POLARIS

Propeller Observation, Logging, Acquisition and Rotation Instrumentation Stand

Static thrust test rig developed by Céu Azul Aeronaves team for characterization of propellers used in SAE Brasil Aerodesign competition aircraft, on Advanced class.

---

Overview

POLARIS is a complete acquisition and analysis system for static propeller testing. It captures thrust, torque, and RPM in real time from a custom mechanical bench, performs traceable multi-point calibration, automatically extracts steady-state operating points from manual throttle sweeps, computes non-dimensional aerodynamic coefficients (C_T, C_P, C_Q, FOM), and generates publication-ready PDF reports with cross-reference to the UIUC Propeller Database.

The system was designed around three principles:

• Traceability — every measurement carries the calibration ID (SHA-1 hash) and full ambient metadata
• Repeatability — automatic detection of steady regimes, hysteresis tracking, and online anomaly detection
• Practicality — single-click setup, mobile remote monitor, and one-click PDF report generation

---

Table of Contents

• Features
• Hardware
• Installation
• Quick Start
• User Guide
  • 1. Calibration
  • 2. Data Collection
  • 3. Analysis
  • 4. Test Database
  • 5. Remote Monitor
• Technical Details
• Project Structure
• Troubleshooting
• Roadmap
• License

---

Features

Acquisition

• Real-time data streaming from Arduino via USB serial (115200 baud)
• Two HX711 load cells for thrust and torque measurement
• RPM via ESC signal wire using Pin Change Interrupt with debounce filtering
• Multi-point calibration with mandatory up/down sweep for hysteresis quantification
• Automatic tare before each test
• Configurable moving-average filter (1–200 samples)

Analysis

• Manual sweep extraction — automatically detects stable plateaus in a CSV from a manual throttle sweep
• Non-dimensional coefficients — C_T, C_P, C_Q, Figure of Merit (FOM)
• FFT spectral analysis — identifies 1×RPM (imbalance), BPF (blade-pass frequency) and harmonics
• UIUC database integration — automatic lookup and side-by-side comparison with reference data
• Online anomaly detector — warns about thrust drops, torque spikes, and RPM oscillations during the test

Outputs

• CSV with full metadata (propeller, motor, battery, ambient conditions, calibration ID, marked events)
• Parallel JSON file with structured metadata
• PDF report with cover page, calibration summary, sweep table, performance plots, and UIUC comparison
• SQLite database indexing all tests for filtering and multi-test comparison
• Mobile remote monitor — HTTP page accessible from any device on the same Wi-Fi

---

Hardware

Bill of Materials

Component	Model	Notes
Microcontroller	Arduino Nano	ATmega328P, 16 MHz
Thrust load cell	10 kg with HX711	DT=D3, SCK=D4
Torque load cell	5 kg with HX711	DT=D5, SCK=D6
RPM sensor	ESC yellow signal wire	D7 (PCINT23)
Motor	Any	14 poles = 7 pole pairs
ESC	Hobbywing Platinum V4	RPM signal output via yellow wire
Propeller	Any	Configurable in test metadata

Wiring Diagram

Arduino Nano               ESC                       Battery
─────────────              ─────                     ───────
   D2 ───────── (free)
   D3 ─── DT  ┐
   D4 ─── SCK ┤ HX711 #1 (thrust)
   D5 ─── DT  ┐
   D6 ─── SCK ┤ HX711 #2 (torque)
   D7 ────────────────── Yellow (RPM signal)
   GND ───────────────── Black (BEC GND)        ←── CRITICAL: shared ground
   5V ── (USB powered, NOT from BEC)
   USB ── PC
                          Red ── (BEC +5V, NOT connected to Arduino)
                          White ── Receiver throttle channel

⚠️ CRITICAL: The Arduino ground MUST be connected to the ESC ground (BEC black wire or battery negative terminal). Without a common ground, the RPM signal will be unstable and produce nonsensical readings. DO NOT connect the BEC red wire (+5V) to the Arduino — the Arduino is powered by USB.

Mechanical Setup

The bench uses an aluminum profile structure with a sliding carriage that pulls a horizontally mounted thrust load cell via a threaded rod. The motor mount is connected to a torque arm whose force is captured by the second load cell. The default torque arm length is 7 cm (configurable in config.py).

