Resonance Enhanced Piezoelectric Sensor for Early Bearing Fault Detection
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Solution Overview
Problem
Current vibration sensors are ineffective in detecting transient, small-amplitude fault signals in heavy-load, slow-speed rotating equipment due to resonance reduction, limited frequency band, and interference from environmental noise, making it difficult to capture early fault signals.
Innovation Solution
A detector system incorporating a resonance enhanced piezoelectric sensor with a sensor trigger detection circuit, sensor signal selection circuit, sensor signal processing circuit, and programmable gain circuit, which enhances signal strength and reduces noise interference by amplifying fault signals within the 30 KHz to 40 KHz frequency range, allowing for timely detection of bearing faults.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional vibration sensors are used, then the sensor structure is simple and easy to manufacture, but the sensor cannot detect transient, small-amplitude fault signals in heavy-load, slow-speed rotating equipment
Solution Approach 1:
The patent employs a resonance-enhanced piezoelectric sensor that utilizes mechanical resonance to amplify transient fault signals. The sensor is designed to resonate at specific frequencies matching the fault signal frequencies, thereby enhancing the detection capability for small-amplitude transient signals in heavy-load, slow-speed rotating equipment while maintaining a relatively simple sensor structure.
Solution Approach 2:
The patent changes the operating parameters of the piezoelectric sensor by adjusting its resonance frequency to match the fault signal frequencies. This parameter adjustment allows the sensor to selectively amplify specific frequency ranges, improving fault detection capability without requiring complex sensor structures.
2Adaptability or versatility
If the frequency band of the vibration analyzer is widened to capture complex fault signal components, then the detection coverage is improved, but the hardware overhead and software overhead become very large
Solution Approach 1:
The patent extracts and amplifies only the relevant fault signal frequency components (30-40 KHz range) using resonance enhancement, rather than analyzing the entire frequency spectrum. This extraction approach allows the system to focus computational resources on detecting specific fault-related frequencies, reducing both hardware and software overhead while maintaining high detection coverage for bearing faults.
3Measurement precision
If conventional vibration sensors are used, then the device is simple to operate, but early fault signals are drowned by external noise in noisy environmental conditions
Solution Approach 1:
The patent uses resonance enhancement to amplify the amplitude of fault signals, making them stand out from background noise. By tuning the sensor to resonate at the characteristic frequencies of bearing faults, the system achieves a higher signal-to-noise ratio in noisy industrial environments without requiring complex signal processing algorithms.
Solution Approach 2:
The patent introduces an intermediary resonance-enhanced piezoelectric sensor that acts as a mediator between the fault source and the detection system. This intermediary amplifies the weak fault signals before they reach the detection electronics, improving measurement precision while keeping the overall system relatively simple.
4Reliability
If resonance-reduced type sensors are used, then periodic signals can be collected effectively, but transient fault signals with limited impact energy cannot be captured
Solution Approach 1:
The patent inverts the conventional approach by using resonance enhancement instead of resonance reduction. Rather than damping vibrations to eliminate resonance, the sensor is designed to resonate at specific frequencies, amplifying transient fault signals with limited impact energy. This inversion allows effective capture of transient signals while maintaining the ability to detect periodic signals.
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 effectively detects initial transient bearing fault signals with increased signal strength and reduced noise interference, enabling early fault detection and analysis, potentially predicting faults 3 to 6 months in advance.
Implementation Method 1
a piezoelectric ceramic sheet is clamped between the anode conductive rod and the cathode conductive rod
Data Source
AI summary
A detector capable of detecting bearing faults in advance is disclosed. The detector includes a microprocessor with an input terminal connected to a power supply and an output terminal connected to a detection information output device. A resonance enhanced piezoelectric sensor is provided. A sensor trigger detection circuit is electrically connected between the sensor and the microprocessor. An input terminal of the sensor trigger detection circuit is connected in parallel with a sensor signal selection circuit. The sensor signal selection circuit is connected in series with a sensor signal processing circuit. An output terminal of the sensor signal processing circuit is connected in series with a programmable gain circuit. The programmable gain circuit is connected to the microprocessor. The sensor trigger detection circuit, the sensor signal selection circuit, the sensor signal processing circuit, and the programmable gain circuit are respectively connected to the power supply.