read data from a pi server -凯发k8网页登录
this example shows you how to read data from an osisoft™ pi server using the read
method. the read capability of industrial communication toolbox™ for pi provides a variety of options and flexible ways to get the data from your server. running this example requires that an osisoft pi system is installed. the demo tags used in this example were provided by osisoft and may be downloaded from the following location:
the pi server is capable of storing decades of real-time data from hundreds of assets. the matlab® interface for the pi system leverages the system's asset framework (af) to access time series data of your assets.
create client/server connection and retrieve required tags
connect to a pi server using the function. in this example the windows computer name is used as the pi af server name. your situation may vary depending on pi system configuration.
host = getenv("computername");
client = piclient(host);
request a list of related to the asset of interest. for more detailed information see .
tagsturbine = tags(client, name = "osidemo_gu4 turbine*")
tagsturbine=17×1 table
tags
___________________________________________________________________________________________
"osidemo_gu4 turbine.bearing temperature.c73204fa-e8f2-5513-1bc9-b5f097831d16"
"osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7"
"osidemo_gu4 turbine.cooling water intake temperature.f987e786-7a17-5027-1492-0482f0ae04b9"
"osidemo_gu4 turbine.cooling water output temperature.62d8d7be-2b82-53bc-09f1-660ffa00aa70"
"osidemo_gu4 turbine.cooling water pressure output.7c04f479-ae18-5207-0690-514252308c5b"
"osidemo_gu4 turbine.hours since last maintenance.ec8ae125-0ae5-5d45-1de6-0643ffac4983"
"osidemo_gu4 turbine.lubricant oil intake temperature.7fc3f299-b6ee-5e2e-3e7b-ca4ca59a9d9c"
"osidemo_gu4 turbine.lubricant oil output temperature.03c2ec47-7719-5f48-32b5-6c961d1a7912"
"osidemo_gu4 turbine.lubricant oil pressure output.9dd81865-26b3-57fb-0791-bf7a3cfea158"
"osidemo_gu4 turbine.oil level.201c4312-8852-50be-1d8b-297c216712ec"
"osidemo_gu4 turbine.total hours running.4438ad34-9e54-5075-1c76-19e3ac3fb728"
"osidemo_gu4 turbine.turbine vibration.e4c9f243-d5c9-5f5c-3b82-ed8076592ff9"
"osidemo_gu4 turbine.vane angle.3ddc1860-a9cc-54ee-2d41-595eb92fc677"
"osidemo_gu4 turbine.water flow.cf5b9b79-af11-5637-2317-f518e59b0c9f"
"osidemo_gu4 turbine.water in oil.562f483e-a814-5b11-3dd7-44b9735068ca"
"osidemo_gu4 turbine.water ph intake.2f31c444-6f9a-5005-083c-db8531de4d07"
⋮
read latest value of tag
read the most recent recorded value of a tag using the method.
vibrationlatesttt = read(client, tagsturbine.tags(2))
vibrationlatesttt=1×3 timetable
time tag value status
_________________________ ____________________________________________________________________________ _____ ______
21-december-2021 15:40:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.8 good
read values over period of time
to read values over a period of time, you first define a period. for example, to read values of a tag over the last two days, use the daterange
name-value pair to specify a starting datetime
and ending datetime
. set the start date to two days ago.
startdate = datetime("now") - days(2);
set the end date to now.
enddate = datetime("now");
use these to specify the starting datetime
and ending datetime
in your request.
vibrationtwodaystt = read(client, tagsturbine.tags(2), daterange = [startdate, enddate])
vibrationtwodaystt=559×3 timetable
time tag value status
_________________________ ____________________________________________________________________________ _____ ______
19-december-2021 10:45:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.83 good
19-december-2021 10:50:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.86 good
19-december-2021 10:55:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 1.03 good
19-december-2021 11:00:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.85 good
19-december-2021 11:05:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.8 good
19-december-2021 11:10:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.88 good
19-december-2021 11:15:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.89 good
19-december-2021 11:20:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.89 good
19-december-2021 11:25:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.79 good
19-december-2021 11:30:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.88 good
19-december-2021 11:35:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.84 good
19-december-2021 11:40:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.7 good
19-december-2021 11:45:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 1.04 good
19-december-2021 11:50:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.83 good
19-december-2021 11:55:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.82 good
19-december-2021 12:00:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.74 good
⋮
read all recorded values of a tag
to read all recorded values of a tag, it is useful to know when data recording began. you may use the earliest
name-value pair to determine this.
vibrationearliesttt = read(client, tagsturbine.tags(2), earliest = true)
vibrationearliesttt=1×3 timetable
time tag value status
_________________________ ____________________________________________________________________________ _____ ______
04-november-2021 20:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" nan bad
notice the value of this tag at the earliest recorded time is a nan. this is often the case for the first data point in a series as the pi server indicates a status of bad for this data point upon creation. you may take actions to exclude this from your data set if desired.
this earliest data point identifies the time of the first recorded value. you may now use this information to establish a starting datetime
for your request.
startdate = datetime(vibrationearliesttt.time(1));
set the ending datetime
to now.
enddate = datetime("now", timezone = "local");
depending on your system, this query may return a large amount of data. if you have an extensive history of data that makes this too slow or impractical, you may want to skip this step.
vibrationalltt = read(client, tagsturbine.tags(2), daterange = [startdate, enddate])
vibrationalltt=13171×3 timetable
time tag value status
_________________________ ____________________________________________________________________________ _____ ______
04-november-2021 20:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" nan bad
04-november-2021 20:30:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.72 good
04-november-2021 20:35:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.73 good
04-november-2021 20:40:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.86 good
04-november-2021 20:45:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.75 good
04-november-2021 20:50:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.73 good
04-november-2021 20:55:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.85 good
04-november-2021 21:00:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.83 good
04-november-2021 21:05:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.97 good
04-november-2021 21:10:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.77 good
04-november-2021 21:15:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.72 good
04-november-2021 21:20:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 1.02 good
04-november-2021 21:25:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.83 good
04-november-2021 21:30:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.89 good
04-november-2021 21:35:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.88 good
04-november-2021 21:40:00 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.95 good
⋮
reduce dataset using linear interpolation provided by pi server
notice the large number of datapoints in the result of the previous step. you may reduce the dataset by using the interval
name-value pair. for example the following read requests data with an interval of 30 minutes. the interval
name-value pair requests the pi server to perform linear interpolation on recorded values and provide results at the specified interval.
vibrationinterpolatedtt = read(client, tagsturbine.tags(2), daterange = [startdate, enddate], interval = minutes(30))
vibrationinterpolatedtt=2247×3 timetable
time tag value status
_________________________ ____________________________________________________________________________ _______ ______
04-november-2021 20:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" nan bad
04-november-2021 20:55:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.84713 good
04-november-2021 21:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.8386 good
04-november-2021 21:55:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.80423 good
04-november-2021 22:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.86857 good
04-november-2021 22:55:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.80717 good
04-november-2021 23:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.71863 good
04-november-2021 23:55:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.96133 good
05-november-2021 00:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.8542 good
05-november-2021 00:55:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.8 good
05-november-2021 01:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.74573 good
05-november-2021 01:55:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.72857 good
05-november-2021 02:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.79997 good
05-november-2021 02:55:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.8385 good
05-november-2021 03:25:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.79857 good
05-november-2021 03:55:43 "osidemo_gu4 turbine.bearing vibration.64a3ce99-f31e-593c-3e29-595f32095ce7" 0.74147 good
⋮
cleanup
when you are finished working with the pi server, disconnect and remove the client by clearing its variable from the workspace.
clear client;