The next paragraphs will explain how to change settings. The settings of the oscilloscope are divided into two groups: Instrument settings, that affect all channels of the instrument and Channel settings, which only influence a specific channel.

Instrument settings:

• Record length
• Sample frequency
• Pre trigger percentage
• Trigger timeout
• Trigger source

Changing the instrument settings can be done in different ways:

• Using the instruments menu.
• Right click the text labels on the instrument bar
• Right click the instrument in the object tree.

Channel settings:

• Coupling
• Sensitivity
• Trigger level
• Trigger hysteresis
• Trigger type

Changing the channel settings can be done in three different ways:

• Using the Instruments menu.
• Right click the channel in the object tree.
• Right click the channel axis.

The AWG control window can be opened by double clicking on the AWG object in the object tree. More information on the AWG can be found on the AWG page.

The demo source contains a little bit of data, which is only meant for demonstration. There are two different data sets from which one is chosen depending on the number (even or odd) of the demo source.

Hint:

Try creating two demo sources and add them to an empty graph. If you set the graph to XY-mode you can see the purpose of the demo data. You can read how to view data in a graph here.

The software generator can be used to generate standard signals like sine, block and triangle. Through its popup menu all its settings can be changed. This object can be used in combination with any other source, including the channels of the measurement instruments. The generator supports the following signal types:

• Sine
• Triangle
• Square
• Noise

Several signal parameters can be adjusted:

• Signal frequency
• Phase
• Amplitude
• Offset
• Symmetry
• Data size
• Sample frequency

Averaging is useful in situations when the signal of interest is periodic and (random) noise is present on top of it. By taking multiple measurements of the signal and averaging them, the signal to noise ratio will increase.

The average I/O object can work in two different modes: running average (default) and average-of-n. When the object is working in running average mode, it will continuously replace a part of its memory by the newly arriving data, effectively "forgetting" the oldest measurements. In average-of-n mode, the average will automatically be cleared after n measurements. You can manually clear the average with the Clear option in its menu.

When the Stop after count option is checked, the average I/O will stop collecting data when Averaging count measurements have been collected. The internal average count is reset when Clear is pressed.

When only expand is set, the data size of the average gets higher when the source's data size grows, but does not shrink when the source's data does. This can be useful when averaging data of a source with variating data size.

The Min/Max detector can be used for detecting minimum or maximum values of a source. By default maximum values are be detected. Every time the source of the Min/Max detector signals new data, the detector will compare each value in memory to the new source data and keep the largest value. Minima can be detected instead of maxima by choosing Minimum in the popup menu. In the figure below, the spikes (maxima) in a sinusoidal signal (green) are detected by a Min/Max detector (purple).

Optionally a fall-off percentage can be set. If this percentage is not zero, the output will slowly fall back to the input signal. The higher the fall-off percentage, the faster the memory values of the detector will fall in the direction of the source values. The effect can be compared to a VU-meter with peak detect.

When only expand is set, the data size of the Min/Max detector gets higher when the source's data size grows, but does not shrink when the source's data does. This can be useful when detecting minima or maxima of a source with variating data size.

This processing block can be used to filter data. Data is filtered with a first order low-pass IIR filter. The cut-off frequency can be entered through its popup menu. The filtered data can be multiplied by a gain which can also be entered through the popup menu.

The data collector object can be used when performing streaming measurements. During streaming measurements, data arrives in blocks with a size equal to the instrument's record length. To form a continuous stream of data, these blocks must be appended to each other. The data collector does this job. It will fill its data with the arriving blocks of data, see the picture below. The size of the collected data can be set to a maximum of 20 million samples.

The data collector object has several options:

• The size of the output block can be set with the Data size item in the menu
• Two different Fill modes can be selected:
  • From left to right: new data is appended starting from the left
  • From right to left: existing data is shifted to left, new data is appended at the right
• When the output data block is full, different actions can be performed:
  • Continue: the oldest data is shifted out at the left, while new data is appended to the right
  • Stop: data collecting is stopped when full. (The measurement is NOT stopped.)
  • Clear: the output data is cleared and the filling starts over again
  • Overwrite: existing data in the output array is overwritten by the new data (roll mode)

The Gain/Offset I/O can be used to multiply a signal with a certain factor and to add an offset. It is mostly used in combination with sensors. For example, if you are measuring with an acceleration sensor which produces 167 mV/g, you can convert the measured voltage to g's with a gain factor of 1/0.167=5.99. Note that you do not have to calculate this. You can enter this value directly as "1/0.167" or "1/167m".

