Spectrum Analyzer

Lab 6: Spectrum Analyzer

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1. โครงสร้างภาพรวมของ Lab

Why? - ทำไมต้องเรียนรู้เรื่องนี้

• Frequency Analysis: วิเคราะห์องค์ประกอบความถี่ของสัญญาณ

• FFT Understanding: เข้าใจ Fast Fourier Transform

• Audio Applications: ใช้ใน equalizer, tuner, speech analysis

• Educational Demo: เห็นความแตกต่างของ spectrum ในแต่ละ waveform

What? - จะได้เรียนรู้อะไร

1. FFT Concept: Time domain → Frequency domain

2. FFT API: aic_fft_init(), aic_fft_calculate()

3. Bar Chart: แสดง spectrum แบบ bar graph พร้อม spacing

4. Gain Control: ปรับ gain ด้วย slider

5. Waveform Selection: เลือก waveform เพื่อดู spectrum ที่แตกต่าง

How? - จะทำอย่างไร

1. Initialize FFT กับ buffer size (power of 2)

2. สร้าง waveform (Sine, Square, Triangle, Sawtooth)

3. คำนวณ FFT spectrum

4. แสดงผลบน Bar chart พร้อม spacing ระหว่าง bar

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2. หลักการทำงานและ Flowchart

2.1 FFT Concept

┌─────────────────────────────────────────────────────────────┐
│                    FFT CONCEPT                              │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│   Time Domain (Waveform)       Frequency Domain (Spectrum)  │
│                                                             │
│      ╭──╮   ╭──╮                      ▓                     │
│     ╱    ╲ ╱    ╲                     ▓                     │
│   ╱       ╲       ╲     FFT          ▓▓                     │
│                        ─────►        ▓▓▓                    │
│   Input: N samples               ▓▓▓▓▓▓▓                    │
│   (e.g., 256)                  ─────────────                │
│                                0   f1  f2  fmax (Hz)        │
│                                                             │
│   Output: N/2 frequency bins                                │
│                                                             │
└─────────────────────────────────────────────────────────────┘

2.2 Frequency Bins

┌─────────────────────────────────────────────────────────────┐
│                   FREQUENCY BINS                            │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│   FFT Size: 256                                             │
│   Sample Rate: 44100 Hz                                     │
│   Bins: 128 (= 256/2)                                       │
│                                                             │
│   Bin Resolution = Sample Rate / FFT Size                   │
│                  = 44100 / 256 = 172.3 Hz                   │
│                                                             │
│   Bin 0:    0 - 172 Hz    (DC + low freq)                   │
│   Bin 1:  172 - 344 Hz                                      │
│   Bin 2:  344 - 517 Hz                                      │
│   ...                                                       │
│   Bin 127: 21756 - 22050 Hz (Nyquist)                       │
│                                                             │
│   Maximum frequency = Sample Rate / 2 = 22050 Hz            │
│                                                             │
└─────────────────────────────────────────────────────────────┘

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3. ฟังก์ชันสำคัญ

3.1 FFT API

Function	Description
aic_fft_init(fft_size)	Initialize FFT (size must be power of 2)
aic_fft_calculate(input, output)	Perform FFT
aic_fft_dominant_frequency()	Find strongest frequency

3.2 FFT Parameters

#define FFT_SIZE        256    // Must be power of 2
#define FFT_BINS        (FFT_SIZE / 2)  // = 128 output bins

int16_t fft_input[FFT_SIZE];    // Time domain
uint16_t fft_output[FFT_BINS];   // Frequency domain (magnitude)

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4. Code Example

4.1 Global Variables

#define FFT_SIZE        256
#define FFT_BINS        (FFT_SIZE / 2)
#define FFT_CHART_BINS  64      /* Displayed bins (decimated for better visibility) */
#define SAMPLE_RATE     48000

