Magnetic Sensor System-Level Error Detection via Signal Analysis
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Solution Overview
Problem
Magnetic sensors currently do not detect or signal system-level errors, such as wheel runout, air gap changes, or broken teeth, which are essential for maintaining accurate rotational data and preventing system failures.
Innovation Solution
A magnetic sensor system that detects system-level errors by analyzing signal characteristics of the magnetic field waveform, such as extrema and offset values, and provides an indication using a system error protocol, including specific signal levels or pulse widths, to an electronic control unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If magnetic sensor analyzes signal characteristics to detect system-level errors, then reliability is improved, but device complexity increases
Solution Approach 1:
The magnetic sensor performs preliminary analysis of signal characteristics (extrema, offset values, waveform patterns) during normal operation to detect system-level errors before they cause failures. This proactive error detection approach improves reliability by identifying issues like wheel runout, air gap changes, or broken teeth early, while the analysis is integrated into the existing sensor processing pipeline to minimize added complexity
Solution Approach 2:
The magnetic sensor is designed to perform multiple functions: it simultaneously measures rotational position/speed and analyzes signal characteristics for error detection. By making the sensor multi-functional, the system achieves improved reliability through error detection capability without requiring separate dedicated error detection devices, thus limiting the increase in device complexity
2Loss of information
If magnetic sensor provides error indication in output signal, then information completeness is improved, but signal processing complexity increases
Solution Approach 1:
The error indication is merged with the existing output signal that carries rotational information. The sensor combines normal operational data with error status indicators in a unified output protocol, allowing complete information transmission (both rotational data and error states) without requiring separate communication channels or significantly increasing signal processing complexity at the controller end
3Reliability
If magnetic sensor detects system-level errors, then system safety is improved, but manufacturing complexity increases
Solution Approach 1:
The error detection capability is achieved by analyzing existing signal parameters (extrema values, offset values, waveform characteristics) that are already present in the magnetic sensor's output. By utilizing changes in these existing parameters rather than requiring additional hardware components or complex manufacturing processes, the system achieves improved safety while minimizing increases in manufacturing complexity
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
Enables the detection and signaling of system-level errors, allowing for timely corrective actions and preventing failures by providing clear indications of issues like wheel runout, air gap changes, and broken teeth to the electronic control unit.
Implementation Method 1
A magnetic sensor may sense a magnetic field produced or distorted by a rotating magnet wheel
Data Source
AI summary
A magnetic sensor may include one or more sensor components to detect a system-level error, associated with a sensor system that includes the magnetic sensor, based on a set of signal characteristics of a waveform corresponding to a magnetic field present at the magnetic sensor. The one or more sensor components may provide an indication of the system-level error in an output signal.