Real-time noise spectrum analyzer system hardware and software design and implementation

1. Project Overview

1.1 Introduction

With the development of industrial production, transportation, urban construction, the increase in population density, and the increase in household facilities (audio, air conditioning, television, etc.), environmental noise has become increasingly serious, and it has become a major public hazard that pollutes the human social environment. Therefore, the monitoring of environmental noise has become a problem that people pay close attention to. The real-time noise spectrum analyzer is an essential device for measuring and analyzing noise signals. It is a common tool for professional noise monitoring and audio signal research and application, and is widely used.

Traditional analog audio spectrum analyzers have obvious disadvantages. They are complex in hardware implementation, can only measure the amplitude of the frequency, lack phase information, are large in size, inconvenient to carry, and cannot perform real-time measurements in complex noise sites. Therefore, they cannot meet the requirements of modern environmental noise measurement. Modern spectrum analyzers based on fast Fourier transform (FFT) decompose the measured signal into discrete frequency components through Fourier operation to achieve the same results as traditional spectrum analyzers. This new type of spectrum analyzer uses a digital method to directly sample the input signal through an analog/digital converter (ADC), and then obtains a spectrum distribution diagram after FFT processing to achieve spectrum analysis of audio.

1.2 Project Background/Motivation for Topic Selection

The AVR EVK1105 development kit used in this project is based on the AT32UC3A0512 microcontroller, which has a built-in hardware multiplier, supports DSP instruction set, 64K SRAM, and has powerful fixed-point computing capabilities, so it can fully meet the data computing requirements in digital signal processing; and the AVR EVK1105 development kit is equipped with a TLV320AIC23B low-power stereo audio codec chip, which supports both MIC and LINE IN input modes, and has programmable adjustable gain for both input and output. It integrates an analog-to-digital conversion (ADC) component that can provide 16-bit sampling in the frequency range of 8K to 96K, and can achieve higher data sampling accuracy; the QVGA (320*240) full-color LCD display can well display the waveform and spectrum of the noise signal and has a good user interface.

Therefore, this project makes full use of the software and hardware resources provided by the AVR EVK1105 development kit, and uses digital signal processing methods to implement a real-time noise spectrum analyzer based on Wi-Fi control. The real-time noise spectrum analyzer uses a digital method to directly obtain sampling data from the analog/digital converter (ADC), uses the FIR digital filtering algorithm and the FFT algorithm to obtain the spectrum distribution diagram of the real-time noise signal, and calculates the relevant parameters of the noise at the same time, realizing the measurement and analysis of real-time noise. The noise spectrum analyzer can obtain good linearity and high resolution, and with the addition of a Wi-Fi wireless control module, it can complete the noise measurement tasks in complex noise fields and unmanned laboratory environments. The device is small in size, simple to operate, and easy to carry and use.

2. Demand Analysis

2.1 Functional requirements

1) Realize the parameter measurement function of the input noise signal:

a) Display the real-time waveform of the noise signal;

b) Display the octave and 1/3 octave spectrum of real-time noise signal;

c) Measure relevant parameters of real-time noise signal:

The sound pressure level Lp of the noise signal based on A, C, and Z weighting;

‚Maximum and minimum sound pressure level measurement (A, C weighting), peak sound pressure level (C weighting), equivalent continuous sound pressure level Leq (A, C weighting);

ƒAccumulated percentage of noise signal level Ln (A, C weighted);

2) Based on Wi-Fi wireless network connection, remote equipment control can be realized, and noise measurement can be achieved in unmanned environment;

3) SD card realizes data storage and playback functions;

4) Calibration: Sound calibration, using a sound calibrator.

2.2 Performance requirements

(1) Measurement range: 30~120dB;

(2) Octave bandwidth: 31.5~16KHz;

(3) 1/3 octave bandwidth: 20Hz~20KHz;

(4) Frequency resolution: 20Hz;

3. Solution Design

3.1 System Function Implementation Principle

This system mainly uses the audio data input interface or microphone on the AVR EVK1105 development board to obtain noise signal data, and uses the TVL3230AIC23B low-power stereo audio codec chip on the development board to implement 16-bit A/D conversion, realize the conversion of analog signals to digital signals, and use the DSP instruction set of AT32UC3A0512 to implement FIR digital filtering and FFT algorithm to obtain the spectrum data of the audio signal, calculate the relevant parameters of the audio signal, and display the waveform, spectrum and related parameter values ​​of the noise signal on the full-color LCD screen on the development board in real time. The collected data can also be stored in the SD card through the SD card slot on the development board for subsequent data playback and analysis.

The system also supports remote control of equipment based on Wi-Fi wireless network interface, such as measurement parameter setting, measurement start, stop and other commands, to achieve noise parameter measurement in unmanned environment, thus completing the monitoring and analysis functions of noise signals.

The system hardware structure block diagram is shown in Figure 1:

Figure 1 System hardware structure diagram

3.2 Hardware platform selection and resource allocation

1. Hardware platform:

The system uses the AVR EVK1105 development board, which is an evaluation kit based on the AT32UC3A0512.

EVK1105 development board hardware resources usage: