1. Sensor
A sensor is a device that detects and measures physical properties or changes in the environment and converts this information into signals or data that can be interpreted, displayed, or used by other systems. There are many types of sensors and signals. However, the brief explanation behind the sensor technology is to acquire information by detecting the physical, chemical, or biological property quantities and convert them into readable signal.
Listed below are the main sensor types and measurement areas;
- Accelerometers: used in acceleration, vibration, shock, calibration and many similar fields.
- Load cells: used in measuring weight and load.
- LVDT sensors: used in displacement and distance measurements.
- Microphones: used in inspection of sound waves.
- Strain Gages: used in strain measurements, if the Youngs modulus of the structure is known then it is possible to calculate the stress by using hook’s law as well.
- Thermocouple, Resistance Temperature Detector (RTD) & Thermistor: used in temperature measurements.
Depending on the type of sensor, its electrical output can be voltage, current, resistance or another electrical characteristic that changes over time. Some sensors can be used with digital outputs so that they output a range of byte scaled or unscaled data. The output of these analog sensors is typically connected to a signal conditioner input, which we will be cover ed in the next section.
Ultimately, people use sensors to measure acceleration, temperature, force, gauge distance, regulate pressure and a myriad of other uses.
2. Signal Types
2.1 Analog Signal
Figure 1: Analog vs Digital Signal
Analog signals are continuous signals that vary smoothly over time. They are characterized by having an infinite number of possible values within a given range. They normally take the form of sine waves, and they can be defined by amplitude, frequency and phase. Amplitude denotes the highest height of the signals, frequency denotes the varying rate of the analog signals and phase denotes the position of the signal in time. Analog signals can represent a wide range of physical quantities, and they are used in various applications, including audio transmission, video transmission, and many types of sensors.
2.2. Digital Signal
Digital signals are discrete signals that represent information using a sequence of discrete values or symbols. Unlike analog signals which have a continuous range of values, digital signals have a finite set of distinct levels, often represented by binary digits (bits) zeros and ones. They are defined by bit interval and bitrate where bit interval is the required time to transmit one bit and bitrate is the frequency of the bit interval. Digital signals are widely used in modern communication, computing, and electronic systems due to their robustness against noise and ease of processing.
2.3. Analog to Digital Converter
An Analog-to-Digital Converter (ADC) is a crucial component in the field of electronics and signal processing. Its primary function is to convert continuous analog signals into discrete digital values, making it easier to process, store, and analyze the data using digital systems.
As seen above, an ADC inputs an analog electrical signal, such as voltage or current, and outputs a binary number. This is how it can be represented in block diagram form.
The main purpose of AD converters within a data acquisition system is to convert conditional analog signals into a digital data stream so that the data acquisition system can process them for display, storage and analysis. The ADC takes an analog signal and converts it into the digital domain. Although there are five main types of ADCs today, in the modern data acquisition systems (DAQ) world, it can be split into two notion;
- Successive Approximation Register (SAR)
- Delta-Sigma (˄-Σ)
SAR offers an excellent balance of speed and resolution and handles a wide range of signals with excellent accuracy. SAR designs are stable and reliable and the chips are relatively inexpensive. They can be configured both for low-end AD cards where a single ADC chip is “shared” by multiple input channels (multiplexed AD cards) or in configurations where each input channel has its own ADC for true simultaneous sampling.
Due to their limited amplitude axis resolution, they are not suitable for high dynamic applications such as noise, sound, shock and vibration, equalization, sine processing, etc. For these applications, engineers should turn to delta-sigma ADCs.
A newer ADC design is the Delta-Sigma ADC, which utilizes digital signal processing technology to improve amplitude axis resolution and reduce the high-frequency quantization noise found in SAR designs.
The complex and powerful design of “˄-Σ” ADCs makes them ideal for dynamic applications that require as much amplitude axis resolution as possible. For this reason, they are widely found in audio, audio and vibration, and a wide range of high-end data acquisition applications.
To sum up the sensor technology is the technology that uses sensors to acquire info from a certain quantity and converts them into a readable signal. To make sense of this issue the signal types play an important role in the background and the main two signal types “analog signal & digital signal” have been explained up to this point. Last but not least, it should be emphasized that the choice of which ADC technology to use should always be based on application requirements. If you are primarily measuring static and quasi-static (slow) signals, of course you don’t need a super high speed system, but you probably want one with as much amplitude axis resolution as possible. Stationary systems used in industry usually have requirements that do not change much and it is usually easier to choose a system. For DAQ systems, however, it is a bit more challenging as these systems are used in a variety of applications over time. The solution is to choose the one with the best overall performance and protection against noise, aliasing and aging.