This article will take an in-depth look at data acquisition systems.
The article will bring more information to topics such as:
This chapter will discuss what data acquisition systems are, their components, and their measurements.
A data acquisition system is a system that comprises sensors, measurement devices, and a computer. A data acquisition system is used for processing acquired data, which involves collecting the information required to understand electrical or physical phenomena.
This information is required for understanding how a data acquisition system performs. As an example, a data acquisition system can be used when testing the temperature of a heating coil used for heating an object to a specific temperature. The level of success of the heating coil is understood by measuring its temperature. That simple task of measuring and recording temperature is called data acquisition and is achieved using a data acquisition system. Another example where a data acquisition system comes into play is when measuring and recording the potential difference in current flow across an electrical resistor.
The reason for measuring and recording the electrical and physical phenomena using a data acquisition system is to enable further analysis. A data acquisition system uses software to perform its functions and it is capable of quickly processing and storing data in many ways. Data acquisition systems can capture data from an actual system and store the data in a simple format that is easily retrievable for further engineering or scientific review.
Data acquisition systems are either handheld, or they can be remotely operated. Handheld data acquisition systems are used when there is a requirement for taking readings of a specimen which can be physically interacted with. When direct human interaction with an object is not possible or necessary, this is when remote data acquisition systems are used to take remote DAQ (data acquisition) measurements.
The physical phenomena or physical characteristics to be measured comes first in the data collecting process. Temperature, light intensity, vibration, gas pressure, fluid movement, and force are a few examples of factors often considered in a DAQ system. No matter what kind of physical property has to be measured, the physical state must first be unified into a form that a data acquisition system can sample.
These alterations are carried out by sensors. An ensemble of software and hardware known as a data acquisition system enables the measurement or control of physical properties of objects in the real world. A full data acquisition system consists of DAQ hardware, sensors, actuators, signal conditioning gear, and a computer running DAQ software. Furthermore, an independent timing system must be used if timing is important (for example, in event mode DAQ systems).
Sensors or transducers serve the purpose of interacting with the subject measured. They interact with the subject either directly or indirectly, or as defined in other words, contact or non-contact. These tools convert the physical values to produce an output of electrical signals. There are many different types of sensors that are utilized in data acquisition systems depending on the nature of their application. For instance, when the temperature is being measured, a temperature sensor is used, but when measuring light, a photovoltaic sensor is used.
These tools both have a common function of converting analog signals like temperatures, light, speed, etc. into digital signals that are compatible with a computer. The sensors utilized by DAQ systems are high-quality sensors that are capable of giving accurate readings with minimal or no noise.
The electrical signals obtained from the sensors may contain noise or other interference and need modification; they could not be used directly as is. The signals might also be weak to a point where the data acquisition system cannot measure them. Hence additional circuitry is utilized for optimizing the signals. This additional circuitry is known as a signal conditioner. Signal conditioning then is the process of optimizing the signals.
The signal conditioner makes use of filter circuits for separating the noise from the real signal and utilizes an amplification circuit for strengthening weak signals. These are two of the most common functions that are served by the transmission or signal conditioners. A suitable signal conditioning circuit can achieve additional processes like linearization, calibration, and excitation. The selection of the signal conditioning circuit is largely dependent on the characteristics of the sensors employed in the DAQ system.
Data acquisition hardware is the hardware that is connected between the sensors and the computer. This hardware is either connected to the computer employing a USB port or through the PCI-express ports that are found on the motherboard. The data acquisition hardware serves to take in the signals from the sensors and then convert them into digital signals that are readable by the computer. This is the function that DAQ hardware performs.
This component of the DAQ system serves to convert analog signals into digital signals. This component is at the core of all data acquisition systems. This chip serves to take data from the environment and convert it into separate levels that can be interpreted by a processor. These distinct levels correspond to the smallest detectable change that can be found in the measured signal.
The higher the number of bits of an analog to digital converter, the greater the number of discrete levels that can be used for representing an analog signal, and the greater the resolution of the analog to the digital converter. The resolution of an analog to digital converter is essentially comparable to the marks that are found on a measuring stick.
Using a metric measuring stick, a measuring stick that has mm marks has greater resolution than that with only cm marks; here in the United States, a yardstick featuring the specific inches would show greater resolution than one only broken down by individual feet. The need for mm or cm depends on what is being measured – the same is true for analog to digital converter resolution.
The function of this component of a DAQ system is to provide support for inputting, as well as outputting, binary signals.
