Pump-Mounted Accelerometer for Low-Power Vibration Severity Measurement
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Solution Overview
Problem
Conventional vibration sensors for measuring vibration severity on rotating equipment are often expensive, complex, and require significant computational resources, leading to high power consumption and larger device sizes.
Innovation Solution
A low-cost sensor system that includes a single unit mechanically attached to rotating machinery, utilizing a low-cost accelerometer and a multi-purpose processor to compute velocity root mean square (RMS) vibration measurements locally, with the ability to wirelessly transmit these measurements to a user device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional vibration sensors are used to measure vibration severity, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses a low-cost accelerometer to capture vibration data and copies the functionality of expensive conventional vibration sensors by performing RMS calculations through software algorithms on a microprocessor, rather than using complex hardware-based velocity sensors
Solution Approach 2:
The patent replaces mechanical/physical hardware-based velocity sensing systems with an electronic accelerometer combined with digital signal processing, substituting complex mechanical RMS-to-DC conversion circuits with software-based calculations on a microprocessor
2Measurement precision
If conventional vibration sensors with hardware-based RMS calculation are used, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The patent replaces power-hungry hardware-based RMS-to-DC conversion circuits with software algorithms executed on a low-power microprocessor, significantly reducing power consumption while maintaining measurement precision
Solution Approach 2:
The system performs vibration measurements in periodic snapshots rather than continuous monitoring, with the microprocessor calculating RMS values from collected acceleration data and then entering low-power mode, reducing overall power consumption
3Measurement precision
If conventional vibration sensors are used, then measurement precision is improved, but device size increases
Solution Approach 1:
The patent uses a small accelerometer combined with software algorithms to copy the measurement capabilities of large conventional velocity sensors, achieving the same measurement precision in a much smaller form factor
Solution Approach 2:
The patent replaces bulky hardware-based velocity sensing and RMS conversion circuits with a compact accelerometer and microprocessor system, dramatically reducing device size while maintaining measurement accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides a cost-effective, compact, and power-efficient solution for obtaining standardized vibration measurements, enabling remote monitoring and reducing the need for complex hardware-based solutions.
Implementation Method 1
A sensor system that includes a single unit mechanically attaches to an outside surface of a piece of rotating machinery and detects vibration. The sensor system uses a low-cost accelerometer to generate raw sensor data
Data Source
AI summary
A device, system, and method are provided for providing vibration data for rotating machinery. A sensor device is provided as a one-piece unit that is mechanically mounted to a pump. The sensor includes a vibration sensor, a processor, a wireless communications interface for exchanging data with a user device, and an internal battery. The processor is configured to receive a measurement request from the user device via the wireless communications interface. In response, the processor is further configured to configure the vibration sensor, receive data samples for multiple axes from the vibration sensor, and calculate a component velocity root mean square (vRMS) value, from the data samples, for each of the multiple axes. The processor may combine the component vRMS values into a sample vRMS value, and send a final vRMS value, based on the sample vRMS value, to the user device via the wireless communication interface.