An industrial safety monitoring system based on intelligent thermal imaging

Abstract

The invention provides an industrial safety monitoring system based on intelligent thermal imaging. The system comprises a safety monitor correspondingly arranged for an operator, an independently arranged display unit, a lower-layer control unit used for sending a stopping instruction to machining equipment, and a cloud server used for collecting, analyzing and classifying violation data recorded on the safety monitor. The safety monitor is provided with a communication port and a thermal imaging assembly. The communication port is connected with the cloud server, the lower-layer control unit and the display unit through a wireless network. The system is simple in structure, long in service life and high in working efficiency. The production process is monitored in real time through the thermal imaging assembly. Compared with the prior art, the monitoring is more accurate. Furthermore, the cloud server is used for carrying out data sampling on the safety monitor correspondingly arranged for the operator. Therefore, the adaptability of operators to various devices is analyzed, so that an optimal operator for each device can be found out for users.

Description

technical field [0001] The invention relates to the field of safety production monitoring equipment, in particular to an industrial safety monitoring system based on intelligent thermal imaging. Background technique [0002] For production enterprises, safe production is treated as the first principle of production, so modern production and processing equipment manufacturers will add safety protection devices to their own equipment to ensure the safety of the production process, but most of the production Safety accidents are random and sudden, and the activation of safety protection devices often requires response time, so the safety production monitoring device used to predict the trend of dangerous events is particularly important. [0003] The main safety monitoring parameter in the existing technology is the distance, that is, the distance between the parts of the operator's body used for operation (hands, feet, etc.) and the dangerous area of ​​the processing equipment...

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Problems solved by technology

[0002] For production enterprises, safe production is treated as the first principle of production, so modern production and processing equipment manufacturers will add safety protection devices to their own equipment to ensure the safety of the production process, but most of the production Safety accidents are random and sudden, and the activation of safety protection devices often requires response time, so the safety production monitoring device used to predict the trend of dangerous events is particularly important

[0003] The main safety monitoring parameter in the existing technology is the distance, that is, the distance between the parts of the operator's body used for operation (hands, feet, etc.) and the dangerous area of ​​the processing equipment (drill bits, cutting saws, high-speed rotating parts, high-speed extrusion parts, etc.) The main method is to read the switching value through a simple infrared sensor to ensure timely alarm and stop the device when it crosses the boundary. However, the work of the infrared sensor is usually affected by the environment and becomes unstable. Simple infrared switches are prone to failure. This makes such safety monitoring devices prone to error

[0004] Furthermore, today's production equipment has higher requirements for the quality of operators. In traditional factories, it is difficult to distinguish the true quality of employees through manual observation by the line leader or workshop director or one or two skill assessment methods, which are often regarded as Most of the employees who are selected to operate those difficult and dangerous equipment are selected because of their excellent performance once or twice, which makes it very difficult to control the triggering factors of safety accidents in actual equipment operation. It is determined that the big data technology for cloud analysis is mature. If this method can be used to collect operator data in real time for analysis, the results obtained will obviously be more accurate than the traditional method, and the existing technology cannot meet the requirements of this idea. of

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