This component has the function of providing support for taking input from single-ended wires.
Some types of DAQ hardware are standalone, capable of operating on their own without the requirement of a connection to a computer. This is possible through the use of a processor as well as a computing unit that is embedded within the hardware of the data acquisition system. Standalone data acquisition hardware is capable of helping users with real-time data representation. Prime examples of DAQ systems that can work without a computer are standalone oscilloscopes, as well as other data logger devices used to measure specific information.
The sampling rate, known as the frequency or F, is determined by the nature of the process being monitored and common sense. With digital data acquisition, transducers output signals to be digitized by a computer. Unfortunately, a computer is unable to store continuous analog time waveforms and breaks the signals into samples that are stored. In essence, the sampling rate or sampling frequency is the number of samples per unit of time taken from a continuous signal, which can be measured in hertz.
An aspect of data acquisition that can influence the interpretation of a trend is the sampling rate. If the sampling rate is too slow, important trends may be missed or hidden. Years ago, the excuse was that a computer did not have enough disk space or memory, which is not applicable to modern day computers.
An understanding of sampling rates is essential to an understanding of data acquisition. In many cases, clients want fast sampling rates when they are doing short term testing. More accurate interpretations of data can be acquired through long term examinations of processes with sampling rates of a second or less with data storage taking several forms depending on the needs of the client.
The computer is the end piece of a DAQ chain. The computer’s function is to gather all data that comes through the DAQ hardware for further analysis. However, it is not enough to simply connect the DAQ hardware to a computer in order to make sense of the data collected. DAQ software that uses data from the DAQ hardware is still required for creating readable and meaningful results. This data acquisition software acts as the layer between the DAQ hardware and the user. With the data that is collected from the DAQ, computers are critical to performing higher-order computations.
This chapter will discuss the measurements, modules and methods used in data acquisition systems.
Data acquisition systems are capable of making many different types of measurements. These types of measurements are typically derived from analog signals. Before their transfer into any computer system, they must be in a digital format.
Many different parameters can be measured using a data acquisition system including the following:
Separate modules or sensors may be utilized for measuring different, specific parameters, although several multi-input, general-purpose data acquisition devices can interface to these various sensors. The types of sensors that are utilized in data acquisition measurements usually return values of voltage in particular since these readings can be converted into measurements of temperature, displacement, or anything that is being studied.
Often a data acquisition module, as well as a sensor, will make use of a transducer of some kind in order to create a base measurement parameter- like voltage. This measurement is known as the primary measurement. It will then be converted into subsequent parameters as required. In this way, data acquisition modules are capable of measuring almost any required parameters which may need to be made or obtained.
As a result, the vast array of DAQ modules which exist are capable of measuring almost anything possible. Additionally, they can meet very specific requirements. However, sensor designs requiring special DAS modules can also be obtained. In this way, the customization of these data acquisition modules for specific measurements with specific sensors can still be made.
Many data acquisition systems have rack modules that are filled with cards for providing the different measurement functions that are needed. These cards obviously must conform to the overall system that is utilized in both electrical and mechanical interfaces. The rack systems used are often standardized and the modules employed are often available from many manufacturers, thereby making their selection more convenient.
Specialized data acquisition software required for acquiring, storing, and processing data in a logical format is available. Software used in data acquisition systems can be written in various languages and can be written for a specific application in mind. Alternatively, there are many different data acquisition software packages available that can be utilized instead.
The benefit of proprietary data acquisition software packages is that all of the development has already been undertaken and the system has already been deployed; therefore, most problems have already been encountered. Even though a charge for the software maintenance is applicable, this will be considerably less than trying to do maintenance on a similar home-grown data acquisition software package.
Accordingly, most companies choose to buy their data acquisition software and then utilize this in developing tests for their own particular use.
Transducers are the electronic devices that change energy from a particular source into an electronic signal. Depending on the specific variable that the DAQ system is designed to measure, the output signal varies. Data acquisition systems are usually discussed in terms of the output signal they generate. The output signal generated may be digital or analog.
Some of the data acquisition techniques include:
This is a data acquisition method used in some very specific data acquisition systems. This method is mostly utilized by forensic investigators. It is a flexible method of data acquisition, and it allows the creation of one or more copies of an original drive. More importantly, it also copies everything from the original drive, including interconnected sectors or clusters, in order to retrieve files that were subsequently deleted or tampered with. Some popular tools used for reading the disk-to-image files include EnCase, X-Ways, FTK, ILook Investigator, etc.