---

Installation

Prerequisites

• Python 3.10 or newer (tested on 3.10–3.13)
• Arduino IDE (1.8 or 2.x) for firmware upload

Software setup

# Clone the repository
git clone https://github.com/ceuazul/polaris.git
cd polaris

# Install Python dependencies
pip install pyserial numpy matplotlib pandas reportlab

Windows note: if you get ModuleNotFoundError: No module named 'serial.tools', you have a conflicting package. Fix with:

pip uninstall serial pyserial -y
pip install pyserial

Firmware upload

1. Open firmware_arduino/firmware_arduino.ino in the Arduino IDE
2. Select Board: Arduino Nano
3. Select Processor: ATmega328P (try "Old Bootloader" if upload fails)
4. Select the correct Port
5. Click Upload

You should see in the Serial Monitor (115200 baud) the line ID:THRUST_RIG_V2 confirming the firmware is running.

Optional: UIUC Propeller Database

For comparison with reference data, download files from the UIUC Propeller Database and place the *_static_*.txt files in the uiuc_data/ folder.

Run the application

python app.py

---

Quick Start

1. Calibrate thrust and torque cells (one-time setup)
        ↓
2. Connect the rig (Arduino → USB → PC)
        ↓
3. Tare (with motor stopped)
        ↓
4. Click "▶ New Test", fill metadata
        ↓
5. Run the throttle in steps (e.g., 30%, 50%, 70%, 90%, then back down)
        ↓
6. Stop, save CSV
        ↓
7. Go to Analysis tab → Detect plateaus → Generate PDF

---

User Guide

The application has four main tabs:

Tab	Purpose
📊 Coleta (Collection)	Real-time acquisition with live plots
⚖ Calibração (Calibration)	Multi-point load cell calibration
🔬 Análise (Analysis)	Sweep extraction, FFT, UIUC comparison, PDF
🗂 Ensaios (Tests)	SQLite database of all tests

1. Calibration

Calibration is mandatory before the first test and recommended periodically.

Procedure:

1. Open the Calibração tab
2. Select Empuxo (thrust) radio button
3. Click Tarar (zero) with no load on the cell
4. Place the first known weight (e.g., 500 g), enter the value, select subida (going up), click + Adicionar Ponto
5. Repeat with increasing weights until covering the expected range (typical: 0, 500, 1000, 2000, 3000, 5000, 7000 g)
6. Now do the down sweep: remove weights in reverse order, switching the direction selector to descida
7. Click 📊 CALCULAR REGRESSÃO
8. Repeat steps 2–7 selecting Torque instead
9. Click 💾 Salvar

Why up AND down? Mechanical structures exhibit hysteresis — the reading at 1000 g going up is not exactly the same as 1000 g coming down. The difference quantifies the irreducible measurement uncertainty of your bench. Quality criteria:

• R² ≥ 0.999 → Good
• Hysteresis < 5 g → Good
• R² < 0.99 or hysteresis > 20 g → Mechanical issues (loose screws, friction, misalignment) — fix before testing

Each calibration receives a SHA-1 ID hash that is permanently recorded in every CSV file produced afterward, ensuring full traceability.

2. Data Collection

Before connecting the battery:

1. Connect the Arduino to the PC via USB
2. Click Conectar in the Coleta tab; status should turn green
3. Click TARA with the motor mounted but not running

To start a test:

1. Click ▶ Novo Ensaio
2. Fill in the metadata dialog:
   • Propeller: pick a preset or enter manually
   • Motor: pick a preset — pole pairs default to 7
   • Battery: cells, capacity (mAh), initial voltage
   • Ambient conditions: temperature, pressure, humidity → click Calcular rho to compute air density (CIPM-2007 formula)
   • Operator and notes
3. Click OK — collection starts immediately

During the test:

• The plot shows thrust, torque, and RPM in three stacked panels
• Numeric indicators show filtered values plus derived quantities (P_mec, T/P, C_T, FOM)
• The "REGIME" label shows whether the signal is steady (green) or transient (orange)
• A configurable moving average smooths the live plot (does not affect saved data)
• Anomaly detector displays warnings if it detects sudden thrust drops, torque spikes, or RPM oscillations
• Click 🗑 Limpar Gráficos anytime to reset the plot view (raw data is preserved)
• Click ⚑ Marcar Evento to mark a timestamp with a label (e.g., "throttle 50%", "vibration started")

Manual sweep procedure:

For sweep analysis to work later, you need to hold each throttle level constant for at least 6 seconds before changing. A typical pattern:

0%  →  30% (8s)  →  50% (8s)  →  70% (8s)  →  90% (6s)  →
50% (8s)  →  30% (8s)  →  0%

Stopping and saving:

1. Click ⏹ Parar when done
2. Click 💾 Salvar CSV, choose location
3. The system saves three things:
   • ensaio_<name>_<timestamp>.csv — full time series with all derived values
   • ensaio_<name>_<timestamp>.json — structured metadata
   • The test is automatically indexed in the SQLite database

3. Analysis

In the Análise tab:

1. Click 📂 Carregar CSV and pick the test file
2. The full time series is plotted automatically

Sub-tabs:

Sweep (steady plateaus)

Automatically extracts stable operating points from a manual sweep.

