Magnetic Revolution Counter Self-Detecting Error States
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Solution Overview
Problem
Existing magnetic revolution counters lack the ability to identify error states during operation, which can lead to faulty measurements and incorrect counting of revolutions, particularly in applications requiring reliable error monitoring and self-identification.
Innovation Solution
The implementation of a magnetic revolution counter with domain wall conductors made of GMR or TMR layer stacks, where magnetic 180° domain walls are introduced, pinned, or deleted in a controlled manner, and electrical contacts are used to form Wheatstone half bridges for multiplex read-out, allowing for continuous comparison of resistance patterns against stored target values to detect errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If magnetic revolution counters are used for non-contact and powerless counting of revolutions, then the device can be miniaturized and operated in a currentless manner, but the device lacks the ability to self-detect error states during operation
Solution Approach 1:
The revolution counter performs self-diagnosis by automatically comparing its own measurement signals against stored reference patterns. The evaluation electronics continuously monitor the sensor element's output signals and compare them with target value patterns stored in memory, enabling the device to self-detect errors without external intervention or additional complex hardware.
Solution Approach 2:
The system implements feedback by storing reference measurement patterns in memory and continuously comparing current measurement signals against these stored patterns. When deviations are detected, the system generates error signals that trigger error states, creating a closed-loop feedback mechanism for error detection that enhances reliability without significantly increasing device complexity.
2Measurement precision
If domain walls are transported in open spirals or closed loops to determine revolutions, then the counting function is achieved, but error states such as deleted or nucleated domain walls cannot be identified
Solution Approach 1:
Reference measurement patterns are pre-stored in memory before the actual counting operation begins. These target value patterns represent the expected measurement signals for each revolution state under normal conditions. By having these reference patterns prepared in advance, the system can immediately compare current measurements against them to detect any deviations caused by domain wall errors, thereby ensuring measurement precision while enabling error identification.
Solution Approach 2:
The system creates copies of expected measurement patterns and stores them in memory as reference patterns. Instead of requiring complex real-time calculations or additional sensors, the system simply compares the actual sensor output signals against these pre-copied reference patterns. This copying approach allows for accurate revolution counting and reliable error detection without increasing device complexity.
3Temperature
If multiple sensor elements are interconnected to form Wheatstone bridges, then the influence of temperature on the magnetoresistive signal is suppressed, but the device still cannot identify error states during operation
Solution Approach 1:
The Wheatstone bridge circuit configuration serves multiple functions simultaneously: it provides temperature compensation by suppressing thermal influences on the magnetoresistive signal, and it generates measurement signals that can be compared against stored reference patterns for error detection. This multi-functional use of the same hardware components achieves both temperature stability and error identification capability without requiring separate dedicated systems for each function.
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 identification of electric and magnetic error states, allowing for the determination of correct revolution numbers even in error conditions, without the need for external means or re-initialization, and supports continued operation by monitoring errors during counting.
Implementation Method 1
The sensor element at least partially has a layer composition comprising at least one hard magnetic layer and at least one soft magnetic layer... This differing orientation of the magnetizations results in a difference in the electrical resistance in different conductor sections, which can be read out by way of the GMR or TMR effect.
Implementation Method 2
This differing orientation of the magnetizations results in a difference in the electrical resistance in different conductor sections, which can be read out by way of the GMR or TMR effect.
Implementation Method 3
Within the soft magnetic layer, two differently magnetized regions are separated from one another by a magnetic domain wall (DW). During operation of the sensor system, a change in position of the outer magnetic field, for example due to rotation, in the sensor element results in a powerless movement of the magnetic domain walls that exist in the sensor element.
Data Source
AI summary
A magnetic revolution counter for the self-identification of error states includes magnetic domain wall conductors which are composed of open spirals or closed, multiply-wound loops, formed by a GMR layer stack or a sort magnetic layer of locally present TMR layer stacks and in which the magnetic 180° domain walls can be introduced and located, wherein a predefinable bijective magnetization pattern of domain walls and/or domain wall gaps is written in, and the associated signal levels thereof are stored in the form of signal level sequences in a first memory in tabular form, which is compared to tabular target value patterns of the signal level sequences stored in a second memory for each permissible revolution i (0≤i≤n), and a third memory is provided, in which tabular error target value patterns of deviations of signal level sequences, caused thereby, from regular signal level sequences stored in the second memory are stored.