What is a Smart Sensor? Smart Sensor Introduction Brochure

 

 

A good 'smart sensor' is a sensor and instrumentation package driven by a microprocessor with functions such as communication and on-board diagnostics.

 

Smart sensors can store various physical quantities detected and process these data as instructed to create new data. Intelligent sensors can exchange information, and can self-determine the data that should be transmitted, discard abnormal data, and complete analysis and statistical calculations.

 

 

Smart sensors are smart devices that integrate sensors, actuators and electronic circuits, or devices that integrate sensing elements and microprocessors, and have monitoring and processing functions. The biggest feature of smart sensors is the output of digital signals, which is convenient for subsequent calculation and processing. The functions of smart sensors include signal perception, signal processing, data verification and interpretation, signal transmission and conversion, etc. Major components include A/D and D/A converters, transceivers, microcontrollers, amplifiers, and more.

 

 

Sensors are devices that convert specific physical quantities into electrical signals to detect, measure or indicate them. When the sensor senses and sends information, the actuator is activated and starts working. The actuator receives the signal and sets its desired action so that it can act in the environment.

 

Smart sensors refer to smart sensor devices that can sense, collect and independently judge, analyze and process external environmental information. Smart sensors are multi-component integrated circuits with functions of information collection, processing, exchange, storage and transmission. They are system-level devices that integrate sensors, communication modules, microprocessors, drivers and interfaces, and software algorithms. Diagnostic and self-compensatory abilities, as well as sensory integration and flexible communication.

 

 

3.1 Self-Test, Self-Calibration, and Self-Diagnosis: The Self-Diagnostic function performs a self-test at power-up and uses diagnostic tests to determine if a component has failed. It can be corrected online according to the time of use, and the microprocessor uses the stored measurement characteristic data for comparison and verification.

 

3.2 Induction fusion: Smart sensors can measure multiple physical and chemical quantities at the same time, giving more comprehensive information reflecting the laws of matter motion. For example, fusion liquid sensors can simultaneously measure the temperature, flow, pressure and density of a medium. How does a mechanical sensor measure the three-dimensional vibration acceleration, velocity, displacement, etc. of a certain point of an object at the same time.

 

3.3 High precision: The intelligent sensor has the function of information processing, which can not only correct various deterministic system errors through software, but also make appropriate compensation for random errors and reduce noise, thereby greatly improving the accuracy of the sensor.

 

3.4 High reliability: The integrated sensor system eliminates some unreliable factors of the traditional structure and improves the anti-interference performance of the whole system. At the same time, it also has functions such as diagnosis, calibration, data storage, etc., with good stability.

 

3.5 Cost-effectiveness: Under the same precision requirements, the cost-effectiveness of multi-functional smart sensors is significantly higher than that of ordinary sensors with a single function, especially after integrating a cheaper microcontroller.

 

3.6 Diversified functions: intelligent sensors can realize multi-sensor and multi-parameter comprehensive measurement, and expand the measurement and use range through programming. It has a certain adaptive ability, and can change the range from the output data accordingly according to the change of the detected object or condition. With the function of digital communication interface, it can be directly sent to the remote computer for processing. With a variety of data output forms, suitable for various application systems.

 

3.7 Signal normalization: The analog signal of the sensor is normalized by an amplifier and then converted into a digital signal by an analog-to-digital converter. Microprocessors also perform digital normalization in various digital transmission forms such as serial, parallel, frequency, phase, and pulse.

