Geo-Adaptive Tilt Measurement Filtering for Working Machines
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Solution Overview
Problem
Existing tilt and angular velocity measurement systems in working machines face delays in adapting filter parameters to changing environmental conditions, leading to unreliable sensor output due to sensitivity to dynamic influences like high-frequency vibrations and varying ground conditions.
Innovation Solution
A measurement system with adaptive filtering that selects filter parameters based on the geographical position and ground conditions, using a geopositioning system to quickly adjust to changing environmental conditions, incorporating a filter parameter selection unit that determines optimal filter settings based on real-time geographical data and environmental properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If filter parameters are selected based on calibration under static conditions, then measurement precision is improved under controlled conditions, but adaptability to dynamic operating conditions deteriorates
Solution Approach 1:
The filter parameters are made dynamically adjustable based on detected operating conditions rather than being fixed during calibration. The system transitions from static calibration-based parameters to dynamic condition-based parameter selection, allowing the measurement system to adapt to varying ground conditions, vibration levels, and environmental factors in real-time.
Solution Approach 2:
The system changes filter parameters based on detected operational characteristics such as vibration amplitude, ground condition, and motion patterns. Different filter parameter sets are selected or adjusted according to the current operating state, enabling the system to optimize measurement precision for each specific dynamic condition rather than relying on a single calibrated parameter set.
2Adaptability or versatility
If filter parameters are adapted online to changing conditions, then adaptability is improved, but measurement precision deteriorates due to delays in parameter adaptation
Solution Approach 1:
The system performs preliminary detection and classification of operating conditions before finalizing filter parameter selection. By pre-identifying the operational state (e.g., through vibration analysis or motion pattern recognition), the system can proactively select appropriate filter parameters in advance, reducing the delay between condition change and parameter adaptation while maintaining measurement precision.
Solution Approach 2:
The system continuously monitors measurement quality and operating conditions, using feedback to adjust filter parameters. When deviations from expected behavior are detected, the feedback mechanism triggers parameter re-adjustment, ensuring that measurement precision is maintained while adapting to changing conditions. This closed-loop approach minimizes delays by continuously optimizing parameters based on real-time performance data.
3Adaptability or versatility
If multiple filter parameter sets are maintained for different conditions, then adaptability is improved, but device complexity increases
Solution Approach 1:
The filter parameter management system is segmented into distinct parameter sets organized by operating condition categories. Each segment corresponds to a specific operational state (e.g., high vibration, low vibration, specific ground conditions), making the complex parameter management task more structured and manageable. This segmentation allows the system to efficiently select from predefined parameter sets rather than managing a single complex parameter space.
Solution Approach 2:
The system automatically selects and switches between filter parameter sets based on detected operating conditions without requiring manual intervention. The self-service mechanism uses condition detection algorithms to autonomously determine the appropriate parameter set, reducing the operational complexity of managing multiple parameters while maintaining high adaptability across different working conditions.
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 rapid adaptation to dynamic conditions, providing reliable tilt and angular velocity measurements by minimizing delays in filter parameter updates, thus improving measurement accuracy and stability under varying ground conditions.
Implementation Method 1
The sensor units do usually include spring-supported movable masses which are capacitively coupled to provide a variable capacitance output depending on gravity and motion-induced force
Implementation Method 2
The variable capacitance is conventionally measured to provide an electrical sensor signal in the form of e.g. a voltage signal or the like, depending on gravity and motion-induced force, such as an inertial force or centripetal force
Implementation Method 3
Due to gravitation, such IMUs always provide a constant output vector which may offset all other measured acceleration forces. The direction of the gravitation-induced constant output vector may be regarded as an indicator of the tilting angle of the device
Implementation Method 4
preprocessing may include filtering of the raw sensor signals, particularly to reduce or eliminate dynamic influences, such as from high-frequency vibrations or the like
Data Source
AI summary
The present invention relates to a measurement system (14), particularly a tilt measurement system or an angular velocity measurement system, for outputting output sensor data wherein the output sensor data indicate, with respect to a gravitational force vector, an inclination (tilting angle) or respectively an angular velocity of the device, particularly a working machine (1), which it is fixedly attached to, comprising:a sensor unit (22), particularly an inertia measurement unit or a gyroscope, including one or more sensor elements for detecting force and/or angular velocity and being configured to continuously provide raw sensor data samples for each of the sensor elements.a filter parameter selection unit (24) configured to select one or multiple filter parameters sets each including one or more filter parameters for the filtering, wherein the filter parameters sets are selected by at least one predetermined rule applied on the raw sensor data samples,a filter unit (23) configured to filter data to provide the output sensor data depending on the selected one of a plurality of filter parameter sets, wherein the data depends on or corresponds to the raw sensor data samples obtained by the sensor elements;characterized by a geopositioning system (25) configured to provide a geographical position of the measurement system (14),wherein the filter parameter selection unit (24) is further configured to select the one or multiple filter parameter sets depending on the geographical position of the measurement system.