A data acquisition system typically consists of five components:

1. Sensors or transducers: These are devices that convert a physical parameter, such as temperature or pressure, into an electrical signal that can be measured and processed
2. Signal conditioning circuitry: This circuitry is used to amplify, filter, and/or shape the signals from the sensors so that they can be accurately measured by the data acquisition system.
3. Analog-to-digital converter (ADC): The ADC is used to convert the analog signals from the sensors into digital values that can be read by a computer or other data logging device.
4. Data acquisition (logging) hardware: This is the hardware that collects the digital data from the ADC’s.  It often involves concepts like system bus (supporting modularity), synchronization, triggering, recording, storage and even pre-processing. The data logging hardware will typically connect and interface to a computer or server to deliver the data for subsequent visualization, storage, and post-processing. However, DAQ systems can also operate in self-contained and autonomous stand-alone mode without continuous connection to a PC.  
5. Software: The data acquisition software is used to control the data acquisition hardware, collect, and store data, analyze, and display the measurement results in a way easily perceivable and intuitively understandable for the user.

A data acquisition system can measure a wide range of electrical and physical phenomena, depending on the field of application. DAQ systems that focus on electromechanical systems, which represents a large and important market segment would typically cover quantities like: 

• Voltage 
• Current 
• Temperature 
• Strain 
• Flow 
• Pressure 
• Acceleration and vibration 
• Sound pressure and noise 
• Displacement 
• RPM, angle 
• Resistance 
• Humidity  

To measure these physical quantities a sensor or transducer is required, that converts the primary physical quantities to an electrical signal, that is suitable for technical processing. Depending on the specific transducer, these analog electrical signals will require, certain analog signal conditioning: This can involve amplification of small and sensitive signal levels, filtering, and diverse circuitry and provisions for adaptation. 

An analog-to-digital converter (ADC) is used to convert analog signals into digital data in a data acquisition system. An ADC works by sampling the analog signal at regular intervals and converting each sample into a digital representation, typically in the form of a binary number. 

The ADC converts the analog signal into digital data by performing the following steps:

1. Sampling: The analog signal is sampled at regular intervals, typically using a clock signal to synchronize the sampling process.
2. Quantization: The sampled analog signal is quantized, or divided into discrete levels, based on the resolution of the ADC.
3. Encoding: Each quantized level is assigned a digital code, typically in the form of a binary number.
4. Conversion: The analog signal is converted into a digital signal by encoding each sample as a digital code.

The digital data produced by the ADC can then be read and processed by a computer or other data logging device.

The primary purpose of a data acquisition system is to provide accurate and reliable data that can be used to optimize processes and make informed decisions in a variety of applications. 

• Data collection and storing: A data acquisition system is used to collect and measure data from various sources, such as sensors or transducers, and convert it into a form that can be processed, analyzed, and stored by a computer.
• Data visualization: A data acquisition system can stream the data to a connected display or PC to enable real-time visualization of the data e.g. in a monitoring application. Alternatively, the recorded data can be post-visualized using data visualization software like the imc FAMOS Reader.
• Data analysis: A data acquisition system can analyze collected data in real-time or offline to detect trends, identify patterns, and provide insights that can be used to optimize processes or make informed decisions.
• Data for real-time control: The data from data acquisition systems are often also required as input signals for real-time control and closed-loop control in processes or test bench applications. The control can be done on a separate control system like a PLC, or integrated into the DAQ system - as it is common with imc for example with the imc CRONOScompact system.

Typical Application Fields: 

• Process control: A data acquisition system can be used to monitor and control industrial processes, such as refining oil or generating electricity, to optimize efficiency and safety.
• Quality control: A data acquisition system can be used to test and evaluate the performance of products to ensure that they meet specified standards.
• Research: A data acquisition system can be used to measure and record data from experiments, allowing researchers to analyze and understand complex phenomena.
• Development: A data acquisition system can be used to measure data on newly developed components, assemblies, and prototypes to identify weaknesses and ensure safety and comfort before the new product is released to the market.