 

 

The growing popularity of IoT and Industrial IoT

Trends in vehicle electrification and intelligence

The popularity of wearable consumer electronics

Advances in Sensor Technology and MEMS Manufacturing Processes

The increasing use of various sensors in smartphones

Strong demand for industrial automation and smart manufacturing

Smart Cities, Transportation and Building Intelligence

 

 

From 2020 to 2027, the global smart sensor market will grow at a CAGR of 18.6%, reaching USD 143.65 billion in 2027. Among them, the automotive industry is the world's largest smart sensor application market, accounting for about a quarter. During the forecast period 2020-2027, the automotive smart sensor market growth rate is expected to reach 21.7%. Additionally, wearables and healthcare applications will present near-term growth opportunities for smart sensors. From a technology perspective, Micro Electro Mechanical Systems (MEMS) account for more than 50% of the market. Nanoelectromechanical systems (NEMS) are expected to be the fastest growing product type during the forecast period, but MEMS technology will still dominate.

 

 

The rapid growth and popularity of IoT is driving strong demand for smart sensors. There are many IoT application scenarios, as follows:

 

6.1 Smart Wearables: In many wearable devices, sensors are the core device and the value proposition of the device. Virtual Augmented and Mixed Reality (VR/AR/MR) devices rely on a full suite of sensors to enable users to interact with their surroundings, while virtual content requires a core set of sensors to enable human interaction with the environment. Examples include motion sensors, biosensors, and environmental sensors. A smart wearable device consists of five modules: processor and memory, power supply, wireless communication, sensor and actuator. Among them, the sensor is the innovative element of the five modules and is the core of the communication between people and things. Wearables can now enable more accurate data monitoring thanks to advancements in sensor technology.

 

6.2 Smart home: Smart home is based on housing, integrating security monitoring, home appliance control, lighting control, background music, and voice control. It can be linked with centralized management to provide a more convenient, comfortable, safe and energy-saving family living environment. The smart home system consists of sensors, actuators, control centers, communication networks, etc., and obtains various data of the indoor environment through various sensors. Sensors used in homes include temperature sensors, image sensors, photosensors, and air sensors.

 

6.3 Smart cities: Smart cities are cities that use an information and communication technology (ICT) framework to improve urban management and encourage economic growth. ICT interacts with the Internet of Things (IoT), which can receive, analyze and transmit data about current conditions and events. The Internet of Things includes any device that can make cities more efficient or more accessible, including cell phones, smart vehicles, security cameras, and sensors embedded in roads. The main features of a smart city are physical and technological infrastructure, environmental monitoring and response capabilities, and smart services for citizens. The first is the technological foundation, which includes a large number of smartphones and sensors connected by high-speed communication networks. The second layer consists of application-specific tools that require the right tools to transform raw data into alerts, insights and actions. The third layer is the utilization of cities, businesses and the public. In a smart city, a network of sensors, cameras, wireless devices and data centers form critical infrastructure. Among them, sensing is the core of intelligent infrastructure, sensors are hidden but ubiquitous components in the urban landscape, and an important part of any intelligent control system. Sensor networks include acoustic, lidar, radar, 3D camera sensors, environmental sensors, flow sensors, gas sensors, and humidity and temperature sensors. Integrated sensor systems facilitate seamless interconnection with applications and centralized platforms. Purpose-built sensor networks can support several other connected applications, such as environmental monitoring and public safety, and such a centralized network will help reduce duplicate investment costs and eliminate the need for multiple separate complex networks .

 

6.4 Intelligent transportation: Intelligent transportation is the use of various intelligent technologies and equipment to promote the digitization, networking and intelligence of transportation. Among them, networking is crucial for the development of intelligent transportation. The use of the Internet of Things can make all links and links of traffic network smoothly, not only can effectively strengthen traffic supervision, improve traffic services, but also further improve the existing traffic formats. The application of intelligent transportation system (ITS) in urban transportation is reflected in the microscopic traffic information collection, traffic control, guidance and so on. It improves the efficiency of the traffic system by improving the effective utilization and management of traffic information, mainly through information collection input, strategy control, output execution between subsystems and other subsystems, data transmission and communication. The information collection subsystem collects vehicle and road information through sensors, and the strategy control subsystem uses the calculation method to calculate the optimal solution according to the set target, and outputs a control signal to the execution subsystem to guide and control the passage of vehicles to achieve the preset target.