You can enter the offset in two ways: at the input or at the output. In the example with the accelerometer, you can subtract the component caused by gravity in two ways: enter an input offset of -167 mV, or enter an output offset of -1 g. You can automatically remove the input offset with the Neutralize input offset action.

When the source of the Gain/Offset I/O is a spectrum, you can use the "Spectrum to density" setting to convert a magnitude spectrum into a density spectrum. For example if the unit of the source spectrum is V, the output unit will become V/Hz.

Hint:

To invert a source, you can use a Gain/Offset I/O with a gain of -1.

This processing block can be used to limit or clip a signal to a certain range. The clip range can be set via the popup menu of the limiter. The limiter works as follows: all values of the signal above the maximum of the clip range are changed to the maximum value. All values below the minimum of the clip range are changed to the minimum value.

if sample < Clip_min then sample := Clip_min else if sample > Clip_max then sample := Clip_max;

The FFT I/O object can be used for spectral analysis of a signal. The FFT object converts a time domain signal to a frequency domain signal by means of a Fast Fourier Transform, an efficient algorithm to compute the Discrete Fourier Transform (DFT). The output of an FFT I/O can be connected to a graph with a frequency scale or an empty graph.

The Fast Fourier Transform treats the input signal as if it was a periodical signal. In other words, it assumes the signal is an infinitely long series of repetitions of the record. In practice, mostly the record does not contain an integer number of cycles of the signal. Therefore, if the end of the record is connected to the beginning, a discontinuity will arise, which results in extra frequency components in the resulting spectrum. This effect is called spectral leakage.

To minimize the effect of spectral leakage, the input record of the FFT can be multiplied with a window. This is called windowing. Several windows can be chosen in the menu of the FFT I/O, which all basically perform the same action: they make the edges of the record smoother to make the discontinuities smaller. In most cases, the Blackman-Harris window will give the best results. However, if your data contains an integer number of cycles, the rectangle (no windowing) will give the best result. The following window functions are available for the FFT-block:

• Rectangle
• Hanning
• Hamming
• Bartlett
• Parzen
• Welch
• Blackman
• Blackman-Harris

In modern engines, usually a crankshaft sensor is present which generates a periodic signal with a number of cycles per revolution of the engine. The RPM block can be used to convert this signal into revolutions per minute. The engine speed can be calculated multiple times per revolution. Because of this, variations in the engine speed during a revolution can be seen.

If the figure you can see a crank shaft signal of a truck during start-up, which is converted to the engine speed with an RPM block. The middle picture is a zoomed in part of the top picture.

In a typical crankshaft signal, gaps are present. The signal can for example consist of three times eighteen cycles of a sine and a two cycle gap per revolution, which results in sixty cycles per revolution. This is the default setting of the RPM-detector. The gaps are detected internally by the RPM block and the number of RPMs is only detected between each cycle of the sine wave.

During processing of the input signal, the data is filtered with a second order low pass filter, which makes the detection of the correct engine speed less sensitive for noise and results in a more accurate detection.

The number of periods per revolution of the used engine can be entered through the popup menu of the RPM block. As well as the maximum detectable RPM. Besides the maximum value that will be visible along the axis, the latter setting also influences the cut-off frequency of the internal low-pass filter.

Hint:

To view the number of revolutions per minute as a number, enable the cursor readout of the graph or use a Meter.

The Sum object can be used to add or subtract the data of different sources. The +- mask determines which sources are added and which sources are subtracted. This mask contains a + or - character for every connected source. By default, the mask consists of +-es only and all sources are added. To subtract a source, set its corresponding mask character to -. Up to 32 sources can be added or subtracted with a Sum I/O. Have a look here for an example of using the Sum I/O object.

Some examples of +- masks are shown in the table below:

The Multiply/Divide object can be used to multiply or divide the data of different sources. Depending on the */ mask, the input sources can be either in the nominator (default) or the denominator. This mask works similar to the mask of the Sum I/O. For example, a mask of "*//" will result in src1/(src2*src3). A maximum of 32 sources can be used.