/* Ex6 dedicated variables (not shared with other examples) */
static lv_obj_t *ex6_fft_chart = NULL;
static lv_chart_series_t *ex6_fft_series = NULL;
static lv_obj_t *ex6_peak_label = NULL;
static lv_obj_t *ex6_gain_slider = NULL;
static lv_timer_t *ex6_timer = NULL;
static uint8_t ex6_fft_gain = 50;

static uint16_t fft_output[FFT_BINS];
static aic_wave_type_t current_wave_type = AIC_WAVE_SINE;
static uint32_t current_frequency = 1000;

4.2 Gain Slider Callback

static void ex6_fft_gain_cb(lv_event_t *e)
{
    if (lv_event_get_code(e) != LV_EVENT_VALUE_CHANGED) return;
    lv_obj_t *slider = lv_event_get_target(e);
    ex6_fft_gain = (uint8_t)lv_slider_get_value(slider);
}

static void ex6_wave_cb(lv_event_t *e)
{
    if (lv_event_get_code(e) != LV_EVENT_VALUE_CHANGED) return;
    lv_obj_t *dropdown = lv_event_get_target(e);
    current_wave_type = (aic_wave_type_t)lv_dropdown_get_selected(dropdown);
}

4.3 Timer Callback

static void ex6_timer_cb(lv_timer_t *timer)
{
    (void)timer;

    if (ex6_fft_chart == NULL || ex6_fft_series == NULL) return;

    /* Generate waveform for FFT */
    aic_wavegen_config_t config = {
        .type = current_wave_type,
        .frequency_hz = current_frequency,
        .sample_rate_hz = SAMPLE_RATE,
        .amplitude = 16000,
        .dc_offset = 0,
        .duty_percent = 50
    };

    int16_t fft_input[FFT_SIZE];
    aic_scope_generate_wave(fft_input, FFT_SIZE, &config);

    /* Calculate FFT */
    aic_fft_calculate(fft_input, fft_output);

    /* Find max value for normalization (skip DC bin) */
    uint16_t fft_max = 1;
    for (int i = 1; i < FFT_BINS; i++) {
        if (fft_output[i] > fft_max) fft_max = fft_output[i];
    }

    /* Find dominant frequency */
    uint32_t dominant = aic_fft_dominant_frequency(fft_output, FFT_BINS, SAMPLE_RATE);

    /* Update chart with normalized and gained values */
    for (int i = 0; i < FFT_CHART_BINS; i++) {
        int idx = i * (FFT_BINS / FFT_CHART_BINS);
        int32_t val = (fft_output[idx] * 100 * ex6_fft_gain) / (fft_max * 50);
        if (val > 100) val = 100;
        if (val < 0) val = 0;
        lv_chart_set_value_by_id(ex6_fft_chart, ex6_fft_series, i, val);
    }
    lv_chart_refresh(ex6_fft_chart);

    /* Update peak frequency label */
    if (ex6_peak_label) {
        lv_label_set_text_fmt(ex6_peak_label, "Peak: %u Hz", (unsigned int)dominant);
    }
}

4.4 Main Function

void week5_ex6_spectrum_analyzer(void)
{
    aic_scope_init();
    aic_fft_init(FFT_SIZE);

    /* Reset Ex6 variables */
    ex6_fft_chart = NULL;
    ex6_fft_series = NULL;
    ex6_peak_label = NULL;
    ex6_fft_gain = 50;

    /* Set up screen - dark theme */
    lv_obj_t *scr = lv_screen_active();
    lv_obj_set_style_bg_color(scr, lv_color_hex(0x0a0a1e), 0);

    /* Title */
    lv_obj_t *title = lv_label_create(scr);
    lv_label_set_text(title, "FFT Spectrum Analyzer");
    lv_obj_set_style_text_color(title, lv_color_hex(0xff6600), 0);
    lv_obj_align(title, LV_ALIGN_TOP_MID, 0, 10);

