What would an artificial intelligence monocrystalline silicon pressure transmitter look like? In general, artificial intelligence (AI) is rapidly developing. The intelligent manufacturing of China Manufacturing 2025 and Industry 4.0 is still in the journey from the blueprint to the landing. Now it is too early to talk about the accurate characteristics of artificial intelligence pressure transmitters. However, it is quite certain that the current intelligent pressure transmitter is a smart single crystal silicon pressure transmission for China Manufacturing 2025 and Industry 4.0 compared to the previous generation of metal capacitor analog industrial pressure transmitters. Compared with the present, it should have more advanced intelligence, not only with menu operation, range migration, remote transmission operation and temperature compensation, but also with its own state awareness, real-time monitoring, independent decision-making, and accurate execution of high-level intelligence. The biggest difference is the ability to learn and improve, so that it can be called a true artificial intelligence silicon pressure transmitter. The future high-level deep intelligent pressure transmitter is referred to as Intelligent (AI) Pressure Transmitter, which is specially designed for the manufacture of new monocrystalline silicon technology pressure transmitter for China Manufacturing 2025 or Industrial 4.0 intelligent manufacturing. Not to mention the Smart Pressure Transmitter, which avoids confusion, can be called an artificial intelligence pressure transmitter, which has the following characteristics:
First of all, artificial intelligence pressure transmitter refers to equipment or equipment with digital communication and configuration, optimization, diagnosis, maintenance and other additional functions in addition to its basic functions. It generally has the ability of sensing, analysis, reasoning, decision-making and control. It is advanced manufacturing. A new generation of pressure transmitters for the integration and deep integration of technology, information technology and smart technology;
There is also a high-level intelligent capability of artificial intelligence pressure transmitters, with network communication function, self-perception ability to its own state, environment and process, with analysis, reasoning, decision-making and execution capabilities, with adaptive and optimization capabilities. , can provide all kinds of relevant data, support data analysis and mining, and integrate with the CPS system;
Finally, artificial intelligence pressure transmitters are all aspects of the product life cycle, including market demand analysis, product development and design, product production and management, product quality, supply chain, marketing management, customer management, and after-sales service. (PLM) is also manufactured by China Manufacturing 2025 or Industry 4.0.
The theoretical basis of artificial intelligence pressure transmitter is derived from the theoretical research of artificial intelligence, aiming at the clear goal of industrial safety application, and is expected to lead the basic theoretical direction of artificial intelligence technology upgrade, strengthen big data intelligence, cross-media perception computing, human-machine hybrid intelligence, Basic theoretical research on group intelligence, independent coordination and decision-making. details:
1. Big data intelligence theory. Research on new methods of artificial intelligence combining data-driven and knowledge-guided, cognitive computing theory and methods with natural language understanding and image graphics as the core, comprehensive deep reasoning and creative artificial intelligence theory and methods, and basic theory of intelligent decision-making under incomplete information And framework, data-driven general artificial intelligence mathematical models and theories.
2. Cross-media perception computing theory. Researching perceptual acquisition beyond human visual ability, active visual perception and computation for the real world, auditory perception and computation of natural acoustic scenes, speech perception and computation in natural interactive environments, human-like perception and computation for asynchronous sequences, media-oriented Autonomous learning of intelligent perception, urban full-scale intelligent perception inference engine.
3. Hybrid enhanced intelligence theory. Research on "human-in-the-loop" hybrid enhancement intelligence, human-computer intelligent symbiosis behavior enhancement and brain-computer coordination, machine intuitionistic reasoning and causal model, associative memory model and knowledge evolution method, complex data and task hybrid enhanced intelligent learning method, cloud Robot collaborative computing method, situational understanding in real world environment and human-machine group collaboration.
4. Group intelligence theory. Research group intelligent structure theory and organization method, group intelligence incentive mechanism and emergence mechanism, group intelligent learning theory and method, group intelligence general computing paradigm and model.
5. Autonomous collaborative control and optimization decision theory. Research on collaborative sensing and interaction for autonomous unmanned systems, collaborative control and optimization decision-making for autonomous unmanned systems, knowledge-driven ternary synergy and interoperability theory.
6. Advanced machine learning theory. Study the basic theories of statistical learning, uncertainty reasoning and decision making, distributed learning and interaction, privacy protection learning, small sample learning, deep reinforcement learning, unsupervised learning, semi-supervised learning, active learning and other learning theories and efficient models.
7. Brain-like intelligent computing theory. Research on brain-awareness, brain-like learning, brain-like memory mechanisms and computational fusion, brain-like complex systems, brain-like control, and other theories and methods.
8. Quantum intelligent computing theory. Exploring the quantum model and internal mechanism of brain cognition, researching efficient quantum intelligent models and algorithms, high-performance high-bit quantum artificial intelligence processors, and real-time quantum artificial intelligence systems that can interact with the external environment.
Artificial intelligence pressure transmitters in the field of safety applications, artificial intelligence pressure transmitters will better help the development of safety instrumented systems functional safety pressure transmitters, from now on the user's own experience of pressure transmitter application practice To use the big data to improve the performance of the existing single crystal silicon pressure transmitter, to avoid the measurement of diaphragm corrosion, static pressure overload, pressure shock (water hammer effect) caused by application conditions in single crystal silicon pressure transmitter ), hydrogen permeation embrittlement, etc., as well as failures caused by non-pressure transmitters such as process connection blockage, electronic signal line breakage, etc., so that the safety instrument system truly realizes real-time, uninterrupted protection of production safety.