Measurement Data

Import manually measured tachymeter measurements

To be able to import measurements taken manually with a tachymeter into Sedrix, this data must be converted into a format that Sedrix can read.

We recommend Sedrix Tachymeter CSV, which was developed for this purpose.

Step 1: Create a data source or select an existing one

If no corresponding data source exists, create one in the devices overview:

Please make sure to select the correct coordinate system - this cannot be changed later.

Step 2: Upload files

The data can now be uploaded either via FTP or directly in the web interface.

FTP: The files must be uploaded to the respective import folder. This is recommended when data or lots of files are regularly uploaded at once. However the FTP access will require setting up.

Web interface: In the overview of the data source, select “Upload data” in the context menu. A dialog opens in which files can be uploaded. This is recommended if only a few files are to be uploaded.

Format description: Sedrix Tachymeter CSV

The Sedrix Tachymeter CSV was designed especially for the improt of manual tachymeter measurements. It consists of a header for information regarding the measurements and the actual measurements from the measuring points.

Example:

CODE

Station;Punktgruppe 1;;;;;;;
Measurement time;2018-04-29T18:34:00+02:00;;;;;;;
Start;2018-04-29T18:34:00+02:00;;;;;;;
End;2018-04-29T18:34:00+02:00;;;;;;;
Pressure [mBar];950.3;;;;;;;
Dry temperature [°C];14;;;;;;;
Wet temperature [°C];20.4;;;;;;;
Tachymeter length inclination [gon];0;;;;;;;
Tachymeter cross inclination [gon];0;;;;;;;
Coordinate system; CH1903+ ;;;;;;;
Messpunkt;Measurement time;E;Unit;N;Unit;H;Unit;Durchgänge
MTh_5;2018-04-29T18:34:00+02:00;17.00297406;m;6.978666506;m;1.328789513;m;1
MTh_6;2018-04-29T18:34:00+02:00;16.29822192;m;0.552248402;m;1.302087357;m;1
101;2018-04-29T18:34:00+02:00;8.585497723;m;6.511685539;m;1.007654771;m;1
102;2018-04-29T18:34:00+02:00;8.790657113;m;6.791447731;m;1.006665711;m;1
103;2018-04-29T18:34:00+02:00;8.774723639;m;7.112170485;m;1.005923748;m;1
104;2018-04-29T18:34:00+02:00;9.333302668;m;6.266344943;m;1.008357046;m;1
105;2018-04-29T18:34:00+02:00;9.280260556;m;6.621149192;m;1.006806306;m;1
106;2018-04-29T18:34:00+02:00;9.521870116;m;6.88304942;m;1.004014369;m;1

The header defines the device measuring pointPunktgruppe 1 for the measurement time2018-04-29T18:34:00+02:00, followed by meteorological data at the time of measurement and the coordinate system being used.
The coordinate system given in the CSV file must correspond to the coordinate system specified when creating the data source!
The data division defines the measurement results (coordinates) for the measuring points MTh_5, MTh_6 and 101 to 106.

When creating data files, please adhere exactly to the respective format as specified in order to avoid problems during processing. This applies in particular to the notation of decimal numbers: Unless otherwise specified, please use a dot as a decimal separator and do not add dots as thousands separators.
Example:

1.234,5

1234,5

1234.5

Import manually measured time-value rows

To import time-value measurements that were taken manually into Sedrix, they must first be put into a format that can be read by Sedrix.

We recommend Sedrix Logger CSV, which was developed for this purpose.

Step 1: Create data sourceStep or Cctreate data source or select an existing one

If no corresponding datIf no corresponding data source exists, first create one in the device overview:

Please make sure to select the correct data format.

Step 2: Upload files

The data can now be uploaded either via FTP access or directly in the web interface. The files must be uploaded in the corresponding import folder. This is recommended when data or many files are regularly uploaded at once.the corresponding import folder. This is recommended when data or many files are regularly uploaded at once. It requires setting up FTP access.

Web interface: In the overview page of the data source, you can select “Upload data” in the context menu. A dialog opens to upload files. This method is recommended when only a few files are to be uploaded.

Format description: Sedrix Logger CSV

Column 1: Time stamp with time zone
Example: “Date (UTC-5)”

Column 2: Channel name
Example: “Temperature”

Column 3: Unit
Example: “Unit”

Columns 2 and 3 can be repeated as necessary for further channels.

