This is the fifth and final post in a multi-part series on how to make successful measurements, i.e., how to get “good data.” In the first post we made the case that good data is about time, money, performance, results, and reputation. In the second through fourth posts, we explored various aspects of what is required to get good data. The fourth post wrapped up with a comprehensive answer to the subject question, including:
- the acquisition of high-quality fluctuating data;
- the acquisition of high-quality static data;
- the association of metadata with the acquired data that documents how and when the data was acquired, and how to convert it to engineering units; and
- the association of contextual metadata with the acquired data that documents the conditions under which the data was acquired so that the data can be analyzed.
In this post we will look at the IC2 Complete Shear Stress Measurement System software for an example of how a measurement system can be designed to implement the practices that were discussed in the previous posts in this series.
The IC2 Complete Shear Stress Measurement System
The IC2 Complete Shear Stress Measurement System combines IC2 and NI hardware components (sensor systems and data acquisition hardware), along with IC2 custom software, to enable out-of-the-box measurement capability. A primary focus of the system and software development effort was to provide IC2 DirectShear™ sensor product customers with tools to make high-quality wall shear stress measurements. The software is provided free of charge to IC2 DirectShear sensor customers.
It is intended to be used in one of three ways:
- as is, for a turnkey product;
- modified by the customer to fit their unique needs; or
- as an example for how to develop your own custom data acquisition application for wall shear stress measurement.
Since the IC2 Complete Shear Stress Measurement System makes both fluctuating and mean shear stress measurements, it is a good case study for this “Good Data Acquisition” blog series.
A key feature of the IC2 Complete Shear Stress Measurement System is live monitoring. If the application software is running, it is almost always acquiring data. If it is not actively streaming data to a file during a data acquisition event, the data is being streamed to data visibility windows on the host computer screen, enabling the ability to screen sensors for health and determine optimal settings for upcoming acquisition events. When an actual data acquisition event happens, and data is saved to a file, metadata is also saved. Implementations of these capabilities are shown and discussed in the following sections.
Fluctuating Shear Stress Data Acquisition Preparation
As discussed in the second post in this series, live monitoring windows relevant to fluctuating shear stress include an RMS-voltmeter-like display, an oscilloscope-like time series display, a spectrum analyzer-like frequency domain display, and a Probability Density Function (PDF) display.
These displays, as implemented in the IC2 Complete Shear Stress Measurement System, are shown in Figures A, C-E.
These displays are controlled, in part, from a DirectShear Monitor window as shown in Figure B.
The monitor window lets the operator select which displays they want to see and the data channel that they want to view in the selected displays.
It also allows the operator to set monitoring parameters for signal acquisition.
The signal acquisition parameters pertinent to fluctuating shear stress include Sample Rate / Bandwidth, Block Size, and, for each channel, the AC Range setting.
Each individual window also has its own set of controls to customize the display of data within the window.
The time series and frequency domain displays provide sensor health screening capabilities.
All fluctuating measurements are automatically AC coupled so the full range of the analog-to-digital converter (ADC) is available for the measurement.
Finding the optimal range setting is supported by the RMS-voltmeter-like display and the PDF display.
Also note the green Overload indicator on the RMS display that flashes red whenever an overrange condition occurs.
The operator interacts with these displays to establish confidence in sensor health and to optimize sensor range settings prior to a fluctuating shear stress data acquisition event.
Mean Shear Stress Data Acquisition Preparation
As discussed in the third post in this series, a live monitoring window relevant to mean shear stress includes DC voltage meters. This Mean Shear display, as implemented in the IC2 Complete Shear Stress Measurement System, is shown in Figure F.
As with the fluctuating monitor displays, this display is controlled, in part, from the DirectShear Monitor window as shown in Figure B. For mean shear measurements, the monitor window lets the operator specify the Number of PLCs (Power Line Cycles) over which they want to average for each DC reading and, for each channel, the DC Range setting. The Mean Shear window also has its own set of controls to customize the display of data within the window.