Sensors and transducers are devices that are used to measure physical quantities, such as temperature, pressure, strain, or light intensity, and convert them into an electrical signal that can be measured and processed by a data acquisition system. There are many different types of sensors and transducers, each designed to measure a specific physical quantity.

• Thermocouples: A thermocouple is a type of sensor that is used to measure temperature. It consists of two wires made of different metals that are joined at one end. When the junction between the two wires is heated, a voltage is produced that is proportional to the temperature. The voltage produced by the thermocouple can be measured and used to determine the temperature.
• Thermistors: A thermistor is a type of sensor that is used to measure temperature. It consists of a semiconductor material that has a resistance that is sensitive to temperature. When the temperature of the thermistor changes, the resistance of the material also changes. This change in resistance can be measured and used to determine the temperature.
• Resistance temperature detectors (RTDs): An RTD is a type of sensor that is used to measure temperature. It consists of a wire that is made of a material whose resistance is sensitive to temperature. When the temperature of the RTD changes, the resistance of the wire also changes. This change in resistance can be measured and used to accurately determine the temperature.
• Strain gauges: A strain gauge is a type of transducer that is used to measure strain, force, or pressure. It consists of a thin wire or foil that is attached to a flexible backing. When a force is applied to the strain gauge, the wire or foil deforms, causing a change in electrical resistance. This change in resistance can be measured and used to determine the magnitude and direction of the applied force.
• Load cells: A load cell is a type of transducer that is used to measure force or weight. It consists of a small metal structure that deforms when a force is applied, causing a change in electrical resistance. The change in resistance can be measured and used to determine the magnitude of the applied force. Load cells are commonly used in data acquisition systems to measure weight, force, or pressure.
• LVDT sensors: An LVDT (Linear Variable Differential Transformer) sensor is a type of transducer that is used to measure linear displacement or position. It consists of a core that is surrounded by two primary windings and a secondary winding. When the core is moved, the magnetic field produced by the primary windings changes, causing a voltage to be induced in the secondary winding. The magnitude of the induced voltage is proportional to the displacement of the core and can be measured and used to determine the position of the core.
• Accelerometers: An accelerometer is a type of sensor that is used to measure acceleration or vibration. It consists of a mass that is suspended on a spring or flexure and is connected to a sensing element, such as a piezoelectric crystal or a capacitive plate. When the accelerometer is subjected to acceleration, the mass moves, causing a change in the electrical properties of the sensing element. This change in electrical properties can be measured and used to determine the acceleration of the accelerometer.
• Microphones: A microphone is a type of transducer that is used to measure sound pressure or sound intensity. It consists of a diaphragm that is attached to a coil of wire or a piezoelectric element. When sound waves impinge on the diaphragm, it vibrates, causing a change in the electrical properties of the coil or piezoelectric element. This change in electrical properties can be measured and used to determine the sound pressure at the microphone.
• Current transducers: A current transducer is a type of transducer that is used to measure electrical current. It consists of a sensor that is inserted in the circuit and is used to measure the magnetic field produced by the current. The magnitude of the magnetic field is proportional to the current and can be measured and used to determine the current flowing in the circuit.

Signal conditioners (also known as measuring amplifiers) are used in a data acquisition system to amplify, filter, and/or shape the signals from sensors or transducers so that they can be accurately measured by the data acquisition system. They are typically used to improve the signal-to-noise ratio of the signals, making them easier to measure and interpret. 

There are many different types of signal conditioners, each designed to perform a specific function. For example, an amplifier can be used to amplify weak signals from sensors to make them more visible to the data acquisition system. A filter can be used to remove noise or unwanted frequency components from the signals, improving the signal-to-noise ratio. A pulse shaping circuit can be used to shape the pulses from sensors into a specific format, such as a square wave or a pulse train, making them easier to measure and interpret.