Sometimes, when the creation of a bit-stream disk-to-image file is not possible due to software or hardware errors or other incompatibilities, a bit-stream disk-to-disk method is used instead. When investigators face such issues mentioned above while they try to acquire data from older drives, they create a bit-stream disk-to-disk copy of the original drive or disk. The tools that are used to create the disk-to-disk bit-stream copy of an original tampered drive include EnCase, SafeBack, as well as Norton Ghost. These tools are capable of modifying the target disk’s geometry for matching the data copied from the original suspect drive.
This method is used for gathering only the files that are required for an individual case investigation. For example, the collection of Outlook .ost or .pst files in email investigations, and the collection of specific records from a large RAID server would be utilized through this procedure.
This method is similar to logical acquisition. With this method, investigators are capable of collecting fragments of unallocated data. This method is mostly used when there is no necessity of inspecting the whole drive.
Some of the considerations when setting up data acquisition systems include:
Prior to anything else, you must be certain of how long you want the system to operate without interruption. The choice of hardware and operating system will be significantly influenced by this period of time. Additionally, there is a great likelihood that the data flow may become backed up, along with subsequent errors resulting, due to buffer overflow if the processor is under stress from having to keep up with the tasks continually. The system's hard drive and battery will begin to wear down, eventually stopping after a decade or sooner. Therefore, the first factor to take into account when considering a DAQ system is the length of time you’ll want the system to operate. Only then, will you be able to move on to consider the other things you’ll need to think about (as listed below) when choosing the best option for your needs.
The power source is the next item to think about. You must determine if the system will have access to a reliable power supply or if the DAQ system will require a secondary power source. Choosing a secondary source is obviously less of an issue the more reliable the primary power source may be. Some common back-up power sources include generators, batteries or solar panels. Where multiple, reliable energy sources are available, performing power calculations is advisable; when doing so, it is best to be cautious and monitor power when working under actual conditions.
The transfer of data from the system should be taken into account next. You must determine if the data collection system requires local data storage or remote data transmission of data from the field or the facility. Additionally, you must choose the system based on how much storage you will need. Furthermore, you must decide if you want the system to still have the ability to store and forward data in order to buffer the collected data while the link is unavailable, and continue sending when it becomes accessible.
You must be explicit when setting up a data acquisition system on whether you will require remote access before you configure the system or determine if it is functioning properly. In today’s work-from-home environment, it is advisable to build up a system for data collection that can be accessible from a distance. Additionally, it is possible that you may require access to the system in order to change the system's acquisition parameters itself.
When setting up a data acquisition system, you must decide in advance whether you merely need to gather raw data or whether you need to treat the data in a certain way after the acquisition process. When choosing the best data collecting system, this issue must be taken into account. A straightforward system would be enough if all you needed to do was collect data from the process. However, a CPU would be necessary in the system if you needed it to execute some specialized functions, such as filtering, Windowing, and other operations.
Finally, you must examine your input channel. You must be certain of the effectiveness of your input channel. The main elements to take into account in this case are the sample rates, the data to be obtained from the signals, the synchronization of signals, and the range of signals considered. Taking into account each of these aspects will help you select the best data collecting system for your needs.
This chapter will discuss the different types of data acquisition systems and data acquisition signals.
The types of data acquisition systems include:
Data logging is the process whereby collected data is recorded. This data is collected over a defined amount of time. data loggers tend to be small and they are mostly used for the measurement of relatively small signals. Many of these data acquisition systems are intended for the collection of data over a long period of time.
Depending on the type of application, the data can be used to read voltages, temperature measurements, humidity levels, currents, or other signals of interest. Data loggers are self-contained data acquisition systems with built-in processors and predefined software embedded in the unit.
A data logger is capable of running as a standalone device. Data loggers are popular due to their portability as well as ease of use for specific tasks. Every data logger consists of local storage capacity for saving data. Some data loggers include SD (secure digital) slots as a means for providing additional memory through the utilization of memory cards (featuring memory chips). The data may be collected and temporarily stored on an individual data logger and then sent via a data link ( a removable memory card) at regular, convenient intervals. Some web-enabled data loggers can even be configured to directly share their data over a network.
Some data loggers are battery-powered for additional portability. By definition, a data logger will consist of a more limited set of inputs and tend to have a more basic format like the already mentioned signals including temperature, current, voltage, etc. Data loggers can also be used for the collection of geological data for long-term monitoring of many items.
