VibraLink

What it does

This project involves the design and development of a compact wireless vibration monitoring and diagnostic system using ADXL345 and ESP8266. Real-time triaxial acceleration data is acquired, transmitted, and visualised via LabVIEW, efficient remote analysis.

Your inspiration

The idea for this project originated from a growing need to monitor vibrations in rotating machines to prevent unexpected failures. We observed that existing systems were often wired, expensive, or lacked portability. Inspired by advancements in wireless sensors and low-cost microcontrollers, we aimed to develop a compact, wireless vibration monitoring and diagnostic system. The solution idea came from combining engineering knowledge with real-world needs — offering a cost-effective, 3D-printed device using an ADXL345 sensor and ESP8266 module, capable of sending vibration data wirelessly and visualising it through LabVIEW for analysis.

How it works

Our device is a compact, wireless vibration monitoring system designed to detect machine health by tracking vibration levels. Inside the 3D-printed case, we placed a small sensor called the ADXL345, which can measure movements up to 16 times the force of gravity. This sensor detects tiny vibrations in all three directions (X, Y, and Z). The sensor sends this vibration data to a small computer called the ESP8266 microcontroller. The ESP8266 processes and transmits the data wirelessly using Wi-Fi. We programmed it to send vibration signals in packets, which are then received and displayed in real-time using LabVIEW, a software that shows the vibration levels on a graph. We carefully arranged and mounted the hardware inside the case to ensure accurate readings and proper airflow. The system is powered by a rechargeable lithium-ion battery, making it portable and convenient for field testing and long-term use on machines without needing a constant power source.

Design process

The project began with identifying the need for a low-cost, portable, and wireless vibration monitoring system. Initially, we brainstormed possible configurations, focusing on key components: the ADXL345 vibration sensor, ESP8266 microcontroller, and a lithium-ion battery. Using SolidWorks, we developed early CAD models for the casing. The first design lacked airflow and had weak mounting options, so we redesigned it with snap-fit features, improved support, and ventilation slots. After selecting PETG for strength and heat resistance, we 3D-printed our first prototype. Internally, we tested hardware positioning for balance and signal clarity. On the software side, we used Arduino IDE to configure I2C communication and optimize data packet sizes for wireless transmission. The initial LabVIEW interface was laggy, prompting adjustments to UDP buffer size, ADC calibration, and spectrum display. Design D was finalised after evaluation using a Pugh matrix. We also conducted structural analysis to ensure the casing could endure 16 g vibrations. Functional testing validated sensor accuracy, especially along the Z-axis. Final improvements included better PCB support, secure headers, and testing under real vibration scenarios to ensure reliability.

How it is different

Our design stands out due to its compact integration of low-cost components into a fully wireless and portable vibration monitoring system. Unlike typical wired or bulky industrial systems, our prototype uses the ADXL345 accelerometer and ESP8266 microcontroller in a lightweight PETG 3D-printed enclosure. What makes it unique is the tailored internal layout for component stability, a rechargeable battery system for off-grid usage, and real-time spectrum analysis via LabVIEW, all in one compact unit. We optimised the data flow using I2C communication and UDP protocol, reducing lag and increasing reliability. The snap-fit casing features ventilation for heat management and sensor isolation to reduce noise interference. Our solution bridges the gap between affordability and performance, ideal for educational, research, or small-scale industrial monitoring applications where commercial systems are too expensive or over-engineered for basic diagnostic needs.

Future plans

The next steps involve refining the prototype for long-term deployment by improving PCB design, enhancing casing durability, and integrating onboard data storage. We plan to expand functionality with multi-axis analysis and machine learning for fault detection. Field testing in real industrial environments will help validate performance. Eventually, we aim to develop a user-friendly mobile or web interface for remote monitoring and make the system scalable for multiple sensors, offering a low-cost, reliable solution for predictive maintenance.

Awards