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Prosensor sensors are devices that convert mass signals into measurable electrical signal outputs. When using a sensor, the actual working environment of the sensor must be considered first. This is crucial for the correct selection of load cells, as it affects whether the sensor can operate normally, its safety and service life, and even the reliability and safety of the entire weighing system. There are qualitative differences between the old and new national standards regarding the basic concepts and evaluation methods of the main technical indicators of load cells. The main types include S type, cantilever type, spoke type, plate ring type, membrane box type, bridge type, and column cylinder type.

Prosensor sensor classification

Lasers can be divided into 4 types according to the working medium. (1) Solid-state lasers: The working medium is solid. Common examples include ruby lasers, neodymium-doped yttrium aluminum garnet lasers (i.e., YAG lasers), and neodymium glass lasers. Their structures are roughly similar, characterized by being small, robust, and high-power. Neodymium glass lasers are devices with the highest pulsed output power, reaching tens of megawatts. (2) Gas lasers: The working medium is gas. There are now various gas atomic, ion, metal vapor, and gas molecular lasers. Common examples include carbon dioxide lasers, helium-neon lasers, and carbon monoxide lasers. Their shape resembles ordinary discharge tubes, characterized by stable output, good monochromaticity, and long life, but lower power and lower conversion efficiency. (3) Liquid lasers: These can be further divided into chelate lasers, inorganic liquid lasers, and organic dye lasers, among which organic dye lasers are the most important. Their greatest feature is continuously tunable wavelength. (4) Semiconductor lasers: This is a relatively young type of laser, with gallium arsenide lasers being more mature. They are characterized by high efficiency, small size, light weight, and simple structure, making them suitable for use on aircraft, warships, tanks, and for carrying by infantry. They can be made into rangefinders and sights. However, they have lower output power, poorer directionality, and are significantly affected by ambient temperature.

Prosensor sensor principle

When a laser sensor operates, the laser emitting diode first emits laser pulses toward the target. After reflection from the target, the laser scatters in all directions. Part of the scattered light returns to the sensor receiver, is received by the optical system, and is imaged onto an avalanche photodiode. An avalanche photodiode is an optical sensor with internal amplification functionality, so it can detect extremely weak light signals and convert them into corresponding electrical signals. The common type is the laser distance sensor, which determines the target distance by recording and processing the time elapsed from the emission of the light pulse to its return and reception. Laser sensors must measure transmission time extremely precisely because the speed of light is very fast.

Prosensor sensor applications

Over-limit detection of vehicle width and height: Laser sensors are used for rapid measurement. The network kernel of the PC industrial PC and visual programming software VB is utilized for real-time data transmission and processing with the sensors. User-friendly upper computer control software has also been designed. Field test data shows that the system has good real-time performance, high measurement accuracy, and certain practical value. Highway toll stations: Used at highway toll stations for vehicle counting and safety protection. Malaysia's Teras company has applied hundreds of sets of BEA laser sensors in its manual and automatic toll station systems. The laser sensors adopt the Time of Flight (TOF) measurement principle, forming 4 planes within the detection area to detect vehicles. Meanwhile, the product also features functions such as anti-rear-end collision and vehicle safety protection. Compared with traditional light curtains, laser sensors offer advantages such as high sensitivity, high precision, convenient installation, high cost-performance ratio, and strong stability. Google's second-generation driverless car: Equipped with laser sensors. In Google's second-generation autonomous vehicle prototype, besides the laser sensor on the top which remains quite obvious, other sensors are set up very discreetly. Distinctive Google driverless car logos are affixed to the front, rear, and both sides of the vehicle. The control and driving principle of the Google driverless car involves numerous sensors installed around the car continuously collecting precise data about the vehicle itself and its surroundings. The onboard processor analyzes and calculates this data, and then controls the vehicle's movement based on the results. The driverless car uses GPS equipment and sensors to accurately locate the vehicle's position and forward speed, and to identify surrounding pedestrians, vehicles, bicycles, traffic lights, and many other objects. On the roof of this Lexus, there is a laser holographic sensor rotating 360°, which can almost simultaneously sense the conditions in front, to the sides, and behind the car. Data collected by the sensor is input via green data cables into the processor located on the right rear side of the vehicle. This laser sensor also allows the driverless car to achieve global precise positioning. The original L type Lexus emblem on the front of the car was removed and replaced with a radar sensor; this is used to measure the distance ahead and vehicle speed, in order to judge the traffic conditions ahead and control safe acceleration and deceleration of the vehicle. Position sensors are also installed on the tire hubs to detect wheel rotation, helping the vehicle with positioning. The heart of the Google driverless car—the processor—is located on the right rear side of the vehicle. Data information from various sensors is transmitted here via data wires, where it is analyzed and processed by software to precisely sense and judge different objects near the driverless car. In addition to analyzing and judging the current positions of objects around the driverless car, the software needs to calculate and accurately predict the possible next position of each object. Finally, the driverless car makes safe driving decisions based on all collected data, including controlling vehicle speed and distance from surrounding vehicles.

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