    /*=========================================================================
     * FFT BAR CHART - CRITICAL: Use pad_column for bar spacing
     *=========================================================================*/
    ex6_fft_chart = lv_chart_create(scr);
    lv_obj_set_size(ex6_fft_chart, 400, 180);
    lv_obj_align(ex6_fft_chart, LV_ALIGN_CENTER, 0, -10);
    lv_chart_set_type(ex6_fft_chart, LV_CHART_TYPE_BAR);
    lv_chart_set_point_count(ex6_fft_chart, FFT_CHART_BINS);
    lv_chart_set_range(ex6_fft_chart, LV_CHART_AXIS_PRIMARY_Y, 0, 100);

    /* Cyan theme for FFT */
    lv_obj_set_style_bg_color(ex6_fft_chart, lv_color_hex(0x001a1a), 0);
    lv_obj_set_style_line_color(ex6_fft_chart, lv_color_hex(0x003333), LV_PART_MAIN);
    lv_chart_set_div_line_count(ex6_fft_chart, 4, 5);
    lv_obj_set_style_border_width(ex6_fft_chart, 1, 0);
    lv_obj_set_style_border_color(ex6_fft_chart, lv_color_hex(0x006666), 0);

    /* CRITICAL: Add spacing between bars */
    lv_obj_set_style_pad_column(ex6_fft_chart, 2, 0);

    /* Add series - CYAN color */
    ex6_fft_series = lv_chart_add_series(ex6_fft_chart,
                          lv_color_hex(0x00ffff), LV_CHART_AXIS_PRIMARY_Y);

    /* Initialize all bars to 0 */
    for (int i = 0; i < FFT_CHART_BINS; i++) {
        lv_chart_set_value_by_id(ex6_fft_chart, ex6_fft_series, i, 0);
    }
    lv_chart_refresh(ex6_fft_chart);

    /*=========================================================================
     * Controls
     *=========================================================================*/
    /* Frequency scale labels */
    lv_obj_t *freq_0 = lv_label_create(scr);
    lv_label_set_text(freq_0, "0 Hz");
    lv_obj_set_style_text_color(freq_0, lv_color_hex(0x888888), 0);
    lv_obj_align_to(freq_0, ex6_fft_chart, LV_ALIGN_OUT_BOTTOM_LEFT, 5, 5);

    lv_obj_t *freq_max = lv_label_create(scr);
    lv_label_set_text_fmt(freq_max, "%u Hz", (unsigned int)(SAMPLE_RATE / 2));
    lv_obj_set_style_text_color(freq_max, lv_color_hex(0x888888), 0);
    lv_obj_align_to(freq_max, ex6_fft_chart, LV_ALIGN_OUT_BOTTOM_RIGHT, -5, 5);

    /* Wave type dropdown */
    lv_obj_t *wave_dd = lv_dropdown_create(scr);
    lv_dropdown_set_options(wave_dd, "Square\nSine\nTriangle\nSawtooth");
    lv_dropdown_set_selected(wave_dd, 1);
    lv_obj_align(wave_dd, LV_ALIGN_TOP_LEFT, 10, 35);
    lv_obj_add_event_cb(wave_dd, ex6_wave_cb, LV_EVENT_VALUE_CHANGED, NULL);

    /* Gain slider */
    lv_obj_t *gain_lbl = lv_label_create(scr);
    lv_label_set_text(gain_lbl, "Gain:");
    lv_obj_set_style_text_color(gain_lbl, lv_color_hex(0x00ffff), 0);
    lv_obj_align(gain_lbl, LV_ALIGN_BOTTOM_LEFT, 10, -50);

    ex6_gain_slider = lv_slider_create(scr);
    lv_obj_set_size(ex6_gain_slider, 140, 20);
    lv_slider_set_range(ex6_gain_slider, 10, 100);
    lv_slider_set_value(ex6_gain_slider, 50, LV_ANIM_OFF);
    lv_obj_align(ex6_gain_slider, LV_ALIGN_BOTTOM_LEFT, 60, -50);
    lv_obj_add_event_cb(ex6_gain_slider, ex6_fft_gain_cb, LV_EVENT_VALUE_CHANGED, NULL);

