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Thang Nguyen

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Thang Nguyen last won the day on July 10 2019

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About Thang Nguyen

  • Birthday 04/30/1980

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    LabVIEW 2016
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  1. Hi, Previously, I posted this question in wrong place. I moved it here. My team is trying to track down a memory leak issue with NI CSV (Compact Vision System). If the RT device run for 4 days it will have "Not enough memory" issue, but we still see available memory. We also limit the obtain reference. I would like to know if there is any property I can use to track down the allocated memory as well as release memory so I can track down on this memory issue. Thanks in advance!
  2. David, Currently, we already have that simple loop which can run with 10msec per image or 100 FPS. We are looking for option to upgrade to 150 FPS. The camera can up to this speed but the bottle neck is the compression step. That why I would like to do the compress at the end of each step. With your experience, do you think if I save each images separately into files will be faster than write into database? I can read, compress and write to SQLite database at the end of the test. Thank you very much!
  3. I would like to provide more information regarding my data: The image array size is 300,000 pixel * 8 One test has about 5528 images + particle measurement array in each them. Read Temp Table Time: 12.810000 sec Compress Image Time: 54.924000 sec Write Actual Table Time: 1.619000 sec (not sure why it is very fast here) Drop Temp Table Time: 265.688000 sec Originally, I have another index table which is foreign key reference to the image table. I also have to create temp table to reference to temp image table. The time above is for image table and index table with it.
  4. The reason I have these images save to a database is that at the end of the test, I need to collect this file as test data for post analyzing. I am thinking about your suggestion that temporary save the original images then compress them and save to database at the end but also the cost to save these images to file and read it back later. I hope to improve the speed from 100FPS to 150FPS or more. With your experience, do you think I can achieve the speed? The software is run on NI Compact Vision Controller (CVS).
  5. Currently, my vision software will do a compression (subtract to background image then count zero) and write to a table in SQLite file. Since we want to speed up the process, I write entire image in a temporary table. Then at the end, I read the table, do compression and write to the actual table, then drop the temporary table. This takes a lot of time too even I use the Journal mode = memory. I think the issue is I put the process code in 4 separated modules: Select the temp table -> output array Compress the output array of step 1 Insert the compress data from step 2 to actual table Drop the temp table I am looking for an option to mix these steps together to speed up the speed for example select and delete the row in temp table at the same time then at the end I can drop the table faster. Currently, it takes significant time to drop the table. Our raw data can be up to 3GB. But I don't know how to combine the query. I also read that SQlite does not support this. So I also looking for an advice on how to make this process more efficient. I thought about using the queue too but I need input before I change it. Thank you in advance.
  6. @Rolf You are correct about header. I added a header I can find on NI forum as below and it works. Thank you for your input
  7. Hi everyone, I am start working on a project require to communicate with a web service (written by another team). I have to use POST HTTP function to request access token with provide username, password and tenant name in JSON format. I use Flatten to JSON to convert a cluster to JSON string for buffer. I have connect URL as it suppose to be. I event use string constant to pass in the JSON directly, but when I ran, it returned header: HTTP/1.1 401 UNAUTHORIZED Date: Tue, 15 Dec 2020 04:05:22 GMT Content-Type: application/json Content-Length: 44 Connection: keep-alive Access-Control-Allow-Origin: * Server: Werkzeug/0.14.1 Python/3.7.2 body: {"message":"Error in Database connnection"} The another team told me to test with Postman and it run fine with the same input URL and JSON data. It returns the correct access token. I am not sure what the different between my labVIEW code and the Postman structure. I don't have much experience with HTTP and Web service through so I ask for your inputs. Thank you very much in advance.
  8. @JKHS. Thank again. Our lab does not use LIMS. My task is find out how to integrate our instrument test data to customer LIMS. As you describe, I will need to look for technical manual of our customer LIMS software.
  9. @JKSH: Sorry for late reply. My software controls an instrument in the lab to run cell analyst. One experiment session is start with pressurize the cell through a channel and using machine vision to analyze image captured of the channel. The experiment data is captured in database include of hardware data like pressure, voltage. In some lab they use LIMS to manage the workflow. I still not sure how should I integrate my test data into LIMS. Thanks for your information.
  10. Hi, I was asked by my supervisor about LIMS compatibility of our software. I did some research including search on LAVA still cannot get much information about technical side of LIMS. somehow I only know that it uses the OPC protocol but beside that I don't have any more information. Could you please share with me some information about LIMS and how do we communicate with LIMS from LabVIEW side. I worked with OPC server before. Thank you in advance.
  11. @Neil: Yes, this is what I need. Thank you very much.
  12. I want 1.2ex10 not 12.0ex9 as you can see in my example. I will check format into string.
  13. I need to display the engineer string in a tree so I used number to engineer string. The issue is it is very limited to format the engineer string with this function. Look at below example I want only one digit number before the decimal point but I don't know how to set that. Please let me know how to do it. Thank you in advance.
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