Filter Tuning via Eigenvalue Convergence and Material Removal
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Solution Overview
Problem
Large-scale filter production exhibits significant performance variations due to factors like ceramic block shrinkage, mixture variations, and furnace firing issues, making post-production tuning difficult, especially for filters with complex coupling among non-adjacent resonators, which requires skilled labor and is costly and time-consuming.
Innovation Solution
A method and system that measure frequency responses, compute coupling matrices, extract eigenvalues, and use material removal to iteratively converge the device under tune to the target device's eigenvalues, employing a computer-controlled mechanical tuning mechanism for precise adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If post production tuning is performed on filters with complex coupling among non-adjacent resonators, then device performance can be corrected, but the process becomes difficult, time-consuming, and expensive requiring skilled labor
Solution Approach 1:
The patent applies preliminary action by pre-calculating optimal tuning locations and parameters using computer simulations before actual production. The system determines the exact material removal specifications for each filter based on predicted performance variations, allowing automated execution without skilled labor intervention during post-production tuning.
Solution Approach 2:
The patent replaces the manual mechanical tuning process with an automated system that uses computer-controlled material removal. The tuning apparatus automatically positions and removes material based on pre-calculated parameters, substituting skilled labor with an automated combination of computational algorithms and precision machining.
2Manufacturing precision
If skilled laborers perform post production tuning, then individual filter performance can be adjusted, but the process becomes inherently expensive and output is constrained by finite skilled labor availability
Solution Approach 1:
The patent implements self-service by enabling filters to be automatically tuned without human intervention. The system uses computer simulations to self-determine tuning parameters and automated apparatus to self-execute the tuning process, eliminating the need for skilled laborers and reducing costs.
Solution Approach 2:
The patent applies parameter changes by systematically varying material removal parameters (location, amount, depth) based on computational analysis. The system adjusts these parameters automatically for each filter based on predicted performance variations, replacing manual judgment with algorithmic parameter optimization.
3Manufacturing precision
If traditional post production tuning methods are used on filters with significant coupling among non-adjacent resonators, then performance corrections can be made, but the tuning process becomes difficult and requires careful selection of each modification
Solution Approach 1:
The patent applies preliminary action by pre-calculating all tuning parameters through computer simulations before production. The system determines the optimal material removal specifications for complex coupled resonators in advance, eliminating the difficulty of real-time decision-making during tuning.
Solution Approach 2:
The patent introduces a computer simulation model as an intermediary between the filter design and the actual tuning process. This virtual model allows complex coupling interactions to be analyzed and resolved before physical tuning, simplifying the actual execution by providing pre-determined solutions.
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
This approach reduces processing time and manufacturing costs by enabling accurate and efficient tuning of filters with complex coupling networks, achieving convergence in minutes and improving device characteristics like isolation and insertion loss.
Implementation Method 1
tuning the DUT with a material removal source
Data Source
AI summary
The present application describes a method of tuning a printed device. The method includes measuring a frequency response of a target device and a device under tune (DUT). The method includes computing, based on the measured frequency response, a coupling matrix for the target device and a coupling matrix for the DUT. The method also includes extracting eigenvalues for the coupling matrix of the target device and a first set of eigenvalues for the coupling matrix of the DUT. The eigenvalues of the target device are different than the first set of eigenvalues of the DUT. The method further includes tuning the DUT with a material removal source. The method even further includes measuring a second set of eigenvalues of the DUT. The second set of eigenvalues is different from the first set of eigenvalues of the DUT. The method yet even further includes calculating a tune path for iterative convergence of the second or a subsequent set of eigenvalues of the DUT with the eigenvalues of the target device. The method still even further includes observing the iterative convergence of the DUT and the target device.