    /* Peak frequency label */
    ex6_peak_label = lv_label_create(scr);
    lv_label_set_text(ex6_peak_label, "Peak: -- Hz");
    lv_obj_set_style_text_color(ex6_peak_label, lv_color_hex(0xffff00), 0);
    lv_obj_set_style_text_font(ex6_peak_label, &lv_font_montserrat_16, 0);
    lv_obj_align(ex6_peak_label, LV_ALIGN_TOP_RIGHT, -20, 40);

    current_wave_type = AIC_WAVE_SINE;
    current_frequency = 1000;

    /* Footer */
    aic_create_footer(scr);

    /* Timer for updates (100ms) */
    ex6_timer = lv_timer_create(ex6_timer_cb, 100, NULL);
}

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5. องค์ความรู้และเทคนิค

5.1 CRITICAL: Bar Chart Spacing

/*=========================================================================
 * IMPORTANT: Without pad_column, bars will appear as solid block!
 *=========================================================================*/

/* WRONG: Bars merge into solid block */
ex6_fft_chart = lv_chart_create(scr);
lv_chart_set_type(ex6_fft_chart, LV_CHART_TYPE_BAR);
/* Missing pad_column = solid fill */

/* CORRECT: Individual bars with spacing */
ex6_fft_chart = lv_chart_create(scr);
lv_chart_set_type(ex6_fft_chart, LV_CHART_TYPE_BAR);
lv_obj_set_style_pad_column(ex6_fft_chart, 2, 0);  /* 2px spacing */

5.2 Dedicated Variables Pattern

/*=========================================================================
 * Use DEDICATED variables for each example
 * Avoid sharing static variables between examples
 *=========================================================================*/

/* BAD: Shared variable may conflict with other examples */
static lv_obj_t *main_chart = NULL;  /* Used by multiple examples */

/* GOOD: Dedicated variable for this example only */
static lv_obj_t *ex6_fft_chart = NULL;  /* Only used in Ex6 */

5.3 FFT Size Selection

/* FFT Size affects:
 * - Frequency resolution: Higher size = better resolution
 * - Processing time: Higher size = more computation
 * - Latency: Higher size = more samples needed
 *
 * Common sizes:
 * 128:  Low resolution, fast (speech)
 * 256:  Good balance
 * 512:  Higher resolution
 * 1024: High resolution, slow (music)
 */

5.4 Decimation for Display

/*=========================================================================
 * Decimate FFT bins for better bar visibility
 * FFT_BINS = 128 (too many for display)
 * FFT_CHART_BINS = 64 (better visibility)
 *=========================================================================*/

#define FFT_CHART_BINS  64

for (int i = 0; i < FFT_CHART_BINS; i++) {
    /* Sample every 2nd bin */
    int idx = i * (FFT_BINS / FFT_CHART_BINS);
    int32_t val = fft_output[idx];
    lv_chart_set_value_by_id(chart, series, i, val);
}

5.5 Gain Control

/* Gain slider allows user to adjust display sensitivity */
static uint8_t fft_gain = 50;  /* Default 50% */

/* Apply gain in timer callback */
int32_t val = (fft_output[idx] * 100 * fft_gain) / (fft_max * 50);
if (val > 100) val = 100;  /* Clamp to max */

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6. แบบฝึกหัด

Exercise 1: Note Detection

ตรวจจับโน้ตดนตรี (A4=440Hz, C5=523Hz, etc.)

Exercise 2: Frequency Band Display

แสดงแยก bands: Sub-bass, Bass, Low-mid, Mid, High-mid, High

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7. References

• FFT Explained

• ARM CMSIS-DSP FFT

• Window Functions

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Previous Lab: Lab 5: Oscilloscope UI Next Lab: Lab 7: Spectrum Analyzer in Action