18558952. ACOUSTIC SIGNAL CONNECTION SYSTEM simplified abstract (Schlumberger Technology Corporation)
Contents
ACOUSTIC SIGNAL CONNECTION SYSTEM
Organization Name
Schlumberger Technology Corporation
Inventor(s)
Pontus Loviken of Clamart (FR)
James Matthews of Houston TX (US)
Yong Wee Lee of Singapore (SG)
Haw Keat Lim of Singapore (SG)
Josselin Kherroubi of Clamart (FR)
ACOUSTIC SIGNAL CONNECTION SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18558952 titled 'ACOUSTIC SIGNAL CONNECTION SYSTEM
Simplified Explanation: The patent application describes a method that involves capturing acoustic signals related to emissions from equipment and using a machine learning model to generate an output signal indicating the positional arrangement of two pieces of the equipment.
Key Features and Innovation:
- Acquiring acoustic signals from equipment emissions.
- Inputting the acoustic signals into a machine learning model.
- Generating an output signal indicating the positional arrangement of equipment pieces.
Potential Applications: This technology could be applied in various industries such as manufacturing, automotive, and aerospace for equipment monitoring and maintenance purposes.
Problems Solved: This technology helps in accurately determining the positional arrangement of equipment pieces based on acoustic signals, which can improve maintenance efficiency and reduce downtime.
Benefits:
- Enhanced equipment monitoring capabilities.
- Improved maintenance accuracy.
- Reduced downtime and maintenance costs.
Commercial Applications: The technology could be used in predictive maintenance systems for industrial equipment, leading to cost savings and increased operational efficiency.
Prior Art: Readers can explore prior research on machine learning applications in equipment maintenance and acoustic signal processing to understand the background of this technology.
Frequently Updated Research: Stay updated on advancements in machine learning models for equipment monitoring and maintenance to enhance the effectiveness of this technology.
Questions about Acoustic Signal Processing in Equipment Maintenance: 1. How does acoustic signal processing benefit equipment maintenance?
- Acoustic signal processing helps in detecting anomalies in equipment operation, enabling proactive maintenance actions to prevent breakdowns.
2. What are the challenges associated with implementing machine learning models for equipment monitoring?
- Challenges may include data quality issues, model complexity, and the need for continuous model training and optimization.
Original Abstract Submitted
A method can include acquiring acoustic signals responsive to emissions into equipment: and generating an output signal by inputting the acoustic signal into a machine learning model, where the output signal is indicative of a positional arrangement of two pieces of the equipment.
