Advanced Search

Hello Mbrandt.
I have used the following type of "HDH Exe Platine" with 3 channels.
www.ebay.de/itm/204779209363?srsltid=Afm...Gj67v4RUzT0PLvOgckrB
Very simple and very small. It fits between the glas scales and to the MESA directly. For mine I have paid less than 200 Euro.
[img]data:image/png;base64,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[/img]Best regards
Hartwig
 

Yes, I think he is

Edit:
Don't really have any tricks up my sleeves or anything, YangYang or Mika-net here on the forum coded the S-curve, I did most of the testing, we have not till now found anything better, performance and accuracy wise, it's possible some Algo is out there that is better we just have not come across it.
About the spikes, no idea we run 1ms servo and have not noticed realtime errors, I wasn't looking at servo thread in the scope during testing, I'd like your test codes to compare the spikes, possibly try some optimization, but the current code in the PR is best we got today.

I would use a new output pin that follows the state of estop. 

I think there is no simple answer now.. but from testing last few days its waaay good to control any hardware and smoothness is uncomparable...

I will share testing gcode in comming days .. but basically I go through all examples in nc_file folder and then my code.. my code will be avaible here

I am now searching the best solution of testing and validation ...there is not space for one lady said..

To prove all main stuff but idea is basicaly simole.. step by step test all avaible G code which I have from real machine but there is some limition of my time 

Btw 杨阳 is mika-net at forum? If am I wrong?
 

Hello Hartwig,
Thank you for your reply. I think my machine has some sort of EXE, its a board and the name is NCP59. But i dont know where to intercept the TTL signal from it. There is a version of this board with an extra digital output, but i dont have it on my machine. And buying 3 Heidenhein EXE is a step back. I would like to use a modern version of that.  Maybe a 7i85S or someting like that? 

And the Suplier you sent seams good and I will buy der 7i97T from him.


Here is a picture of the NCP 59:
(1, 2, 3 are X, Y, Z)

 

Thank you so much for the response, I have been going through a trial and a half with this install :') I bought some 2.2k 1/2W resistors just for this project, and have been battling to get a result

In halshow, none of the inputs change state, even the estop. But watchpin in the terminal shows clearly that estop, probe and for whatever reason, Z max (Home) limit switch change state even though it currently doesn't have a pullup. I only get a reaction from Z max when sensor is active.

I currently have a pullup on my X min, but can't get any reaction out of it no matter what state the proximity switch is in (on/off or jumper to GND) when using watchpin.

Just for reference as to wiring, I have all +wires > COM+> +WAGO fed by +FIELD, same setup for GND. Then individually connected sensor wires to MESA inputs. Pretty obvious, but just in case, I figured I best note it.

Also, I figured I will include multi readings in both states for all inputs with sensors on and off. X max excluding as I have found it to be dead. I will be replacing all of these anyway with PNP when they arrive. But was hoping to atleast get it running.

Readings are as follows:

X max DEAD
X min 3.9 off, 7.8 on
Y max 14.7 off, 18.4 on
Y min 12.3 off, 8.3 on
Z max 8.0 off, 14.9 on
Z min 12.4 off, 9.0 on

Readings might be telling or maybe not?

My GUI is also massive and a PITA, so I have mostly been doing my stuff through SSH. No matter what commands I send, I cant get the GUI to scale properly that's everything on the screen though, for whatever reason, my mini pc with Debian 12 cant seem to recognize the screen through HDMI. Any suggestions there would be absolutely amazing!

Should be good! Run it!

The way I would approach this (many ways).

First you need to look at the old controller and pray you see a step and direction text somewhere on the board, wire labels, anywhere.

If so follow the below. If not I'd probably see if I could find the software or manual to program the drives. Maybe chapgtp can help here?

If it's step and direction your life is easy
Step 1. Buy a 7i96 or 7i96s, if doing spindle speed control with a vfd S makes it a bit easier. (If you want to check sanity buy a stepper and drive to verify it works before testing the drives)
Step 2. Test the existing servo/stepper drives to see if they work. If you tore apart the wiring this may take some trial and error.
Step 3. Figure out the screw pitch and run through the pnf config

Finally that spindle looks usable...prob the easiest thing to save. Is it a 3 phase induction motor?

I'm not sure if auto resetting makes sense.

I don't think this would auto reset since I would still have to power the machine on in the ui to reset the drives. Also, the CL57T only allows resetting in this way for following errors and not overheating.

Currently my external estop is wired into the contactor latch for the drives/spindle power. Should I consider changing this?

Have a look at FlexGUI, seems easy to make and GUI you like/need/want
forum.linuxcnc.org/flex-gui/57726-flex-gui

Looking to join a thread on this topic and collaborate. Is there any progress on a Brake Press UI and a repo or something where I can use/contribute.
I'd prefer not to use a glade UI due to deprecation if possible.

I'm not sure if auto resetting makes sense. Often the alarm is raised when a motor overheats and it will need time to cool before engaging. An alternative would be to incorporate the enable signal into your estop circuit so the drives are only enabled when estop is off.
Cycling the estop will clear the error.

Johnny is on the right track. The following works well with qtdragon.
Tormach sell a granite surface plate with a hole in it for TTS tooling.
tormach.com/small-granite-surface-plate-...KYzs44ICkj1ujSHUakPj

Then you can insert your tools into TTS tool holders and pre measure them with a digital height gauge
www.ausee.com.au/products/digital-height-gauge-0-200mm-8
and record each tool's height into the linuxcnc tool table.
Measure the probe the same way as tool 99.
Then you just need select tool 99 and probe the top surface of your work piece. Now whenever a tool change is required, QTdragon's manual tool change will pause and let you change tools and resume your job.

 My thought was to use the tool setter to detect the toollength of the probe but a combination of multiple spring loaded buttons may throw off the actual tool length.

This should be easy enough to test.  Make a cut at a known height, measure the probe with the toolsetter, and probe the new cut.
 

What I do is put something flat like a 123 block in my vice. I lower the spindle without a tool in it so that it just touches the 123 block. I use TTS tooling so the nose of the spindle is what the tooling is going to seat up against when the tool is installed. With the nose of the spindle on the 123 block I make a note of the ABS Z value. Now I probe the 123 block. Now check the ABS value of the point where the probe tripped. Don't forget to account for the amount that the probe backs off after tripping. Min is .25 inch.

So if the ABS value of the nose on block is -12.000 and the ABS of where the probe was after the probe is -7.750 then account for the .25 backoff and the gives you -8.000 trip point. 12.000 - 8.000 = 4.000 so the probes effective length is 8". Put that value in the tool table as the length for tool 99 (The probe) Then when you touch of on the part it can take the Z position at touch-off and adjust it by the tool length of tool 99 and that value would be the Z would be at if the nose was on the part. Then when the length of the tool is applied Z will be what would put the tip of the tool on the part.

I hope this helps