Mitsubishi MELFA 4D-2CG5100-PKG-E, Инструкция по эксплуатации

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11 Appendix
Performance of this product (comparison with built-in type RZ511 vision sensor) 11-140
11. Appendix
11.1.
Performance of this product (comparison with built-in type RZ511
vision sensor)
Below is a comparison of the performance of this product with that of our built-in type vision sensors.
11.1.1.
Comparison of work recognition rate
(1) Comparative results by work shape and conditions
Table 11-1 Comparative Results by Work Shape and Conditions
Work condition Network vision sensor Built-in vision sensor
Overlap
○ ×
Approach or contact
○ ×
Tilt
○ △
Front/rear judgment
○ △
O: Recognition with pretty much no problems possible
△
: Recognition possible under some conditions
×
: Recognition almost impossible
With network vision sensors, it is possible to recognize overlapping work and work nearly in contact
or in contact, work that is difficult to recognize with the built-in vision sensors.
Network vision sensors also improve the recognition rate for tilted work and front/rear work.
(2) Comparison of functions for recognition pattern registration
Table 11-2 Comparison of Functions for Recognition Pattern Registration
Function Network vision sensor Built-in vision sensor
Area size change Yes Yes
Specification of coordinates
for output to robot Yes Yes
Area angle change
Yes
(No need to change the work
angle)
No
(Necessary to change the work
angle)
Area shape change
Yes
(Square/fan shape/round)
No
(Square only)
Network vision sensors improve the work pattern registration functions.
It is possible to change the area angle without any need to change the work angle and the area
shape can be changed to square, fan shaped or circle.
11.1.2.
Comparison of image processing capacity
Table 11-3 Image Processing Capacity
Network vision sensor Built-in vision sensor
4 10 30 4 10 30
Image processing time 276ms 278 ms 367 ms 794ms 946ms 946ms
Data transfer time 121 ms 142 ms 249 ms 80ms 99ms 127ms
Total time 397 ms 420 ms 616 ms 874ms 1045ms 1073ms
"Table 11-3 Image Processing Capacity" shows the measurement results when the work is recognized
with the same conditions.
The image processing time can be reduced by using network vision sensors.
For network vision sensors, the increase in the number of pieces of work recognized increases the data
transfer time.