A typical application of the Multiply/Divide object is power measurement. When you measure the voltage over a load and the current through it, you can calculate the power by multiplying both measurements.

Some examples of */ masks are shown in the table below:

This processing block can be used to take the absolute value of all samples of its source. The block does not have any options. The ABS operation does the following for every sample:

if sample < 0 then sample := -sample;

This processing block can be used to differentiate data. The output is proportional to rate of change of the input. For example, if a source has the unit Volt, the output of the DIFF will have unit Volt/s. The output range can be changed and fixed to user defined values.

Hint:

The differentiate operation is very sensitive to noise, because noise in most cases has a higher frequency than the signal of interest. To minimize the effect of noise, add a low-pass filter processing block before or after the differentiate block. In case you are measuring a periodic triggered signal, you can also use an average operation, which will give better results than filtering.

The Integrate processing block is the inverse of the Differentiate operation. The output range of the integrate processing block can also be changed and fixed.

An ideal integrator integrates all frequencies in a signal. In practice, unwanted offsets can cause problems with an ideal integrator. Therefore the integrate object contains a leakage parameter. In its menu you can set the Leak frequency. All frequencies below the leak frequency will be suppressed.

Hint:

If you are using acceleration sensors, you can integrate their acceleration signal to obtain the speed. Integration of the speed will give the relative position.

The Duty cycle processing block can be used to determine the duty cycle of a signal. Normally the duty cycle is defined as the ratio between the time that a signal is higher than half the amplitude and the period. It is usually expressed as a percentage.

In some applications, for example in automotive applications, it is more convenient to invert the percentage, such that "low" means active. This can be accomplished by selecting "Type->Inverted" in the popup menu.

Normal	Inverted

By default the mid-level is automatically detected, as halfway between the minimum and the maximum of the input signal. In most applications this will give good results. However, when a signal is noisy or inactive, it can lead to wrong duty cycle detection. To prevent this from happening, it is possible to set the mid-level via the popup menu.

The Resampler processing block can be used to decrease or increase the sample frequency (and record length) of a signal. This can be useful when several signals are sampled with a high sample frequency but not all of them require this high speed. With the resampler, the signal(s) that can be represented with a lower sample frequency, can be resampled to a lower sample frequency.

An example: when using a RPM I/O to determine the speed of an engine, the sample frequency must be around 10 kHz or higher to get the accurate rpms. Once the speed has been determined, it can be resampled to a lower sample frequency, for example 10 Hz, because the speed will vary relatively slow. This decreases the amount a memory ( or file size ) by a factor 1000.

The ratio between output sample frequency and input sample frequency can be entered directly via the resampler's popup menu. It is also possible to enter the output sample frequency in the menu. In that case, the ratio is calculated automatically.

Different methods can be chosen for the resampling process:

• normal: When the ratio is smaller than 1, only one sample of the input data is used for each output sample. When the ratio is greater than 1, several samples in the output data are filled with each input sample.
• linear: When the ratio is smaller than 1, the mean value of several samples of the input data is used for each output sample. When the ratio is greater than 1, the output data is a linear interpolation of the input data.

In the pictures below you can see the effect of different out/in-ratios and methods.

IN	ratio, method	OUT
	→ 1/10, Normal →
100 Samples		10 Samples
	→ 1/10, Linear →
100 Samples		10 Samples
	→ x10, Normal →
10 Samples		100 Samples
	→ x10, Linear →
10 Samples		100 Samples

The SQRT processing block calculates the square root of each sample of the source's data.

Hint:

The SQRT-I/O can be used to calculate RMS values. Perform the following steps: Create a multiply/divide Create a low pass filter Create a SQRT Drag your source onto the multiply/divide twice to calculate squared values of the source's data. Drag the multiply/divide onto the low pass filter to calculate a running mean of the squares. Drag the low pass filter onto the SQRT to get the RMS values. Optionally create a resampler and connect the SQRT to it to reduce the sample frequency.

The Meter sink can be used to view numerical values.

