Toyota jidosha kabushiki kaisha (20240257584). VEHICLE DIAGNOSTIC SYSTEM simplified abstract

VEHICLE DIAGNOSTIC SYSTEM

Organization Name

toyota jidosha kabushiki kaisha

Inventor(s)

Hideaki Bunazawa of Nagoya-shi (JP)

Shintaro Mukogawa of Nagoya-shi (JP)

Rikako Zenibana of Toyota-shi (JP)

VEHICLE DIAGNOSTIC SYSTEM - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240257584 titled 'VEHICLE DIAGNOSTIC SYSTEM

Simplified Explanation

The patent application describes a vehicle diagnostic system that uses a learned model to analyze sound data recorded from vehicles to detect anomalies and determine the type of anomaly that has occurred.

Key Features and Innovation

• Storage device stores data of a learned model and probability distribution data obtained by generating pieces of data using sound data recorded from vehicles with identified anomalies.
• Processing circuitry executes a loss calculation process to match sample data with probability distributions of anomalies and outputs a diagnosis result indicating the type of anomaly that has occurred in the vehicle.

Potential Applications

This technology can be used in vehicle diagnostic systems to accurately detect and diagnose various types of anomalies in vehicles, leading to improved maintenance and repair processes.

Problems Solved

This technology addresses the challenge of accurately identifying and diagnosing anomalies in vehicles by using advanced data analysis techniques.

Benefits

• Improved accuracy in diagnosing vehicle anomalies.
• Enhanced maintenance and repair processes for vehicles.
• Increased efficiency in identifying and addressing issues in vehicles.

Commercial Applications

• Automotive industry: Implementing this technology in vehicle diagnostic systems can improve the overall performance and reliability of vehicles, leading to increased customer satisfaction.
• Fleet management companies: Using this technology can help fleet managers better maintain and manage their vehicles, reducing downtime and maintenance costs.

Prior Art

Readers can explore prior research on vehicle diagnostic systems, anomaly detection, and machine learning models in the automotive industry to understand the evolution of this technology.

Frequently Updated Research

Researchers are constantly working on improving machine learning models for anomaly detection in vehicles, as well as developing more efficient diagnostic processes for automotive systems.

Questions about Vehicle Diagnostic Systems

How does this technology improve vehicle maintenance processes?

This technology enhances vehicle maintenance processes by accurately detecting and diagnosing anomalies in vehicles, allowing for timely repairs and maintenance to be conducted.

What are the potential implications of using this technology in the automotive industry?

Implementing this technology in the automotive industry can lead to more reliable and efficient vehicles, ultimately improving customer satisfaction and reducing maintenance costs.

Original Abstract Submitted

in a vehicle diagnostic system, a storage device stores data of a learned model and probability distribution data obtained by generating pieces of generated data by a learned model using pieces of sound data recorded using vehicles with identified types of anomalies and by obtaining, for each of the types of anomalies, a probability distribution of a loss variable. processing circuitry is configured to execute a loss calculation process that generates the pieces of the generated data using pieces of diagnostic sound data and obtains data of a probability distribution of a loss variable in the pieces of the generated data as sample data and a diagnostic process that determines which probability distribution of an anomaly the sample data matches and outputs a diagnosis result indicating that a type of anomaly corresponding to the probability distribution determined to match the sample data has occurred in the target vehicle.