The DC meters provide sensor health screening capability as they show a voltage readout for each sensor. The graphic level displays provide a quick way to view multiple sensors and spot any that may be problematic.
The red vs. blue color of the level meter indicates whether the reading is negative or positive which corresponds to flow direction. These meters can also be used, in conjunction with the green DC overload indicator that accompanies each meter, to determine optimal DC range settings prior to a data acquisition event. The overload indicators flash red whenever an overrange condition occurs.
All of the other DC meter capabilities that influence DC measurement accuracy are automatically configured by the software to provide the best possible reading. Only the number of PLCs, DC range, and DC offset nulling (which will be addressed later in this article) need to be handled by the operator.
The operator interacts with these displays to establish confidence in sensor health and to optimize sensor range settings prior to a mean shear stress data acquisition event.
The Data Acquisition Event
Once the operator has taken all the necessary steps described above, they are ready to acquire data. Sensor health has been confirmed and optimal range settings for both the fluctuating (AC) and mean (DC) measurements have been determined. Data acquisition is controlled from the DirectShear Acquisition window shown in Figure G. Here, we see all of the same acquisition parameters that were in the DirectShear Monitor window, but now they apply to a data acquisition event. Number of Blocks is an additional parameter which, when combined with Sample Rate and Block Size, determines the Acquisition Length, that is, how many seconds of fluctuating data will be acquired per channel. An Acquisition Filename and Acquisition Directory are also added so that the acquisition file can be assigned a name and location. Range setting is identical to what was in the DirectShear Monitor window, in fact, the operator may copy the range settings from the monitor window to the acquisition window if they so choose. For the DC measurement, the operator has control over how many PLCs each DC reading is averaged. The software provides feedback regarding how many readings per channel will be made for a given Number of PLCs (during the time period that the fluctuating data is collected).
During a typical acquisition event, for which setup is initiated by pushing the Setup for Acquisition… button, fluctuating and mean shear stress measurements are made simultaneously. The fluctuating data is sampled simultaneously on all input channels for the Acquisition Length specified in the DirectShear Acquisition window. The mean data is measured using a switched Digital Multimeter (DMM) hardware/software architecture. The switched DMM cycles through the channels sequentially, and repeatedly, in parallel with the fluctuating data acquisition. At the end of the acquisition event, the Number of Readings per channel of mean shear stress data will have been captured. All fluctuating and mean shear stress measurement data is stored in a file along with all the necessary metadata to provide traceability for the acquisition event. Traceability was discussed in the fourth post in this series.
Also, notice the DC Offset Measurement block within the DirectShear Acquisition window. This provides a way to make a DC offset measurement. DC offset measurements, as discussed in the third post in this series, provide a way to account for measurement bias that is attributable to causes external to the DC voltage measurement device. For the DC offset measurement, no fluctuating data is acquired, so the Number of Readings per channel within the DC Offset Measurement block needs to be specified by the operator since it will not be determined by the length of the fluctuating data acquisition. Setup for the DC offset measurement is initiated by pushing the Setup for DC Offset… button. DC Offset data is stored in a file with all the necessary metadata to provide traceability for the acquisition event including a tag indicating that it is a DC offset measurement.
This implementation uses the “minimalist approach” for contextual metadata that was discussed in the fourth post in this series. Specifically, the approach that can be used with this implementation to associate acquired data with other data that provides context for the acquired data, is to use a file naming convention where a unique file name is used to uniquely associate the acquisition event with other relevant data/information. This allows the shear stress data acquisition operator to focus on the immediate task of acquiring good data without being distracted from that task by the demands associated with contextual metadata acquisition/entry.
This use case demonstrates an approach to implementing data acquisition system software that supports all of the principles that were discussed in the previous posts in this series. Hence, this concludes the series on how to make successful measurements with the hope that it helps our readers be more successful in their data acquisition endeavors. Thank you for reading “Good Data Acquisition: How do you know you are getting good data?” and please comment below or contact us at firstname.lastname@example.org if you have any questions!