Data logging is the process of gathering data from a device or system, often through use of a computer. Data acquisition (DAQ) is the process of collecting data from one or more devices and systems, as well as storing and analyzing it.
While data logging and DAQ are very similar, the differences can be seen in their respective goals. Data logging is aimed at storing data while DAQ focuses on processing it. Data logging involves recording raw data from individual instruments or components and storing it in one place for later analysis; DAQ involves collecting and analyzing real-time data from multiple sources in order to make decisions about how best to proceed with a given task.
Data logging is typically used for recording data from one or more instruments or components, such as temperature and pressure sensors. The data is stored for later analysis by a computer system, allowing users to review it at their discretion. Data acquisition is used to collect real-time data from multiple sources in order to make decisions about how best to proceed with a given task.
Data Loggers are designed to measure signals over a long period of time. They take measurements over a period of days, weeks, or even months. They are installed in a fixed location where they work for these extended periods, writing data to internal RAM or to removable data storage. A data logging system consists of a discrete number of inputs, such as voltage, current, temperature, and perhaps one other type of signal. While a data logger is one of many types of data acquisition devices, the data logger by itself cannot be classified as a data acquisition system.
The application of data logging is best exemplified in the standalone data logger device. Take, for example the AR-200 data logger (EX 1). The AR-200, with its sibling the AR-400 with 4 channels, is a discrete device designed to measure and log one type of data, as part of a smaller-scale ready to run solution. A data logger like this one is designed as a complete solution for measuring one type of input. In this case, the AR-200 grabs accelerometer input from machinery on a factory line and stores the readings on an SD card for later use. This kind of data logger allows the operators to upload data, or physically remove the SD card, as needed without requiring dedicated DAQ hardware and software. The data logger provides different trigger modes so that a user can specify start/stop time, and duration of data collection, based on their needs. Contrast this device to an “always on” data acquisition system that performs more of a supervisory function.
Data loggers are often used in conjunction with a data acquisition system. A typical DAQ system can provide the user with a graphical interface that allows them to monitor their measurements in real- time or over time. Some DAQ devices will also store the information they collect so that it can be analyzed later on.
The types of data acquisition systems vary depending on the type of data being collected, as you might have imagined by now, DAQ systems tend to be larger-scale, comprehensive systems that may or may not include data loggers as one part of the larger whole. An example DAQ system (EX 2) usually combines multiple input types into one passive monitoring system.
This example shows a monitoring system for a large beverage plant. On the bottom of the diagram, you can see three different types of temperature sensor: each is connected to one data acquisition module. DAQ modules serve a similar purpose to the DAQ system that the data logger does to its system. DAQ modules, and this is the crucial difference, usually don’t store data on their own. These devices capture data directly from the sensors and translate it into a machine-readable format. In this case, the temperature input modules are capturing the sensor data and encoding it as Modbus values for transmission over the RS-485 network. You will also notice that the DAQ system typically makes use of more devices that act as intermediaries between the data collecting device and the users. In this case, the example uses WISE IIoT edge controllers to provide local control, alarm functions, and to relay the captured data to the control system. At the highest level, the DAQ system will often make use of IoT software or SCADA software to control the entire system, store historical data, and view live incoming data.
While there remain many similarities between data loggers and data acquisition systems, the key operating features presented above are the generally understood differences. These differences are usually defined by the application space in which the devices are used. The needs of your application will usually dictate which type of solution is the best fit.
A larger, more complex system that integrates with control software and IIoT platforms may be required for a large factory, power plant, or multi-story building. The diagram pictured below shows an example of a more complex DAQ, control and monitoring system in place at a facility that stores renewable energy. This system is much more spread out, both figuratively and geographically, than the previous examples.
The system makes use of multiple field level control systems that, if taken in isolation, could be called data logging systems. Each little network takes power readings from the battery cells and stores them on a local controller. The local controller logs data and provides emergency shutdown automation at the level of each battery bank while also providing an interface to the cabinet management platform. The cabinet management platform, in turn, provides local control and data acquisition for multiple battery banks while providing an interface to the overall control network through a cloud platform. The actual control center is located miles away from the site of the battery banks, but operators can access both real time and historical data from almost anywhere using their cloud server.
At the scale of this example, it should be clear why the term “data logging” wouldn’t be a proper fit. A data acquisition system of this scale has a much broader scope of function. It collects different types of data, stores it in multiple locations, provides control and automation functions, and then makes the data accessible to the user’s cloud platform.
There is, of course, a wide gray area in the middle between data logging and data acquisition, where both terms may apply. It’s important, then, to consider the specific needs of the application. In many cases, it will be clear which device or devices are needed. As a rule of thumb: if you need real-time monitoring or analysis over time, a data acquisition system will likely be required; if immediate measurements are needed, or if it’s a smaller application, then a standalone data logger is what’s required.
