Vehicle Noise Localization Using Acoustic and Vibration Sensing
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Solution Overview
Problem
Existing on-board diagnostic systems fail to account for noise and vibration produced by degraded, damaged, or defective mechanical components without electrical sensors, making it difficult to locate these components within a vehicle.
Innovation Solution
A system utilizing a plurality of vehicle sensors, including microphones and vibration sensors, in conjunction with a controller programmed to perform measurements and apply machine learning or analytical methods to determine the location of defective parts based on noise and vibration patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional OBD systems are used to monitor vehicle systems, then electrical components with sensors can be diagnosed, but mechanical components without electrical sensors cannot be monitored or diagnosed
Solution Approach 1:
The system uses microphones and vibration sensors to detect both electrical and mechanical components, making the diagnostic system universal. The controller processes signals from these sensors to identify issues in any vehicle component, regardless of whether it has electrical sensors, thereby achieving multi-functionality in diagnostic capabilities
Solution Approach 2:
The patent replaces traditional mechanical diagnostic methods with acoustic and vibrational sensing. By using microphones to capture noise signatures and vibration sensors to detect mechanical vibrations, the system substitutes direct mechanical inspection with field-based detection, enabling remote and non-contact diagnostics
2Measurement precision
If multiple vibration sensors are used to locate defective parts, then location accuracy improves, but system complexity and cost increase
Solution Approach 1:
The system divides the vehicle into multiple monitoring zones, each covered by specific vibration sensors. By segmenting the diagnostic coverage area and assigning sensors to specific zones, the system achieves comprehensive location accuracy without requiring sensors throughout the entire vehicle, thus managing complexity
Solution Approach 2:
The controller acts as an intermediary that processes signals from multiple vibration sensors and algorithms that analyze vibration patterns. This intermediary layer interprets complex multi-sensor data to determine defective part locations, simplifying the overall system architecture while maintaining high measurement precision
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
Accurately identifies the location of defective parts within a vehicle by analyzing noise and vibration patterns, enhancing diagnostic capabilities beyond traditional OBD systems.
Implementation Method 1
The plurality of vehicle sensors includes at least three vibration sensors. Each of the at least three vibration sensors are affixed to a different location in the vehicle.
Implementation Method 2
The plurality of vehicle sensors includes at least three microphones. Each of the at least three microphones is affixed to a different location in the vehicle.
Data Source
AI summary
A system for noise localization for a vehicle includes a plurality of vehicle sensors. The plurality of vehicle sensors includes at least one of a microphone, a vibration sensor, a vehicle road speed sensor, and a vehicle motor speed sensor. The system also includes a controller in electrical communication with the plurality of vehicle sensors. The controller is programmed to perform a plurality of measurements of a noise produced by a defective part of the vehicle using the plurality of vehicle sensors. The controller is further programmed to determine a location of the defective part within the vehicle based at least in part on the plurality of measurements using at least one of a machine learning based method and an analytical method. The controller is further programmed to identify the defective part of the vehicle based at least in part on the location of the defective part within the vehicle.