 

6.5 Smart grid: Smart grid is a power grid system that realizes energy resource development, conversion and power generation, transmission and distribution, power supply, sales and electricity consumption through information technology, with the goal of saving electricity. The benefits of smart grids lie in reducing carbon dioxide emissions, saving energy, and reducing power outages. The investment required to build smart grids is mainly used for terminal power distribution systems and terminal information systems of power facilities, and a large part of them is the investment in sensor networks. The construction of sensor network is an important part of smart grid transformation, and the key is to introduce sensors into the hierarchical structure of power grids at all levels. Perception layer, network layer, WSN and application layer are the three layers of smart grid. Among them, the perception layer includes two-dimensional code tags and readers, RFID tags and readers, cameras, various sensors and sensor networks. The function of the WSN perception layer is to perceive and identify objects, and to collect and capture information.

 

6.6 Smart buildings: Smart buildings are different from smart homes, and specifically refer to non-residential buildings such as office buildings, shopping malls, and hotels. Devices in these buildings are connected to sensors that can provide energy consumption information and automatically make decisions to optimize operations. A series of networked sensors collect environmental information, as well as data about building operations and usage. This information can either be processed at the edge or sent to a central BMS system running on-premises or in the cloud. This information is then used to trigger automated actions to adjust HVAC systems, lighting systems and many other devices in the building. Buildings can become smart by creating cross-connections between different subsystems with sensors, actuators, and controllers.

 

6.7 Smart Agriculture: Smart agriculture, also known as precision agriculture, uses minimal resources, such as water, fertilizers and seeds, to maximize yields. Through the deployment of sensors and the field of mapping, agricultural workers begin to understand the growth process of crops from a microscopic perspective, scientifically save resources and reduce the impact on the environment. Many sensing technologies are used in precision agriculture, providing data that helps monitor and optimize crops and adapt to changing environmental factors. These include position sensors, optical sensors, electrochemical sensors, mechanical sensors, soil moisture sensors, and airflow sensors.

 

6.8 Smart Medical: Medical sensors are often used in expensive medical devices, so medical electronic sensors are a high-value type of sensor. Medical sensors are classified according to their working principles and application forms. According to the working principle, it is divided into physical sensors, chemical sensors, biological sensors, and biological electrode sensors. According to the application form, it is divided into implantable sensors, temporary implantable sensors, external sensors, sensors for external devices, and edible sensors. With the development of material technology and electronic technology, flexible matrix materials have gradually entered the medical market with their advantages such as flexibility, bendability, ductility, and wear resistance. Flexible sensors have the advantages of flexible matrix materials, are highly adaptable to the human body, and have good adaptability to wearable devices and implantable devices. Flexible sensors can be used in smart band-aids, smart bandages, flexible oximeters, and flexible wearable ionic humidity sensors.

 

6.9 Environmental monitoring: The application of sensor technology in environmental monitoring is reflected in two aspects: physical or chemical reaction with pollutants in the detection material, to determine whether there are pollutants in the detection material. Chemical signals are converted into electrical signals. The application of sensor technology has greatly improved the reliability of environmental detection results. According to the different detection methods, sensor technology can be divided into optical sensors and electrochemical sensors. The different response mechanisms can be classified into biosensors and immunosensors. Different detection objects can be divided into liquid sensors and gas sensors. The basic principle of biosensors is to use functional genes, antibodies and other biological materials as sensitive materials, use a signal acquisition device to collect biochemical information, and convert the biochemical information into electrical signals for analysis. As biosensor technology continues to evolve, there are more and more sensitive materials and sensor elements that help to accurately identify more contaminants in the environment. Compared with traditional sensors, biosensors are more selective, simpler to operate, faster to test, and more accurate in results. Biosensor technology is mostly used for atmospheric environment detection, including sulfur dioxide detection, nitrogen dioxide detection, heavy metal ion detection, pesticide residue detection, etc.

