German AWS Fertigungstechnik sensor AWS Fertigungstechnik model AWS Fertigungstechnik price

AWS Fertigungstechnik sensor pressure sensor for level measurement. The hydrostatic submersible level transmitter (level gauge) is based on the principle that the static pressure of the measured liquid is proportional to its height. It uses advanced foreign isolated diffused silicon sensitive elements or ceramic capacitive pressure sensitive sensors to convert static pressure into electrical signals, which are then converted into standard electrical signals (typically 4 to 20mA/15VDC) after temperature compensation and linear correction.

AWS Fertigungstechnik sensor classification

Lasers can be classified into 4 types according to the working medium. (1) Solid-state lasers: The working medium is solid. Common types include ruby lasers, neodymium-doped yttrium aluminum garnet lasers (i.e., YAG lasers), and neodymium glass lasers. Their structures are roughly similar, characterized by compactness, robustness, 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. Various gas atomic, ion, metal vapor, and gas molecular lasers are now available. Common types include carbon dioxide lasers, helium-neon lasers, and carbon monoxide lasers. They are shaped like ordinary discharge tubes, characterized by stable output, good monochromaticity, and long life, but have lower power and 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 main 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 carrying on aircraft, warships, tanks, and 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.

AWS Fertigungstechnik 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 capability, 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 reception. Laser sensors must measure the transmission time extremely accurately because the speed of light is very fast.

AWS Fertigungstechnik sensor application

Oversize detection of vehicle width and height: Laser sensors are used for rapid measurement. The network kernel of the PC industrial PC and visualization 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 show that the system has good real-time performance and high measurement accuracy, possessing certain practical value. Highway toll stations: Used at highway toll stations for vehicle counting and safety protection. Malaysia's Teras company has already 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 inspect 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, easy 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 prominently visible laser sensor on the roof, other sensors are set up very discreetly. Distinctive Google driverless car logos are affixed to the front, rear, and 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, 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. This Lexus vehicle has a 360° rotating laser holographic sensor on its roof, which can almost simultaneously sense conditions in front of, beside, and behind the car. Data collected by the sensor is input via green data cables to the processor located on the right rear side of the vehicle. This laser sensor also enables global precise positioning for the driverless car. The original L type Lexus emblem on the front of the car was removed and replaced with a radar sensor, used to measure the distance ahead and vehicle speed to determine the condition of traffic ahead and control safe acceleration and deceleration. 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 for software analysis and processing, enabling precise sensing and judgment of different objects near the driverless car. In addition to analyzing and judging the current positions of objects around the driverless car, the vehicle needs to use software 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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