
The rapid development and popularization of the new generation of information technology is causing far-reaching changes in the manufacturing industry all over the world. At present, the manufacturing industry is ushering in the fourth industrial revolution, namely Industry 4.0, which aims to use information integration and control systems to build smart factories and realize smart manufacturing.
In December 2017, the Chinese Academy of Engineering's "China Intelligent Manufacturing Development Strategy Research Report" proposed three basic paradigms for the development of intelligent manufacturing: the first stage, digital manufacturing; the second stage, digital networked manufacturing; the third stage, a new generation of intelligent manufacturing . In 2020, the Ministry of Industry and Information Technology will "accelerate the construction of intelligent manufacturing standard system for subdivided industries" as a key task.
However, the average automation level in petrochemical, pharmaceutical and other industries is not high at present, and the concept and management level of using information management is relatively low. The specific reasons mainly include weak information construction foundation, strong safety and quality supervision, and slow investment returns. The overall automation level of the industry is low, the development foundation of intelligent manufacturing is weak, it is generally in the stage of mechanization, the means of informationization are limited, and many devices still do not have network or data communication functions. As most of the material transfer and delivery between production links relies on manual labor, the data related to production management cannot be interconnected, management operations cannot be "connected into lines", and "information islands" are formed on the data, and there is still a gap between the realization of intelligent manufacturing.
Taking the extraction and stratification process as an example, there has always been the problem of "information islands" in the process of discharging materials from the reactor. Many units use manual observation and discharge, and manual control of the discharge valve to produce. It is impossible to achieve intelligence, and even mechanization cannot be achieved. The reason is that it is difficult to obtain the current liquid phase by intelligent means when discharging after liquid-liquid separation, and automatic control cannot be realized if it cannot be converted into digital signals.
In order to solve this difficulty in a targeted manner, Jiangsu Dongfangsai Optoelectronics Co., Ltd. has launched a smart sight glass product, which is used in the liquid phase detection of sight glass in the chemical industry.
The intelligent sight glass is suitable for the liquid phase detection of intermittent stratification in the synthesis and extraction section of fine chemicals, pesticides and medicines. It can quickly and reliably detect the water phase, oil phase, mixed phase (emulsion layer), and has a sensitive response to air bubbles, emulsion layers and impurities. The prefabricated structure is easy to install and has universal applicability to scenes where borescopes are used.
The use of AI machine vision technology to achieve liquid phase analysis and measurement in the sight glass is a major breakthrough in the informatization of chemical production processes. The smart sight mirror can output 4-20mA/RS485 signal and standard video stream signal synchronously, and the industrial standard 4-20mA signal can be connected to the DCS/PLC system in the control room. Combined with the production process, the automatic system can control all relevant regulating valves to complete automatic production. . The standard video stream signal can be connected to the video surveillance system for recording and monitoring of the production process.
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