Power Steering Anomaly Detection via FFT Signal Analysis
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Solution Overview
Problem
Existing power steering systems, particularly steer-by-wire systems, often mask abnormal vibrations, making it difficult for drivers to detect mechanical issues, and existing evaluation methods fail to pinpoint the location or cause of mechanical anomalies, especially during normal vehicle operation.
Innovation Solution
A system that passively and actively monitors the power steering system using processors to analyze excitation and response signals through FFT, determining frequency response, profile characteristics, and coherence to initiate a diagnostic procedure, identifying mechanical anomalies by comparing baseline and estimated waveforms, and using a mass-spring-damper model to determine the location of anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If software filtering is used to control steer-by-wire system, then abnormal vibrations are filtered and torque feedback is smoothed, but abnormal vibrations are masked and mechanical anomalies are not detected by driver
Solution Approach 1:
The patent introduces an intermediary monitoring system that independently analyzes vibration signals from the steering rack without relying on driver perception. The system uses sensors to capture raw vibration data, processes it through FFT analysis to identify abnormal frequency patterns, and generates alerts when mechanical anomalies are detected, thus bridging the gap between smooth software filtering and reliable anomaly detection
Solution Approach 2:
The patent replaces the mechanical detection method (driver feeling vibrations through the steering wheel) with an electronic sensing and signal processing system. The system uses accelerometers or vibration sensors coupled with digital signal processing (FFT algorithms) to detect and analyze vibration patterns, substituting human sensory detection with automated electronic monitoring that can identify anomalies even when they are filtered from the driver's experience
2Reliability
If existing evaluation systems are used to monitor steer-by-wire systems, then system operation is monitored, but specific location or cause of mechanical issues cannot be pinpointed
Solution Approach 1:
The patent segments the steering system into multiple monitoring zones by placing vibration sensors at different locations (steering rack, steering motor, connection points). Each sensor captures vibration characteristics specific to its location, allowing the system to identify which segment is experiencing mechanical anomalies by analyzing the spatial distribution and patterns of detected vibrations
Solution Approach 2:
The patent utilizes mechanical vibration analysis as the core diagnostic mechanism. By capturing vibration signals from different components and analyzing their frequency content through FFT, the system can identify characteristic vibration signatures that indicate specific mechanical issues (loose fasteners, worn bearings, misaligned components) and locate them based on which sensor detects the anomaly first or with greatest intensity
3Productivity
If passive monitoring is not implemented, then system can only be evaluated during active diagnostic procedures, but mechanical anomalies cannot be detected during normal vehicle operation
Solution Approach 1:
The patent implements continuous passive monitoring that operates throughout normal vehicle operation without requiring active diagnostic procedures. The vibration sensors continuously capture steering rack movements and vibrations during regular driving, and the signal processing system continuously analyzes these signals for anomalies, ensuring uninterrupted monitoring coverage rather than periodic or on-demand checking
Solution Approach 2:
The system performs self-diagnosis by automatically analyzing its own operational data without requiring external intervention or active testing. The monitoring system uses the vehicle's normal operational vibrations as test signals, processing them through FFT analysis to identify anomalies inherent in the system's own operation, eliminating the need for separate diagnostic procedures
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
Effectively detects and diagnoses mechanical anomalies in power steering systems, enabling precise identification of issues during normal operation, even in autonomous vehicles without a steering wheel, improving the ability to maintain system integrity and safety.
Implementation Method 1
estimate the frequency response between the excitation signal and the response signal based on a fast Fourier transform (FFT) algorithm
Implementation Method 2
determine a coherence between the excitation signal and the response signal, and compare the coherence with a threshold coherence value
Data Source
AI summary
A system and method for passively and actively monitoring and determining the location of at least one mechanical anomaly for a power steering system of a vehicle is disclosed. The system includes one or more processors and a memory coupled to the processors. The memory stores a baseline waveform and data comprising program code that, when executed by the one or more processors, causes the system to receive at least one excitation signal and at least one response signal. The power steering system creates the response signal in response to receiving the excitation signal. In response to receiving the excitation signal and the response signal, the system is caused to estimate the frequency response between the excitation signal and the response signal based on a fast Fourier transform (FFT) algorithm. The frequency response is represented by an estimated waveform.