• Adjust Janela (s) = window size for std-dev calculation (default 2.0s)
• Adjust Lim relativo = relative threshold (3% of local mean by default)
• Adjust Min dur (s) = minimum plateau duration to be counted (default 1.5s — increase to 4s for cleaner results)
• Choose Sinal-base = empuxo_g (thrust-based detection) or rpm (RPM-based, often cleaner)
• Click 🔍 Detectar patamares

The table fills with one row per detected plateau, showing mean ± std for thrust, torque, RPM, plus computed P_mec, T/P, C_T, C_P, FOM. Four small plots show the curves vs RPM.

Click 💾 Exportar tabela to save just the sweep results as CSV.

FFT / Spectrum

Spectral analysis of a chosen time segment.

• Set t inicial and Duração (recommend at least 5s in a steady region)
• Click 🔬 Calcular FFT

The plot shows magnitude vs frequency for thrust and torque. Vertical red lines mark expected peaks (1×RPM, BPF, harmonics) based on the average RPM in the segment and 2 propeller blades (configurable in code).

UIUC

Cross-reference with the UIUC Propeller Database.

• Adjust Tolerância (in) if your propeller diameter/pitch doesn't exactly match a database entry
• Click 🔎 Procurar hélice no UIUC

The system searches for a matching propeller (preferring APC, falling back to any manufacturer), parses the static-test file, and shows side-by-side C_T and C_P plots with deviation percentages in a table.

Note: UIUC data is mostly for APC propellers. For non-APC propellers like EOLO, deviations of 15–30% are normal due to geometric differences.

PDF report

Click 📋 Gerar Relatorio PDF to export everything as a multi-page PDF:

• Cover page with full configuration
• Calibration summary with quality assessment
• Sweep table with all extracted points
• Six performance plots (T, Q, P_mec, T/P, C_T, FOM vs RPM)
• UIUC comparison if loaded
• Operator notes

4. Test Database

The Ensaios tab shows all tests indexed in the SQLite database (config_local/ensaios.db).

• Filter by propeller or motor name
• Click headers to sort
• Select 2+ tests and click 📊 Comparar selecionados to overlay their curves on a chosen Y-axis

This is essential for comparing propellers, motors, or pre/post-modification configurations.

5. Remote Monitor

To monitor the test from a phone or tablet on the same Wi-Fi:

1. Check the Monitor remoto box in the top toolbar
2. The app shows a URL like http://192.168.0.15:8765/
3. Open this URL on the phone's browser

The remote view shows the four main numbers (thrust, torque, RPM, P_mec) in large fonts plus a steady-regime indicator, updating twice per second. Useful for keeping the operator at a safe distance from the spinning propeller.

---

Technical Details

RPM measurement

The Hobbywing Platinum ESC outputs one electrical commutation pulse per electrical revolution on the yellow wire. For a motor with N pole pairs, the conversion is:

RPM_mechanical = (pulses_per_second × 60) / pole_pairs

The Arduino uses Pin Change Interrupt (PCINT23 on D7) with a 400 µs software debounce to filter ESC switching noise.

Air density (CIPM-2007 formula)

ρ = (P_dry / R_dry × T) + (P_vapor / R_vapor × T)

where:
  P_vapor = RH × 611.2 × exp(17.62 × T / (243.12 + T))
  P_dry   = P_total - P_vapor
  R_dry   = 287.058 J/(kg·K)
  R_vapor = 461.495 J/(kg·K)
  T       in Kelvin

Typical accuracy: ±0.1%. Sufficient for aerodynamic coefficient calculations.

Non-dimensional coefficients (static, J = 0)

n = RPM / 60        [rev/s]
T = thrust          [N]
Q = torque          [N·m]
P_mec = 2π × n × Q  [W]

C_T = T / (ρ × n² × D⁴)
C_P = P_mec / (ρ × n³ × D⁵)
C_Q = Q / (ρ × n² × D⁵)
FOM = C_T^1.5 / (C_P × √2)         (Figure of Merit, ideal hover)

Note: FOM > 1 is physically impossible (Betz limit). If observed, indicates measurement error in either thrust (too high) or torque (too low).