Data acquisition devices contain signal conditioning circuitry, as well as an analog-to-digital converter. However, they need to be connected to a computer in order to function. Data acquisition devices are a popular choice because they are very flexible and very useful in various applications. Data acquisition devices are DAQ systems that are more complex than data logging systems. However, they do not have the complexity of a full rack-based DAQ system. Data acquisition devices are likely to utilize single devices to which all the sensors can be connected into a full DAQ system.
Data acquisition devices are capable of providing more functionality than data loggers and they are less costly than full rack-based systems. Most of these items are USB data acquisition systems. There are plug-in devices that are used in data acquisition. Users of these devices can either use predefined data acquisition software such as DAQami, or they can also make use of a programming environment like C++, MATLAB, Python, and DASYLab. Data acquisition devices offer a customizable solution for unique applications, with different BUS options as well as the flexibility to function as a part of a larger DAS system.
Modular data acquisition systems are designed for high-channel count devices offering many input channels, as well as complex systems that require integration and synchronization of many types of sensors. These systems are utilized in more demanding situations. The integration and use of these systems are more complex, but they are extremely flexible. These modular systems are the most expensive data acquisition option. However, based on the complex functions performed, many DAQ systems contain features that can only be provided by a modular data acquisition system like PXI.
Both static, as well as dynamic measurements, can be performed by these DAQ systems; therefore, they are capable of both low-speed and high-speed sampling.
Modular data acquisition systems usually have a high-powered computer associated with them due to the demands that are placed on them. The computer associated with these systems is either built-in or connected to them. In this way, data acquisition systems offer maximum as well as flexible performance, but this comes with an additional cost. Modular data acquisition systems can come in larger racks although many compact DAQ systems are also available.
Some of the data acquisition techniques include:
The voltage signal is the most commonly used signal employed by DAQ systems. Strain gauge bridge circuits, thermocouples, and gas concentration probes, for example, all produce a voltage signal. Data acquisition hardware conditions the signal and then converts it into a digital number by employing an analog-to-digital converter. This digital value is stored by the computer. Data acquisition systems are often able to directly handle low-voltage inputs that are, to say, a few millivolts up to a few volts.
Current is usually used for transmitting signals in noisy environments since it is much less affected by environmental background noise. A data acquisition system measures the amount of current that flows and then stores the value in a computer for analysis.
Signals from electrical power supplies can be monitored when the current signal is sensed with a current-sensing resistor, and resistive dividers are used to break down high voltage signals. The current-sensing resistor will provide data to the data acquisition system for measurement and storage so that the power signals can be monitored.
Rather, the voltage depends on the difference in temperature between its two wires (made of two different metals) collected at the thermocouple junction (where the wires meet) and the temperature of the cold junction (the point where the thermocouple wires terminate).
These sensors provide a low voltage signal that is typically a few millivolts. The relationship between the voltage and the temperature is non-linear.
The accuracy of the thermocouple will vary according to the type of thermocouple being used.
Resistance measurements are performed employing a current source together with a normal voltage input. The current flows through an unknown resistance and the voltage drop across that resistance is measured. This voltage drop is then recorded by the data acquisition system.
These bridges provide a special case of resistance measurement. Strain gauge bridges operate on the principle of electrical conductance and its dependence on the geometry of the conductor. A Wheatstone bridge arrangement is utilized for measuring the resistance of the gauge, which will vary as the gauge is distorted by an applied strain. They measure the small differences between a Wheatstone bridge’s two circuits.
Consequently, the measurement of strain is often concerned with the measurement of deviations from the initial values, instead of absolute measurements. The initial values therefore must be known. These may be sufficiently larger than the subsequent changes that occur in the bridge imbalance caused by imposed strain. Therefore an analog to digital converter with high resolution is employed to give the dynamic signal range that is required.
Digital outputs produced by switches and so on are treated as logic signals. These signals are sensed as on(1) or off(0). For volt-free contacts, where there is no switching of external voltage, a small sensing voltage is applied for determining the switch state. This will usually be 5V to be compatible with TTL levels. Where voltage is being switched, the logic state can be determined by the voltage level itself. The type of input required is determined by the voltage levels, for example, TTL, up to 12 V logic or 24 V DC. When the digital signals are rapidly changing and become pulse trains, counter-timer type inputs must be considered.
This chapter will discuss the applications and benefits of data acquisition systems.