Example for two channels, “CA1” and “CA2”:

CODE

Date (UTC-5);CA1;Unit;CA2;Unit;
31.01.2018 16:00;1,3123;bar;0,00;cm;
03.02.2018 08:43;1,3215;bar;-9,41;cm;
07.02.2018 08:37;1,3265;bar;-14,48;cm;
09.02.2018 08:40;1,3284;bar;-16,47;cm;
28.03.2018 09:54;2,4042;bar;-16,47;cm;
30.03.2018 10:09;2,4120;bar;-24,43;cm;
04.04.2018 10:43;2,4189;bar;-31,49;cm;
06.04.2018 09:30;2,4228;bar;-35,47;cm;
11.04.2018 09:30;2,4303;bar;-43,07;cm;
13.04.2018 10:40;2,4303;bar;-43,07;cm;
18.04.2018 11:00;2,4354;bar;-48,32;cm;
20.04.2018 14:10;2,4303;bar;-4

Filter measured data

When assigning raw data to measuring points, filters can be defined to filter the measurement data before it is displayed or processed further.

Moving average filters are currently implemented, which average measurement data according to certain criteria. The current measured value is determined by averaging over a predefined number of measured values in the past, whereby further criteria can be applied to these measured values.

This number of measured values in the past forms the averaging window. The number represents its maximum “width”.
To calculate a specific measured value, you can now imagine this averaging window positioned at the measured value, which selects a certain number of measured values from the time series in the past for averaging. In the course of the calculation for the entire time series, this window is shifted step by step from measured value to measured value, starting with the oldest measured value in the direction of more recent measured values, and the mean value is recalculated for the current measured value respectively.

Note: If using the process outlined above, it does mean that filtering is not possible for a certain number of the oldest measured values in the time series, as there are not enough previous values. The error code 910 is then set for the affected measured values. When interpreting the results, a certain run-in time must therefore always be taken into account, which depends in particular on the selected window width and the measurement cycle with which the time series was recorded.

Simple moving average

The current measured value is determined by averaging over a number of measured values in the past, whereby a maximum measured value age relative to the current measured value timestamp must be specified in addition to the window width to configure this filter.

This means that the new value to be calculated for the current point in time by the filtering is a simple arithmetic mean of the previous values in the averaging window, whereby a measured value in the window is only included in the averaging if its timestamp relative to the timestamp of the current measuring point is not older than the specified maximum age.

In particular, this prevents excessively old measured values from being included in the averaging if there are correspondingly long measurement pauses.

Mean variance

The mean value is initially calculated in the same way as for the simple moving average, but the measured values in the averaging window are ultimately subjected to a further check:

Only measured values that lie within a predefined bound, which is defined as a multiple of the current standard deviation, around the current window mean value contribute to the final mean value.
This makes it possible for outliers to be suppressed.
The “age criterion” described for the simple moving average also applies to measured values in the averaging window for this averaging method.

Set filtering for a channel

Filtering can be defined separately for each measuring point channel. This is done in the assignments of a measuring point, the filter criteria are therefore considered properties of the assignment.

Filter properties

Window width
Specification of the number of measured points in the past which are used for the average - in metaphorical terms: the width of the averaging window.
Restrictions: This whole number must be greater than 2.
The larger the value, the greater the computing effort.
Filter width in hours
Specification of a time period as the maximum age of measured values in the averaging window, relative to the respective current calculated measured value.
Multiple of standard deviation – only for the filter type “Mean variance”:
Specification of a multiple of standard deviation.

The filter width in hours must be set large enough to ensure that there are sufficient measured values in the window for the measurement frequency of the channels that are being filtered.

Status and error codes

Measured values can contain errors if measurements fail for technical reasons. Along with the actual value and its timestamp, each measured value in Sedrix also carries an error code for this reason.

The value of the error code is normally 0, which means that the measured value it belongs to does not contain an error.
An error code can also be used to indicate that a value could not be calculated during processing/analysis in Sedrix, e.g. due to an incorrect configuration of a function block.

Error classes

Status and error codes are divided into the following error classes according to the severity of the states or errors they indicate:

Codes < 1000: Status codes: No error
Examples:
- Code 10: Value has been interpolated
- Code 900: No data
- Code 905: Value is not calculable
- Code 910: Not enough data for filtering
Codes >= 1000 but less than 2000: Minor errors
Example:
- Code 1000: Measured value available but unreliable
Codes >= 2000 but less than 3000: Moderate errors
Examples:
- Code 2000: Measured value available, but very likely invalid
Codes >= 3000: Serious errors
I.e. no measured value is available
Example:
- Code 3001: Reference measurement not found
- Code 3220: Invalid measured value

Displaying status and error codes

Status and error codes can be displayed if necessary in table evaluations. These evaluations have a setting option for this purpose with the following options:

“Display error codes (only error codes > 10)”
“In separate column (all)”
“In separate column (only error codes > 10)”
“Do not display”

If one of the options for displaying error codes is selected here, any status or error codes that have occurred are displayed in a small box next to the relevant measured value or, if necessary, in a separate column.
The color of the box gives a quick overview concerning the severity of the error:

light blue: status codes and minor errors
Orange: moderate errors
Rot: serious errors

Hover your mouse over an error code box to see a short text description of the error displayed as a tooltip.