About MauroRiboniMX

Disclaimer The goal is to use ctrlX CORE or a ctrlX OS as AI/Data analysis platform and code directly over the device without the necessity to create anytime an application. Jupyter APP ctrX Requirements: ctrlX CORE - x3 or x7 or a ctrlX OS installation Please note: Jupyter app is coming soon - Currently only available as B-Sample STEP0: install the app Once installed the Jupyter app will be present on the left sidebar.  Jupyter Sidebar Once we click on the Jupyter icon the app opens up. We can modify the content of the active directory and upload here our files.  Jupyter code   STEP1: Install and use libraries To install and use PIP downloadable libraries is very simple! First we need to open a new terminal and decide where to install the libraries. The command we need to run is: pip3 install LIBRARY -t LOCATION The library is then downloaded and installed in the chosen directory, it is suggested to use: SNAP_DATA: only for the app. SNAP_COMMON: mantained if the up is updated. SNAP_COMMON/solutions/activeConfiguration/YOURLIBRARYFOLDER (see below to create the folder): it is possible to backup and restore the libraries in this way! For the first and second method we can direclty run the installation command! Install PIP packages For the last method we need to create the library first, how? We open up a terminal and we run the following command, taking in account thet we want to create a folder that is called "mylibs". mkdir $SNAP_COMMON/solutions/activeConfiguration/mylibs create Folder Once the right libraries are there, we can create our Notebook. We need to add the created folder to the python folders in order to be able to use the libraries! use folder If we used the last method our code should look like this: use folder persistent STEP2: Upload zip files The app is equipped with the unzip packet. we can upload a file and the use the unzip command to unzip the archive in the local folder! Have Fun! ... View more

Disclaimer The goal is to use ctrlX CORE or a ctrlX OS installation in order to store and monitor High Frequency signals for condition monitoring. Let's go.  Oversample Array Requirements: ctrlX CORE - x3 or x7 or a ctrlX OS installation PLC app Node-Red just  PLC app + ctrlX WORKS Jupyter app (coming soon) STEP0: install Node-RED, InfluxDB, PLC app, and Jupyter (to come) The first goal is to install the needed apps and configure them. For Node-RED and InfluxDB apps we can follw this link: Setup influxDB and node-red.  Once we have anything installed we need to keep the influxDB token and write a simple plc Progam. STEP1: setup the PLC project We need to simulate the acquisition of an HighFrequency signal. We can think it like a simple function like y=Kt+White Noise, where t is an index of an array that contains the value of the function. We need to think that we need the following process: Create the vector and sample the generated value. Read the data with some high level language and format it accordingly for InfluxDB using a trigger Once the load is stored then reset the signal and repeat.  This simple functionality can be achieved using a simple PLC program.  PLC code STEP2: get the data, format it correctly and ship it in influxDB - Node-RED version To correctly load an array we need to create a string that contains the measurement name, the field and the value and the time. The string is then repeated with "\n" as ending character. It is also important to Set the right precision/ authorization and database details. Node-RED function Once the packet is ready we need to send a POST request that contains all the details.  Node-RED post The code can be shaped so that any time the PLC apps has a new array recorded Node-RED can then read and ship it. Can be also convenient to visualize directly in node-red the shape and maybe apply some downsampling if needed. The full code is attached. Node-RED code   Node-Red graph Anyway, the data will be visible in influxDB and IOT Dashboard as well! InfluxDB output STEP2: get the data, format it correctly and ship it in influxDB - python version The code in python is similar. Can be used externally or inside ctrlX CORE with a custom app or with Jupyter APP. Use Jupyter notebook to test this code!  Python Code Ciao 🙂 ... View more