All posts by vogler

Native Image with GraalVM

19. November 2019Allgemeinvogler

Get the Windows version of GraalVM: https://github.com/oracle/graal/releases
Extract it to C:\app
Uninstall any Visual C++ 2010 Redistributables
Get the Microsoft Windows SDK for Windows 7 and .NET Framework 4 (ISO): https://www.microsoft.com/en-us/download/details.aspx?id=8442
Use the GRMSDKX_EN_DVD.iso
Mount the image and runF:\Setup\SDKSetup.exe
Run the Windows SDK 7.1 Command Prompt by going to Start > Microsoft Windows SDK v7.1 > Windows SDK 7.1 Command Prompt

c:\app\graalvm-ce-19.2.1\bin\native-image -jar Example.jar ^ --no-fallback ^ --report-unsupported-elements-at-runtime ^ --allow-incomplete-classpath ^

IIS Reverse Proxy Configuration

10. November 2019WinCC Unifiedvogler

If you need to add a reverse proxy to your Internet Information Server (IIS) you can just add a rule to your site configuration file. In the following example we add a reverse proxy (url rewrite) for a GraphQL Server to our WinCC Unified WebRH. Afterwards restart the site with the IIS services manager.

IIS Configuration File: 
"C:\Program Files\Siemens\Automation\WinCCUnified\SimaticUA\web.config"
 
 <configuration>
   <system.webServer>
     <rewrite>
       <outboundRules>
         <rule name="Remove Server header">
           <match serverVariable="RESPONSE_Server" pattern=".+" />
           <action type="Rewrite" value="" />
         </rule>
       </outboundRules>
             <rules>
                 <rule name="Reverse Proxy to GraphQL" stopProcessing="true">
                   <match url="^graphql" />
                   <action type="Rewrite" url="http://localhost:4000/graphql" />
                 </rule>                      
                 <rule name="UMC SSO Static">
                     <match url="(.*)" />
                     <conditions>
                         <add input="{URL}" pattern="(.*)\/umc-sso(.*)" />
                     </conditions>
                     <serverVariables>
                         <set name="HTTP_COOKIE" value="{HTTP_COOKIE};ReverseProxyHost={HTTP_HOST};ReverseProxyPort={SERVER_PORT}" />
                     </serverVariables>
                     <action type="Rewrite" url="http://localhost:8443/umc-sso{C:2}" />
                 </rule>  
             </rules>
     </rewrite> 
...

More examples for rewrite rules

<rewrite>
    <rules>
        <rule name="Reverse Proxy to webmail" stopProcessing="true">
            <match url="^webmail/(.*)" />
            <action type="Rewrite" url="http://localhost:8081/{R:1}" />
        </rule>
        <rule name="Reverse Proxy to payroll" stopProcessing="true">
            <match url="^payroll/(.*)" />
            <action type="Rewrite" url="http://localhost:8082/{R:1}" />
        </rule>
    </rules>
</rewrite>

Restart site with “Internet Information Services (IIS) Manager”

WinCC OA OPC UA Server

8. November 2019WinCC OAvogler

For testing sometimes it is too hard to deal with security :-). To make the OPC UA server in WinCC OA unsecure add the following lines to the config file.

[opcuasrv]
disableSecurity = 1
enableAnonymous = 1

Add the WCCOAopcuasrv manager to the project and start it.

To publish datapoints don’t forget to add the datapoints to the DP groups “OPCUARead” and “OPCUAWrite”.

Size of tables in PostgreSQL vs Apache Cassandra…

4. July 2018BigData/NoSQLvogler

PostgreSQL table with ts+key as primary key: ~43GB

PostgreSQL wide column table with ts as primary key : 247GB
Cassandra wide column table with ts as primary key: 4.5GB

Strange that in PostgreSQL a table with much less rows (but much more columns) needs a lot of more space (both tables store the same amount of data). )

It seems that the Apache Cassandra Column Store can compress the columns pretty good – factor 10 less disk space!

The source table in PostgreSQL (TimescaleDB) with a timestamp and a key column and 8 data columns had about 170 Mio rows.

CREATE TABLE candles
(
    instrument character varying(10) NOT NULL,
    ts timestamp(3) without time zone NOT NULL,
    o numeric,
    h numeric,
    l numeric,
    c numeric,
    primary key (instrument, ts)
)

I needed to flatten the table so that i have just the timestamp as primary key and many columns and each column is of a type. It ends up in a table with about 1.6 Mio rows and many columns.

CREATE TYPE price AS (
    o       float,
    c       float,
    h       float,
    l       float,
    volume  float
);

CREATE TABLE candles_wide
(
   ts timestamp(3) without time zone NOT NULL,
   AU200_AUD price,
   AUD_CAD price,
   AUD_CHF price,
   AUD_HKD price,
   AUD_JPY price,
   AUD_NZD price,
   ... 124 columns

Apache Cassandra wide column store table with ts as primary key and many columns.

CREATE TABLE candles (ts timestamp,
   AU200_AUD tuple<float,float,float,float,float>,    
   AUD_CAD tuple<float,float,float,float,float>,  
   AUD_CHF tuple<float,float,float,float,float>,  
   ... 124 tuples

Machine Learning for Sensor Prediction….