Multiple sources can be connected to the meter and per source, multiple measurements can be displayed. Connecting a source can be done in two ways:

• drag the source onto the Meter in the object tree
• drag the source onto the window of the Meter

The measurements are performed over all post samples of the associated source. To enable and disable measurements, use the context sensitive popup menu. The following measurements are available:

• Maximum
• Minimum
• Top-Bottom
• Root Mean Square (RMS)
• Mean
• Variance
• Standard Deviation
• Frequency
• Crest factor
• Rise time
• Fall time
• dBm
• Total Harmonic Distortion (THD)

The measurement values can be displayed in segment displays (default) as well as gauge displays. You can change the display type through the item Type in the popup menu of each measurement.

The Disk writer sink can be used to store measured data directly to disk. Both 'normal' oscilloscope measurements and streaming measurements can be stored. When streaming measurements are stored, the newly arriving data will be appended to the previous data, forming one large block of data per stream. For more information about recording or logging data to disk, see the page about data logging.

The Disk writer object can store the data in files of the following types:

• Matlab (.MAT) data files (version 6)
• Binary files (.BIN)
• Comma Separated Values (.CSV) ASCII files
• Wave audio files (.WAV)

When the first source is connected to the writer, a settings window as depicted in the figure below will show. You can also make this window appear by clicking Show settings window in the menu of the Disk writer.

With this dialog you can select the file type you want to use. By default, Matlab data files are used. Depending on the file format, you can check "All sources in one file" and "All streams in one file". When "All sources in one file" is checked, the data of all sources connected to the writer are written to one file, otherwise, a separate file is created for each source. When "All streams in one file" is checked, the sequential streams are written to one file, otherwise, a separate file is created for each stream or data block.

File names

Limiting file size

File type options

The I²C analyzer can be used to inspect an I²C bus. Just measure the Clock and Data lines of the I²C bus with a scope and connect the measuring channels to an analyzer sink. The sink uses a window for its output. The output can be saved to a text file.

Clear all text Swap inputs Automatic scroll to bottom Save text to file

Adding an alias for a device address makes it easier to recognize the device adresses. Add address Edit addresses alias Remove selected address Load I²C address file Save I²C address file

The I²C analyzer always needs two sources: the first connected source will be used as I²C SCL (clock) and the second connected source will be used as I²C SDA (data).

Tips for the best result:

I²C supports two different bus voltages: 3.3 and 5 Volt, the bus voltage can be selected through the popup menu. The default bus voltage is 3.3 Volt.

Note: Currently I²C High Speed mode is not supported.

The serial analyzer can be used to monitor a serial bus. It can be used to analyze RS232, RS485, MIDI, DMX or other compatible serial buses. The sink uses a window for its output. The output can be saved to a text file.

Clear all text Automatic scroll to bottom Save text to file

Source: The Default settings will be loaded for each source when it is connected. Using the dropdown you can change the setting of each source individually. Baudrate: Can be set to Auto detect or to a fixed value. Databits: 5, 6, 7 or 8 Parity: None, Odd, Even, Mark or Space Stopbits: 1 or 2 Type: Normal or Inverted. In normal mode all levels above mid level are logic 0 and all levels below mid level are logic 1. Mid level: Auto level or user specified value

The serial analyzer can monitor up to eight sources. All captured data will be displayed in chronological order ¹.

Some tips on using the serial analyzer:

Analyzing serial busses

The serial analyzer can be used to analyze RS485, MIDI or DMX. See table below for settings:

1. Chronological ordering works only for sources which are in sync. This means all sources of one (combined) instrument.
2. The serial analyzer needs at least three times the baudrate to function. For proper function use always a multiple of the baudrate. (e.g. 4 or 5, don't use 3.5 or 4.5)
3. If type is set to normal use rising, if type is set to inverted use falling.
4. If measuring on the data+ of the differential bus use normal, if measuring on data- use inverted.

The sound sink can be used to make data audible. It can play data through one of the installed sound cards. If necessary, the data is resampled to fit the sound card's sample frequency.

One or two sources may be connected to each sound sink. If one source is connected, the data will be played in mono, otherwise in stereo. When playing stereo, the first source connected will be at the left and the second source at the right. By default Wave mapper is used to output the data to. You can select another sound output trough the sink's popup menu.