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Automated benchmarking of mechanical components

IP.com Disclosure Number: IPCOM000208902D
Publication Date: 2011-Jul-22
Document File: 3 page(s) / 516K

Publishing Venue

The IP.com Prior Art Database

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Page 01 of 3

Method to benchmark "feel" of air-registers from travel-effort measurements.

To improve perceived quality of air-register operating feel it is important to know what engineering parameters affect customers' perceived quality and how to tune them for optimal feel, and to have a methodology to measure and analyze actual components. A method to process measured data to automatically extract and benchmark the parameters relevant to customers' perception of "feel" (called parameters, hereafter) is here described. This is a novel, automated tool to assess quality. Multiple measurements taken at different speeds, of sampling rates, and by alternate recording methods are used to optimize extraction of the parameters, in a way similar to the high dynamic range composition method used for photo processing.This method articulates in seven steps.

Step 1) First, the total operating friction is extracted from a sample measurement collected at a typical actuation speed. The parameter is estimated as an average and not as a function of position because possible artifacts in the measurement data would make extraction of detailed information pointless. Total operating friction T

f is calculated

for both departure and return actuation trips (called left-to-right and right-to-left travel, respectively, in the rest of this paper.). The averaging effort along both legs of travel are:

f

L

2

R

(

)

f

R

2

L

(

)

f

 L T

2

R

=

n

=

,

1

 R T

nsamples

,

f

2

L

=

n

=

,

1

nsamples

nsamples

n

nsamples

n

Step 2) The end-wall constraints, the fixture play and the register knob wobble are extracted from a sample measurement collected at a low operating speed. Note that both left and right end wall constraints are estimated for both actuation directions, as shown in figure.

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Estimate of end-wall stiffness and fixture play for left-to-right and right-to-left travels.

For the left-to-right travel the identification of the left end-wall boundary is made easy by the presence of play in the fixture. This is a zero effort span in the signal that is easy to identify. First, as the fixture detaches from the part the effort drops from negative to zero. The point at which it happens is the boundary of the end-wall constraints. Then the search is on for the first point at which the fixture re-engages the part. The right wall cannot be identified by looking for sharp changes in the signal first derivative. This is because many registers do not exhibit a well-defined transition. Instead, starting from the right and going left the search is on for the first point at which its slope is less than a predefined threshold.Extra filtering is applied during this process to eliminate false positives. Additionally, the process must be robust in the presence of glitches. Only when the slope remains below a threshold for a specified minimum travel is the search for the wall boundar...