 

6.10 Intelligent Manufacturing: One of the typical applications of intelligent sensing in the manufacturing process is reflected in the CNC machine tools widely used in the machinery manufacturing industry. Modern CNC machine tools are equipped with high-performance sensors for detecting displacement, position, speed, pressure, etc., which can monitor processing status, tool status, wear, energy consumption, etc. in real time, and achieve flexible error compensation and self-correction. Realize the development trend of intelligent CNC machine tools. In addition, the use of visual monitoring technology based on visual sensors makes the intelligent monitoring of CNC machine tools more convenient. Smart sensing has many applications in the automotive manufacturing industry. Taking machine vision based on optical sensing as an example, the main applications in the industrial field are vision measurement, vision guidance and vision inspection. In the automotive manufacturing industry, visual measurement technology can ensure that the product is qualified in the factory by measuring the key dimensions, surface quality, and assembly effect of the product. Vision-guided technology can significantly improve automated handling, best-fit assembly, and precise holemaking by guiding the machine through automated handling. Manufacturing efficiency and body assembly quality. Visual inspection technology can monitor the stability of the body manufacturing process, can be used to ensure product integrity and traceability, and help reduce manufacturing costs. Sensors in the high-end equipment industry are mostly used for equipment operation and maintenance and health management. The intelligent sensor equipped with aero-engine enables the control system to have fault self-diagnosis and fault handling capabilities, which improves the system's ability to cope with complex environments and precise control. In the field of industrial electronics, production, handling, inspection, and maintenance all involve intelligent sensors, such as robotic arms, AGV navigation vehicles, AOI detection and other equipment. In the fields of consumer electronics and medical electronics, the applications of smart sensors are more diverse. For example, the more common smart sensors in smartphones include distance sensors, light sensors, gravity sensors, image sensors, three-axis gyroscopes, electronic compasses, and the like. The most basic function of wearable devices is to realize motion sensing through sensors, usually built-in MEMS accelerometers, heart rate sensors, pulse sensors, gyroscopes, MEMS microphones and other sensors. Smart homes involve technologies such as position sensors, proximity sensors, level sensors, flow and speed controls.

 

 

"The advantage of smart sensors," said Bill Black, controller product manager at GE Fanuc Automation, "is the ability to gather a lot of information from the process to reduce downtime and improve quality." MTS Sensors, Inc. Temposonics (Magnetostrictive Displacement Sensors) Product manager David Edeal added: "The fundamental premise of distributed intelligence is having full knowledge of the state of a system, subsystem or component in place and time to make 'optimal' process control decisions."

 

John Keating, product marketing manager for Checker Machine Vision at Cognex, continued, "For a truly 'smart' (machine vision) sensor, it should not require the user to understand machine vision."

 

Smart sensors must have communication capabilities. "At the very least, a 'smart' sensor must be able to transmit information other than the feedback signal for the most basic application," Edeal said. This can be a HART (Highway Addressable Remote Transducer Highway Open Communication Protocol) signal superimposed on a standard 4-20 mA process output, a bus system, or a wireless arrangement. A growing factor in this area is IEEE 1451, a series of smart sensor interface standards designed to provide plug-and-play capabilities for sensors from different manufacturers.

 

 

Smart sensors can self-monitor every aspect of their operation, including "cameras that are dirty, out of tolerance, or unable to switch," says GE Fanuc Automation's Black.

 

Helge Hornis, Intelligent Systems Manager at Pepperl+Fuchs, adds, “[Besides] there is also the coil monitoring function, if the target is out of range or too close.” It can also compensate for changes in operating conditions. “‘Smart’ sensors,” said Dan Armentrout, strategic creative director at Omron Electronics Ltd., “must first be able to monitor themselves and their surroundings, and then decide whether to automatically compensate for changes or warn those involved.”