4. July 2018Machine Learningvogler

Trained a neural network with values from 30 sensors to predict another sensors value 10 minutes in future, the network hasn’t seen the test data before… with #Python #keras #TensorFlow

Python and WinCC OA…

7. February 2018Machine Learning, WinCC OAvogler

Connected Python to WinCC OA through a Websocket Manager. Python programs can connect to WinCC OA and read/write datapoints. Communication is JSON based, it’s simple to use in Python, see examples below (ws://rocworks.no-ip.org can be used for tests, but will not be available all the time).

https://github.com/vogler75/oa4j-wss

dpGet
dpSet
dpConnect
dpQueryConnect
dpGetPeriod
… more functions will be implemented

Required Python modules:

pip3 install websocket-client
pip3 install matplotlib

############################################################
# Open Connection
############################################################
import json
import ssl
from websocket import create_connection
url='ws://rocworks.no-ip.org/winccoa?username=demo&password=demo'
ws = create_connection(url, sslopt={"cert_reqs": ssl.CERT_NONE})

############################################################
# dpGetPeriod
############################################################
cmd={'DpGetPeriod': {
 'Dps':['ExampleDP_Trend1.'],
 'T1': '2018-02-07T18:10:00.000', 
 'T2': '2018-02-07T23:59:59.999',
 'Count': 0, # Optional (Default=0)
 'Ts': 0 # Optional (0...no ts in result, 1...ts as ms since epoch, 2...ts as ISO8601)
 }}
ws.send(json.dumps(cmd))
res=json.loads(ws.recv())
#print(res)
if "System1:ExampleDP_Trend1.:_offline.._value" in res["DpGetPeriodResult"]["Values"]:
 values=res["DpGetPeriodResult"]["Values"]["System1:ExampleDP_Trend1.:_offline.._value"]
 print(values)
else:
 print("no data found")

# Plot result of dpGetPeriod
%matplotlib inline 
import matplotlib.pyplot as plt
plt.plot(values)
plt.ylabel('ExampleDP_Trend1.')
plt.show()

############################################################
# dpGet
############################################################
cmd={'DpGet': {'Dps':['ExampleDP_Trend1.', 'ExampleDP_Trend2.']}}
ws.send(json.dumps(cmd))
res=json.loads(ws.recv())
print(json.dumps(res, indent=4, sort_keys=True))

############################################################
# dpSet
############################################################
from random import randint
cmd={'DpSet': {'Wait': True, 
 'Values':[{'Dp':'ExampleDP_Trend1.','Value': randint(0, 9)}, 
 {'Dp':'ExampleDP_Trend2.','Value': randint(0, 9)}]}}
ws.send(json.dumps(cmd))
res=json.loads(ws.recv())
print(json.dumps(res, indent=4, sort_keys=True))

############################################################
# dpConnect
############################################################
from threading import Thread

def read():
    while True:
        res=json.loads(ws.recv())
        print(res)
Thread(target=read).start()
    
cmd={"DpConnect": {"Id": 1, "Dps": ["ExampleDP_Trend1."]}}
ws.send(json.dumps(cmd))

Deep Learning Neural Network with WinCC OA and Clojure…

2. November 2017Allgemein, Machine Learning, WinCC OAvogler

To learn how deep learning works I decided to implement a Multilayer Neural Network with Backpropagation by my own in Clojure (I did NOT use a library like Tensor Flow or Deeplearning4j). The link between Clojure and the SCADA system WinCC OA is oa4j. With that connection the Neural Network can be used and trained with sensor data collected by the SCADA system …

Clojure connected to WinCC OA…

22. October 2017Allgemeinvogler

Because Clojure is a JVM language, oa4j can be used to connect to WinCC Open Architecture.

(def manager (new JManager))

(defn callback [values]
  (let [v (reduce #(+ %1 %2) (map #(.getValueObject %) values))];
    (dpSet :ExampleDP_Trend1. v)))

(defn -main [& args]
  (.init manager (into-array args))
  (.start manager)
  (dpSet {:ExampleDP_Arg1. 2.0 :ExampleDP_Arg2. 3.0})
  (println (clojure.string/join "," 
    (dpGet [:ExampleDP_Arg1. :ExampleDP_Arg2.])))
  (let [c (dpConnect [:ExampleDP_Arg1. :ExampleDP_Arg2.] callback)]
    (Thread/sleep 180000)
    (.disconnect c))
  (.stop manager))

Full example can be found here.

WinCC OA on Docker…

14. October 2017Allgemeinvogler

Here you will find Dockerfiles for WinCC OA: https://github.com/vogler75/winccoa-images

Matrix Multiplication in Clojure…

23. September 2017Allgemeinvogler

Clojure code for matrix multiplication (source: Rosetta Code) … short & smart…

(def mmul (fn [a b]
  (let [nested-for (fn [f x y] (map (fn [a] (map (fn [b] (f a b)) y)) x))
        transpose (fn [m] (apply map vector m))]
    (nested-for (fn [x y] (reduce + (map * x y))) a (transpose b)))))

(def ma [[1 2 3 4]
         [4 3 2 1]])

(def mb [[1]
         [2]
         [3]
         [4]])

(defn -main [& args]
  (println (mmul ma mb)))

RocWorks

Andreas Vogler