There are several types of filtering that can be used in a data acquisition system to remove noise or unwanted frequency components from the signals being measured: 

• Low-pass filtering: This type of filter removes high frequency components from the signals, allowing low frequency components to pass through. It is commonly used to remove noise or eliminate high frequency oscillations from the signals.
• High-pass filtering: This type of filter removes low frequency components from the signals, allowing high frequency components to pass through. It is commonly used to remove DC offsets or baseline drift from the signals.
• Band-pass filtering: This type of filter allows a specific range of frequencies to pass through, while removing frequencies outside of this range. It is commonly used to isolate a specific frequency or frequency range from the signals.
• Band-stop filtering: This type of filter removes a specific range of frequencies from the signals, while allowing frequencies outside of this range to pass through. It is commonly used to eliminate specific frequency components from the signals.
• Digital filtering: This type of filtering uses digital signal processing techniques to remove noise or unwanted frequency components from the signals. It can be implemented in software or hardware and is commonly used to improve the signal-to-noise ratio of the signals.
• Anti-aliasing filtering: This type of filtering prevents aliasing, or the distortion of signals that occurs when the sampling rate is insufficient to accurately represent the signals being measured. Aliasing can cause errors in the measurement of the signals and can make it difficult to accurately interpret the data.

The type of filtering used in a data acquisition system depends on the specific requirements of the application and the characteristics of the signals being measured.

he purpose of Analog-to-Digital Converters (ADCs or AD Converters) in a data acquisition system is to convert analog signals, such as voltage or current, into digital values that can be read and processed by a computer or other data logging device. ADCs are an essential part of a data acquisition system, as they allow the system to measure and record analog signals and convert them into a form that can be easily analyzed and understood. 

ADCs work by sampling the analog signals at regular intervals and converting each sample into a digital representation, typically in the form of a binary number. The resolution of the ADC, which is typically measured in bits, determines the number of possible digital values that can be produced and, therefore, the accuracy of the conversion. For example, an ADC with a resolution of 8 bits can produce 256 possible digital values (2^8), while an ADC with a resolution of 16 bits can produce 65,536 possible digital values (2^16), while an ADC with a resolution of 24 bits can produce 16,777,216 possible digital values (2^24). 

Overall, the purpose of ADCs in a data acquisition system is to provide accurate and reliable digital data that can be used to analyze and understand complex analog signals.

Data storage is an important aspect of a data acquisition system, as it allows the system to retain the data collected over a period of time, even when the system is not actively collecting data. This is important because it allows the data to be analyzed and understood at a later time, providing valuable insights that can be used to optimize processes or make informed decisions. 

Data storage is also important because it allows the data to be accessed and analyzed from multiple locations, making it easier to share the data with others or collaborate on data analysis. This is especially important in industries where data is collected from multiple sources or where data analysis is performed by a team of people. 

There are many different ways to store data in a data acquisition system, including: 

• Local storage: The data can be stored locally on the data acquisition hardware, such as on a hard drive or flash memory. This allows the data to be accessed and analyzed directly from the data acquisition system.
• Portable storage: The data can be stored on a portable storage device, such as a USB drive or SD card, and transferred to a computer or other device for analysis. This allows the data to be easily transported and analyzed on different devices.
• Network storage: The data can be transmitted over a network to a remote location, such as a server or cloud storage, for storage and analysis. This allows the data to be accessed and analyzed from multiple locations.

The role of data visualization in a data acquisition system is to provide a visual representation of the data collected by the system, making it easier to understand and interpret the data. Data visualization can be used to identify patterns and trends in the data, allowing users to see the relationships quickly and easily between different data points. 

Data visualization can be used in a data acquisition system for a variety of purposes, including: 

• Identifying problems: By visualizing the data, it is easier to identify problems or anomalies in the data, such as sudden changes or unexpected trends. This can help users to quickly identify and address any issues that may be affecting the system.
• Making informed decisions: Data visualization can help users to make informed decisions by providing a clear and intuitive representation of the data. By visualizing the data, users can better understand the data and make more informed decisions based on the data.
• Communicating results: Data visualization can be used to communicate the results of data analysis to others in a clear and intuitive way. By visualizing the data, it is easier to convey the meaning of the data to others, whether they are technical or non-technical.