These include:
Data acquisition systems are utilized in the electronics industry. They are utilized in the testing of many variables that are involved in the design of electronics like heat production, resistance, conductivity, magnetics, etc.
Data acquisition devices are utilized in automotive manufacturing for testing the quality of the parts that are manufactured.
Data acquisition systems are used for the quality testing of imaging equipment like a photographic lens or video camera, as well as with scientific equipment such as scanners, and microscopes.
Data acquisition systems are utilized in laser technology to test laser performance, light intensity, and color
.Data acquisition systems use remote sensing technologies within radar and sonar applications to calculate their efficiency and effectiveness.
Industrial machines are created to perform multiple times. Therefore, repeatability is of critical importance. Data acquisition systems are often utilized for testing these machines for their tolerance to repetitive forces.
Data acquisition systems are utilized in the non-destructive testing of structures, geology, seismology, ultrasonic measurements, as well as with the analysis of acoustic emission phenomena.
Gas detectors are used to find leaks using tracer gases, such hydrogen and helium. Once a chamber is filled with the trace gas, the loss of gas is measured with a mass spectrometer that detects the trace gas. Gas detection is used to determine the amount and composition of the gas being lost from a system or machine.
The advantages of data acquisition systems include:
Data acquisition systems maximize the absolute accuracy of measurements.
Data acquisition systems make it possible to build mixed-measurement systems that are tailored to specific needs.
There are a variety of hardware options available ranging from processing just limited data to the control of multiple data acquisition systems coordinated to be part of one synchronized application.
Data acquisition systems are utilized in many important facilities around the world for the monitoring of vital parameters. The information that is collected by data acquisition systems is used for enhancing efficiency, ensuring reliability, as well as making sure that the machinery is safely operating.
display measurements without delay. This is an advantage to technicians since it helps them intervene faster if there are any problems encountered and make any necessary repairs to ensure optimal performance in no time.
Top data acquisition systems make it possible for companies to make a reduction in data duplication and adopt technology while making it simpler to analyze the obtained information. These solutions make it possible for the employees to work without having disturbances that may hamper their productivity.
Data acquisition systems allow the automation of data entry processes that were previously done manually. Automation reduces mistakes by eliminating human error as well as providing additional time for staff to perform other duties..
If fewer programs are interfering in a work process, the process becomes more agile. Data acquisition systems ensure total comprehensiveness of information. They also ensure the correctness of the information without having to depend on other types of applications.
Data acquisition systems make it possible for users to access the database, as well as recover information for processing and analysis.
With a data acquisition system, there can be tracking and monitoring of a company’s various procedures in order to identify problems and resolve issues quicker.
Since the process of capturing data is now automated and objective, the human factor has been eliminated. Therefore, the security risks that are associated with data storage, analysis, and management are thereby reduced.
Since the entry of data is faster, the required space takes up less memory, and this information can be recovered without any delay through DAQ systems, work processes become more cost-effective.
Data acquisition systems are capable of confirming that a system is meeting the design specifications so that a product meets the needs of the user. Furthermore, these systems provide testing capabilities to see whether a product has the required quality prior to production. They also provide a means to analyze those products that are defective.
Data acquisition systems are available as multi-purpose devices. They can have an all-in-one configuration with multiple measuring modes that are capable of measuring multiple properties. They can also be single-purpose devices that will only measure a single property.
The data that is collected through a data acquisition system is stored on a computer where it can be analyzed or processed based on the convenience of the user. Also, any additional transfer of data to other devices that may be required is made easier through a computer.
Data acquisition systems allow one to obtain valuable information without bias for improving the performance of a company and for increasing their economic well-being.
Data acquisition systems offer greater control over the processes of an organization as well as a quicker response to any failure that might occur. Data acquisition systems not only work to improve and maximize an organization’s efficiency, they also work to maximize the quality of their products and services.
Data acquisition systems are a process for capturing, storing, analyzing, and manipulating data. The data is acquired through different techniques including voltage signals, current signals, power signals, etc. There are different types of data acquisition systems utilized. Some of them are multipurpose devices with an all-in-one configuration whereas some are single-purpose devices designed for measuring data from single parameters. Data acquisition systems can be applied in a wide variety of industries including the automobile industry, the electronics industry, laser technology, etc. These systems offer so many benefits. They are cost-effective, fast, versatile, and reliable. Data acquisition systems are a very efficient and convenient way of recording data for further analysis. Data acquisition systems not only improve data security since the process of capturing data is now automated, they improve access to data for the users while reducing errors.
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