Characteristics of digital sensors
1. Advanced A/D conversion technology and intelligent filtering algorithm ensure stable output code even at full scale.
2. Feasible data storage technology to ensure that module parameters are not lost.
3. Good electromagnetic compatibility performance.
4. The sensor's performance adopts digital error compensation technology and highly integrated electronic components. Software is used to achieve comprehensive compensation for the sensor's linearity, zero point, temperature drift, creep and other performance parameters, eliminating the influence of human factors on compensation and greatly improving the sensor's overall accuracy and reliability.
5. The output consistency error of the sensor can reach within 0.02% or even higher, and the characteristic parameters of the sensor can be completely identical, thus having good interchangeability.
6. By adopting A/D conversion circuits, digital signal transmission, and digital filtering technology, the sensor's anti-interference capability is increased, the signal transmission distance is extended, and the sensor's stability is improved.
7. Digital sensors can automatically collect data and can preprocess, store, and memorize it. They have unique identifiers, which facilitates fault diagnosis.
8. The sensor adopts a standard digital communication interface, which can be directly connected to a computer or connected to a standard industrial control bus, making it convenient and flexible.
9. A digital sensor integrates an analog-to-digital converter (AD), an EPROM, and a die (DIE, referring to an unpackaged sensor chip, a bare die, with a size between a cell and a chip), all packaged on a PCB, metal block, or ceramic PCB. It is manufactured by calculating the linearity of the DIE through calibration at various temperature and pressure points, and then using an AD converter for compensation.
Applications and Prospects of Digital Sensors
With microprocessors and sensors becoming increasingly cheaper, fully automatic or semi-automatic (high-level operations performed by human instructions, low-level operations handled automatically) systems can contain more intelligent functions and obtain and process more different parameters from their environment. In particular, MEMS (microelectromechanical systems) technology makes digital sensors very small in size and low in energy consumption and cost. Nanosensors made of carbon nanotubes or other nanomaterials also have great potential [1].
Even in its nascent stage, digital sensors are widely recognized as a significant driver of the electronics market in the near future. The fabrication of digital sensor interfaces and the support for the diverse communication protocols used in digital sensor networks present substantial technological challenges. The heterogeneous nature of sensors and the variability of their operating conditions also pose significant challenges to the technological process.
The number of sensors and processors incorporated into system designs is increasing. As the price of sensors and processors continues to decrease, the threshold for replacing mechanical control structures is also constantly changing. Selecting the right sensor combination and processing algorithm in a system can significantly reduce raw material and energy costs and improve overall system performance. Continuously improving operational simplicity and extending energy lifespan is becoming increasingly important, especially as more and more sensor networks are now configured with 1000 or more sensor nodes.
