Coordinate Measuring Machine Dynamic Error Compensation
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Solution Overview
Problem
Coordinate measuring machines (CMMs) face challenges in accurately compensating for dynamic errors and vibrations, which lead to measurement uncertainties due to model-reality mismatches and the complexity of handling varying parameters like air-bearing stiffness and damping, especially in weight-reduced designs.
Innovation Solution
A method using Kalman-filtering to derive dynamic state information by defining a dynamic model with actual state variables, predicting successive states through measurement comparison, and updating the model recursively to reduce errors and compensate for machine vibrations and deformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high static stiffness frame structure is used to improve measurement precision, then measurement precision is improved, but the machine becomes heavy and requires high forces for acceleration
Solution Approach 1:
The patent changes the material parameter from traditional heavy granite to carbon fiber reinforced plastic (CFRP), which has significantly lower density but maintains or improves stiffness through composite material properties. This parameter change resolves the contradiction by achieving high stiffness with reduced weight.
Solution Approach 2:
The patent employs composite materials (carbon fiber reinforced plastic) instead of homogeneous traditional materials like granite. The composite structure provides high specific stiffness (stiffness-to-weight ratio), simultaneously achieving measurement precision requirements while reducing machine weight and inertial forces.
2Speed
If weight reduction is implemented to improve acceleration performance, then acceleration performance is improved, but dynamic errors and vibrations increase
Solution Approach 1:
The patent implements dynamic error compensation through feedback mechanisms that continuously monitor and correct for vibrations and dynamic errors caused by weight reduction. This allows the system to achieve high acceleration while maintaining measurement reliability through active error correction.
Solution Approach 2:
The patent transitions from static error compensation to dynamic error compensation, accounting for time-varying errors that occur during motion. By modeling and compensating for dynamic effects in real-time, the system maintains reliability even with reduced mass that increases susceptibility to vibrations.
3Measurement precision
If static error compensation is used to improve measurement accuracy, then measurement accuracy is improved, but dynamic errors during movement are not adequately addressed
Solution Approach 1:
The patent extends error compensation from static to dynamic conditions by incorporating time-dependent error models that account for acceleration, velocity, and position variations during motion. This enables the system to maintain measurement accuracy across varying operational conditions.
Solution Approach 2:
The patent changes the error compensation approach from fixed static parameters to dynamic parameters that vary with machine state (position, velocity, acceleration). This parameter adaptation enables accurate compensation throughout the full range of motion, not just at static calibration points.
Data Source
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AI summary
The invention relates to a method for providing dynamic state information for at least a part of a coordinate measuring machine, the coordinate measuring machine comprising a base, a probe head, a machine structure with structural components for linking the probe head to the base and at least one drive mechanism for providing movability of the probe head relative to the base. A dynamic model is defined with an actual set of state variables, the state variables being related to a set of physical properties of at least the part of the coordinate measuring machine and representing an actual state of at least the part of the coordinate measuring machine" and the actual state of at least the part of the coordinate measuring machine is derived by a calculation based on the dynamic model. According to the invention, a filtering process is executed with the dynamic model with deriving a set of prediction variables based on the state variables, the prediction variables describing an expected proximate state of at least the part of the coordinate measuring machine, measuring at least one of the state variables and determining a set of observables based on the measuring, deriving a set of successive state variables by comparing the set of prediction variables with the set of observables and updating the dynamic model using the set of successive state variables as the actual set of state variables.