 

Many smart sensors can be retrofitted to the control site, allowing users to replace some 'standard' sensors by providing "settable parameters," Hornis said, "for example, typical sensors are typically set to normally open (NO) or normally closed. (NC), and smart sensors can be set to any of these states.”

 

Smart sensors have many advantages. As the cost of embedded computing functions continues to decrease, more "smart" devices will be used.

 

 

Intelligent sensor system is a modern comprehensive technology, which is a high-tech new technology that is developing rapidly in today's world, but has not yet formed a standardized definition. In the early days, people simply and mechanically emphasized the close integration of the sensor and the microprocessor in the process, and believed that "the sensitive element of the sensor and its signal conditioning circuit and the microprocessor are integrated on a chip to be a smart sensor".

 

There is no unified statement about the Chinese and English appellations of smart sensors. John Brignell and Nell White believe that "Intelligent Sensor" is the British term for smart sensors, while "Smart Sensor" is the common term for Americans to smart sensors. In the article "Integrated Smart Sensor", Johan H. Huijsing called them "Smart Sensor" and "Integrated Smart Sensor" according to the degree of integration. The Chinese translation of "Smart Sensor" is translated as "smart sensor" or "smart sensor".

 

The definition in the book "Intelligent Sensor System": "The combination of intelligence given by sensors and microprocessors, and a sensor with both information detection and information processing functions is an intelligent sensor (system)"; fuzzy sensor is also a kind of intelligent sensor (system), Integrating a sensor with a microprocessor on a single chip is one way to form a smart sensor (system). ("Intelligent Sensor System", Liu Junhua, Xidian University Press)

 

The definition in the book "Principles and Applications of Modern New Sensors": An intelligent sensor is a sensor with a microprocessor, which has functions of information detection, information processing, information memory, logical thinking and judgment. ("The Principle and Application of Modern New Sensors", Liu Yingchun, Ye Xiangbin, etc., National Defense Industry Press, 2000.5)

 

 

In summary, the main functions of smart sensors are:

(1) It has the functions of self-calibration, self-calibration and self-calibration;

(2) With automatic compensation function;

(3) It can automatically collect data and preprocess the data;

(4) It can automatically perform inspection, self-selecting range, and self-finding;

(5) It has the functions of data storage, memory and information processing;

(6) With two-way communication, standardized digital output or symbol output function;

(7) It has the functions of judgment and decision-making.

 

 

The function of the smart sensor is proposed by simulating the coordinated actions of human senses and brain, combined with long-term research and practical experience of testing technology. It is a relatively independent intelligent unit. Its appearance reduces the harsh requirements of the original hardware performance, and the performance of the sensor can be greatly improved with the help of software.

 

11.1 Information storage and transmission - With the rapid development of the all-intelligent distributed control system, the intelligent unit is required to have the communication function, and the communication network is used for two-way communication in digital form, which is also one of the key signs of the intelligent sensor. Smart sensors realize various functions by transmitting test data or receiving instructions. Such as gain setting, compensation parameter setting, internal inspection parameter setting, test data output, etc.

 

11.2 Self-compensation and calculation function—Engineers and technicians who have been engaged in sensor development for many years have been doing a lot of compensation work for the temperature drift and output nonlinearity of the sensor, but they have not solved the problem fundamentally. The self-compensation and calculation functions of smart sensors have opened up new avenues for sensor temperature drift and nonlinear compensation. In this way, to relax the sensor processing precision requirements, as long as the repeatability of the sensor can be ensured, the microprocessor can be used to calculate the test signal through software, and multiple fitting and difference calculation methods are used to compensate for drift and nonlinearity, so as to be able to Get more accurate measurements from pressure sensors.

