to adjust gain value of microphone, then calibration can be performed, but calibration time is very long and production efficiency is low
Solution Approach 1:
The calibration system performs self-calibration automatically without manual intervention. The microprocessor controls the variable resistor to adjust microphone gain automatically, measures the noise reduction effect through the measuring circuit, and iteratively optimizes the calibration parameters based on feedback from the noise reduction measurement, thereby achieving self-service calibration that eliminates time-consuming manual operations
Solution Approach 2:
The system implements a feedback mechanism where the measuring circuit continuously monitors the noise reduction effect during calibration. The measured noise reduction values are fed back to the microprocessor, which adjusts the gain parameters accordingly. This closed-loop feedback process enables automatic optimization of calibration settings while reducing calibration time through iterative improvement based on real-time performance measurement
2Object-affected harmful factors
If passive noise cancelling materials are used with thick structure, then noise isolation is improved, but headphone size and weight increase significantly
Solution Approach 1:
The patent replaces passive mechanical noise isolation materials with an active electronic noise cancelling system. Instead of relying on thick physical barriers to block noise, the system uses microphones to capture ambient noise, processes the noise signals through the microprocessor, and generates anti-phase noise cancellation signals through amplifiers and DACs. This substitution of mechanical isolation with electronic active noise control achieves effective noise reduction without increasing headphone weight or size
Solution Approach 2:
The system dynamically adjusts noise cancellation parameters including gain values of microphones and amplifiers, filter frequencies, and signal processing characteristics. By changing these electrical and signal processing parameters rather than physical dimensions, the system achieves adaptive noise isolation performance without compromising the lightweight design of the headphone
3Device complexity
If passive noise cancelling materials are used, then structural simplicity is maintained, but noise cancellation ability in low frequency band is insufficient
Solution Approach 1:
The patent replaces passive noise cancellation materials with an active electronic system that uses microphones, digital signal processing, and anti-phase signal generation. This electronic substitution enables effective cancellation of low frequency noise through phase inversion and destructive interference, a capability that passive materials cannot achieve at low frequencies without excessive thickness
Solution Approach 2:
The system dynamically processes noise signals in real-time through digital signal processing. The microprocessor continuously analyzes captured noise signals, adjusts gain parameters, applies frequency-dependent filtering, and generates adaptive anti-phase cancellation signals. This dynamic processing enables effective low frequency noise cancellation by continuously optimizing the cancellation signal based on actual ambient noise conditions
4Manufacturing precision
If gain value is adjusted manually and burned in OTP memory, then calibration can be completed, but calibration process requires multiple iterations and consumes excessive time
Solution Approach 1:
The calibration system performs self-calibration automatically without requiring external manual intervention. The microprocessor controls the variable resistor to adjust microphone gain automatically, the measuring circuit evaluates the noise reduction effect, and the system iteratively optimizes parameters based on measured feedback. This self-service calibration process eliminates time-consuming manual adjustments while maintaining high calibration precision through automated iterative optimization
Solution Approach 2:
The system performs preliminary measurements and adjustments during the calibration process to determine optimal gain values before finalizing the calibration. The measuring circuit conducts initial noise reduction measurements, the microprocessor analyzes the results, and adjusts parameters in advance before burning the final calibrated values into memory. This preliminary action approach enables the system to achieve precise calibration faster by pre-determining optimal parameters through automated measurement and adjustment
Data Source
AI summary
A headphone with active noise cancelling and auto-calibration method thereof is disclosed. The headphone includes a first gain-amplifier, an active noise cancelling module, a speaker, a measurement circuit, a calibration control circuit and USB driving circuit. Auto-calibration of the headphone is by use of a USB interface in the instant disclosure, so as to significantly reduce calibration time and then improve production efficiency.