Calibration model

Linear least-squares fit:

raw_count = A × weight + B
weight    = (raw_count - B) / A

Hysteresis is computed point-by-point as the difference between the predicted weight on the up vs down sweep.

Stable-plateau detection (offline)

1. For each sample, compute rolling std-dev in a window of size janela_s
2. Mark as stable where std < max(local_mean × limiar_rel, 5 g)
3. Group consecutive stable samples into plateaus
4. Discard plateaus shorter than min_dur_s
5. Trim 0.4s from each plateau edge to avoid transients
6. Compute mean and std of each channel inside the plateau

Anomaly detection (online)

Three heuristics with 3s cooldown:

1. Thrust drop: thrust falls > 15% over baseline (10s window) → possible blade damage
2. Torque spike: torque rises > 30% without proportional thrust increase → possible stall
3. RPM oscillation: RPM std/mean > 20% in last second → mechanical or ESC issue

---

Project Structure

polaris/
├── app.py                        # Application entry point
├── config.py                     # Constants and paths
├── core/
│   ├── calibration.py            # CalibrationModel + regression + hysteresis
│   ├── serial_reader.py          # Threaded serial reader
│   ├── derived.py                # P_mec, C_T, C_P, FOM, ρ_air
│   ├── stable_detector.py        # Online + offline plateau detector
│   ├── sweep_analyzer.py         # Manual sweep extraction
│   ├── anomaly.py                # Online anomaly detector
│   ├── database.py               # SQLite layer
│   ├── uiuc.py                   # UIUC parser + comparison
│   ├── fft_analysis.py           # FFT with Hann window
│   ├── remote_server.py          # HTTP server for mobile monitor
│   └── report.py                 # PDF generator
├── gui/
│   ├── dialogo_metadados.py      # Test setup dialog
│   ├── tab_coleta.py             # Collection tab
│   ├── tab_calibracao.py         # Calibration tab
│   ├── tab_analise.py            # Analysis tab
│   └── tab_ensaios.py            # Tests database tab
├── firmware_arduino/
│   └── firmware_arduino.ino      # Arduino firmware
├── uiuc_data/                    # ← place UIUC database files here
├── ensaios/                      # CSV outputs (auto-created)
├── relatorios/                   # PDF outputs (auto-created)
├── config_local/                 # calibration, profiles, SQLite DB (auto-created)
└── README.md

---

Troubleshooting

Symptom	Likely cause	Fix
ModuleNotFoundError: No module named 'serial.tools'	Conflicting serial package	pip uninstall serial pyserial -y && pip install pyserial
module 'serial' has no attribute 'Serial'	Same as above	Same fix
Arduino upload fails with "not in sync"	CH340 driver missing or USB cable is power-only	Install CH340 driver; try a different USB cable
RPM always 0	Yellow wire not connected or no common ground	Check D7 wiring; verify ground is shared between Arduino and ESC
RPM erratic / 100x too high	No common ground	Connect Arduino GND to ESC BEC ground (black wire)
RPM doubled or halved	Wrong pole pairs in metadata	SunnySky X4120 = 7 pairs; check motor specs
FOM > 1	Torque measured too low or thrust too high	Check torque arm coupling, recalibrate, verify arm length in config.py
Massive hysteresis (>50 g)	Mechanical issues	Tighten screws, check carriage friction, align thrust cell
Sweep detector finds spurious plateaus at start/end	Default min duration too short	Increase Min dur (s) to 4–5 s
App runs but plot is empty	No data flowing	Check serial monitor first to confirm Arduino is sending; click TARA after connecting

---

Roadmap

Planned for future versions:

• Voltage and current acquisition (INA226 or similar)
• Automated throttle sweep with safety interlocks
• Formal uncertainty propagation (GUM-compliant)
• Vibration measurement (accelerometer integration)
• Real-time efficiency mapping (T/P heatmap vs RPM/throttle)

---

License

MIT License — see LICENSE file for details.

---

Acknowledgments

• Céu Azul Aeronaves team (UFSC, Brasil) for the bench design and testing
• University of Illinois at Urbana-Champaign for the publicly available Propeller Database

---

POLARIS
Céu Azul Aeronaves · Advanced 2026 · Made by @higor0227 and @joaoheck