Built to order

IoT-Based Underground Cable Fault Detection

An ESP32-based unit that locates underground cable faults by measuring line resistance, displays the phase and fault distance on an LCD, and pushes alerts to a cloud dashboard — a classic high-volume EEE search, rebuilt modern while rivals still sell stale Arduino+GSM kits.

Electronics / E&TCIoT & EmbeddedWeb Development ESP32IoTEmbedded SystemsCloud DatabaseWeb DashboardRelay ControlVoltage SensorLCD DisplayHybrid
Illustrative render of the IoT-Based Underground Cable Fault Detection prototype.
More project photos (3)

The problem

When an underground power cable faults, utilities today dig up entire road stretches hunting for the break — expensive, slow, and disruptive. This project pinpoints the fault from the surface: an ESP32-based unit injects a test signal into the cable, measures the resulting line resistance, and computes the fault distance in kilometers using the cable's resistance-per-km constant. The phase and distance show on an LCD and push to a cloud dashboard with alerts. Underground cable fault detection is a classic high-volume EEE student search — three sellers already monetize it with thin WooCommerce pages and stale Arduino+GSM designs. This is the modern ESP32 + cloud rebuild that outranks them.

SYSTEM FLOW

5 components 5 connections

Live flow
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actuatorTest Relay

Injects the low-voltage test signal into the suspect cable.

Follow the working sequence

How it works

  1. The cable is modeled as a resistor ladder; each kilometer of cable contributes a known resistance.
  2. The ESP32 injects a low-voltage test signal through a relay-switched circuit into the suspect cable.
  3. An ADC measures the loop resistance; the firmware divides by the calibrated ohm-per-km constant to compute fault distance.
  4. The faulted phase is identified by testing each phase in sequence; results display on the LCD instantly.
  5. Readings are pushed to the cloud dashboard and an SMS/push alert fires with phase + distance, so the repair crew digs at one spot, not the whole road.

Project features

Features:

  • Fault distance calculation from line-resistance measurement (Murray/Varley loop principle, simplified for demo)
  • Three-phase cable support — identifies which phase faulted (R/Y/B)
  • 16x2 LCD showing faulted phase + distance in kilometers
  • Cloud dashboard (ThingSpeak/Blynk) with fault history and location log
  • SMS/push alert on fault detection with phase and distance
  • Simulated fault switches — create faults at known distances to demo and calibrate
  • Relay-based cable switching for safe test-signal injection
  • Calibration mode: set the cable's ohm-per-km constant for accurate readings

What is included

What's included:

  • Complete ESP32 firmware with full source code
  • Circuit diagram and PCB-ready wiring layout
  • Calibration procedure for the ohm-per-km constant
  • Project report PDF (synopsis, fault-location theory, design, testing, results)
  • Presentation PPT for review/demo day
  • Viva Q&A sheet covering cable faults, Murray loop, and IoT architecture
  • Demo script: injecting faults at known distances and verifying readings

Advantages

  • Fault distance calculated from line-resistance measurement (Murray/Varley loop principle), with three-phase cable support identifying the faulted phase (R/Y/B).
  • 16x2 LCD shows the faulted phase and distance in kilometers at the unit itself.
  • Cloud dashboard (ThingSpeak/Blynk) with fault history and location log, plus SMS/push alerts carrying phase and distance.
  • Simulated fault switches let you create faults at known distances to demo and calibrate; ohm-per-km calibration mode keeps readings accurate.
  • Relay-based cable switching enables safe test-signal injection during detection.

Disadvantages

  • The demo uses a resistor-ladder cable model; real-field deployment needs high-voltage isolation and utility-grade equipment (out of scope).
  • Distance accuracy depends on correct ohm-per-km calibration and stable temperature.
  • Detects short-circuit/low-resistance faults; high-impedance arcing faults need advanced TDR methods (discussed in the report).
  • Cloud alerts need Wi-Fi at the unit's location.

Limitations & prerequisites

  • Demo uses a resistor-ladder cable model; real-field deployment needs high-voltage isolation and utility-grade equipment (out of scope)
  • Distance accuracy depends on correct ohm-per-km calibration and stable temperature
  • Detects short-circuit/low-resistance faults; high-impedance arcing faults need advanced TDR methods (discussed in the report)
  • Cloud alerts need WiFi at the unit's location
  • This is a built-to-order project — delivery time depends on component availability
Components & software requirements
  • ESP32 microcontroller
  • Resistor ladder cable-simulation board (or real cable sample)
  • 16x2 LCD display (I2C)
  • Relay module for test-signal switching
  • Voltage/current sensing circuitry
  • Push buttons for simulated fault injection at set distances
  • Power supply unit, enclosure, connecting terminals
  • ThingSpeak/Blynk cloud dashboard
Download free synopsis (PDF)

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"Underground Cable Fault Detection Using IoT", IJARESM (2022)

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