 

11.3 Self-inspection, self-calibration, and self-diagnosis functions - ordinary sensors need to be regularly inspected and calibrated to ensure sufficient accuracy during normal use. These tasks generally require the sensor to be disassembled from the use site and sent to the laboratory or inspection department. . The abnormality of the online measurement sensor cannot be diagnosed in time. With smart sensors, the situation is greatly improved. First, the self-diagnostic function performs a self-test when the power is turned on, and the diagnostic test determines whether the component is faulty. Secondly, it can be corrected online according to the use time, and the microprocessor uses the measurement characteristic data stored in the EPROM to compare and check.

 

11.4 Composite sensitive function - we observe natural phenomena around us, common signals include sound, light, electricity, heat, force, chemistry, etc. Sensing components are generally measured in two ways: direct and indirect. The smart sensor has a composite function, can measure a variety of physical and chemical quantities at the same time, and provide information that can comprehensively reflect the laws of matter motion. For example, the composite liquid sensor developed by the University of California, USA, can simultaneously measure the temperature, flow rate, pressure and density of the medium. The composite mechanical sensor can simultaneously measure the three-dimensional vibration acceleration (acceleration sensor), velocity (velocity sensor), displacement (displacement sensor) of an object at a certain point, and so on.

 

11.5 Integration of smart sensors ---- Due to the development of large-scale integrated circuits, sensors and corresponding circuits are integrated on the same chip, and such sensors with some smart functions are called integrated smart sensors. There are three advantages: higher signal-to-noise ratio: the weak signal of the sensor is first amplified by the integrated circuit signal and then transmitted over a long distance, which can greatly improve the signal-to-noise ratio. Improve performance: Since the sensor and the circuit are integrated on the same chip, the zero drift, temperature drift and zero position of the sensor can be automatically calibrated regularly by the self-calibration unit, and the frequency response of the sensor can be improved by appropriate feedback methods. Signal normalization: The analog signal of the sensor is normalized through the process control amplifier, and then converted into a digital signal through analog-digital conversion. The microprocessor performs digital normalization in several forms of digital transmission, such as serial, parallel, frequency, etc. Phase and pulse, etc.

 

 

A good sensor design is the result of experience plus technology. It is generally understood that a sensor is a description that converts a physical quantity through a circuit into a physical quantity that can be expressed in another intuitive way. For example, it is converted into signals such as higher voltage and current that only depend on the measured physical quantity, and then displayed. So there are a few things to note:

 

12.1 Generally measured physical quantities are very small, usually with conversion noise inherent to the physical conversion element of the sensor. For example, the signal strength of the sensor under the magnification of 1 is 0.1~1uV, and the background noise signal at this time is also so large that it is even annihilated. How to extract useful signals as much as possible and reduce noise is the primary problem of sensor design.

 

12.2 The sensor circuit must be simple and refined. Imagine an amplification circuit with a 3-stage amplifier circuit and a 2-stage active filter, which amplifies the signal and also amplifies the noise. If the noise does not deviate significantly from the useful signal spectrum, no matter how the filter is filtered, both are amplified at the same time. The result The signal-to-noise ratio is not improved. Therefore, the sensor circuit must be refined and simple. To save a resistor or capacitor, it must be removed. This is an issue that many engineers designing sensors tend to overlook. It is known that the sensor circuit is plagued by noise problems, and the more the circuit is modified, the more complex it becomes, which becomes a strange circle.

 

12.3 Power consumption issues. Sensors are usually at the front end of subsequent circuits and may require longer lead connections. When the power consumption of the sensor is large, the connection of the leads will introduce all the unnecessary noise and power supply noise, making the subsequent circuit design more and more difficult. How to reduce the power consumption when it is enough is also a big test.

 

12.4 Selection of components and power circuit. The selection of components must be sufficient, as long as the device indicators are within the required range, the rest is the problem of circuit design. The power supply is a problem that must be encountered in the design process of the sensor circuit. Do not pursue unattainable power supply indicators, but choose an op amp with a better common mode rejection ratio, and use a differential amplifier circuit to design the most common switching power supply and device can meet your requirements. The decoupling of the power supply must be designed reliably and follow the requirements of the device manual, rather more than less.