18045254. UNDERWATER MACHINERY PERFORMANCE ANALYSIS USING SURFACE SENSORS simplified abstract (International Business Machines Corporation)
Contents
- 1 UNDERWATER MACHINERY PERFORMANCE ANALYSIS USING SURFACE SENSORS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 UNDERWATER MACHINERY PERFORMANCE ANALYSIS USING SURFACE SENSORS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
UNDERWATER MACHINERY PERFORMANCE ANALYSIS USING SURFACE SENSORS
Organization Name
International Business Machines Corporation
Inventor(s)
Sudheesh S. Kairali of Kozhikode (IN)
Sarbajit K. Rakshit of Kolkata (IN)
UNDERWATER MACHINERY PERFORMANCE ANALYSIS USING SURFACE SENSORS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18045254 titled 'UNDERWATER MACHINERY PERFORMANCE ANALYSIS USING SURFACE SENSORS
Simplified Explanation
The patent application describes a system, method, and computer program product for audio-visual inspection of a liquid surface over machinery operating beneath it. The inspection involves analyzing surface wave movements, bubble formation patterns, bubble dimensions, and underwater acoustic information using a neural network to identify anomalies in machinery performance.
- Surface wave movements, bubble formation patterns, bubble dimensions, and underwater acoustic information are fed into a neural network for analysis.
- Anomalies in machinery performance are identified using the neural network based on the audio-visual inspection results.
Potential Applications
This technology could be applied in industries such as manufacturing, oil and gas, and underwater exploration for monitoring and detecting anomalies in machinery performance.
Problems Solved
1. Detecting anomalies in machinery performance without physical inspection. 2. Monitoring machinery operating under liquid surfaces in real-time.
Benefits
1. Early detection of machinery malfunctions. 2. Improved maintenance scheduling. 3. Enhanced safety measures in hazardous environments.
Potential Commercial Applications
Optimizing maintenance schedules in manufacturing plants using real-time anomaly detection technology.
Possible Prior Art
There may be prior art related to underwater inspection systems using neural networks for anomaly detection in machinery performance.
Unanswered Questions
How does this technology handle different types of liquids or environments where the machinery is operating?
The patent application does not specify how the system adapts to various liquid types or environmental conditions.
What is the accuracy rate of anomaly detection using this technology compared to traditional inspection methods?
The patent application does not provide information on the accuracy rate of anomaly detection using this technology.
Original Abstract Submitted
A system, method, and computer program product perform audio-visual inspection at a surface of a liquid over machinery that is operating under the surface. The audio-visual inspection includes each of feeding surface wave movements into a neural network, feeding bubble formation pattern into the neural network, feeding bubble dimensions into the neural network, and feeding underwater acoustic information to the neural network. The system, method, and computer program product further identify, using the neural network, a statistical anomaly from the audio-visual inspection indicating an anomaly of the performance of the machinery.
