Tire mixing process safety emergency stop device based on intelligent AI vision

Abstract

The utility model relates to a kind of tire dense mixing process safety emergency stop device based on intelligent AI vision, belong to tire production field.Tire dense mixing machine is equipped, infrared camera is installed in tire dense mixing machine, networking communication is carried out between infrared camera signal output end and AI host computer input end through network, AI host computer output end is connected with equipment relay signal input end through signal line, equipment relay signal output end is connected with dense mixing machine control unit input end through signal line, and equipment relay signal output end is connected with alarm lamp through signal line.The utility model realizes all-around intelligent monitoring to tire dense mixing process, improves factory equipment production automation level and reduces operator safety risk.

Description

Technical Field

[0001] This utility model relates to the field of tire manufacturing, and more specifically, it is a safety emergency stop device for the tire mixing process based on intelligent AI vision. Background Technology

[0002] As is well known, current emergency stop devices for internal mixers in tire factories generally rely on manually triggered mechanical ropes or push-button switches, which have significant limitations in practical applications: First, emergency response depends entirely on the operator's subjective reaction. In emergency situations, personnel may become anxious, delay in operation, or misjudgment, leading to an escalation of the accident. This is especially true in the event of a sudden malfunction in a high-speed internal mixer, where the timeliness and reliability of manual intervention are difficult to guarantee. Second, while existing emergency stop devices effectively prevent personnel from entering the work area, their protection logic still has significant blind spots: a lack of real-time awareness of the status of personnel within the area. This leads to two risks: first, when equipment restarts unexpectedly or the program malfunctions, internal personnel may be exposed to a dangerous environment due to the failure of the protection system; second, when internal personnel perform non-standard operations (such as troubleshooting or temporary debugging), the system cannot verify the compliance of their behavior, potentially causing a safety accident due to the accidental triggering of the emergency stop device. Therefore, while retaining existing perimeter protection, biometric identification and behavioral analysis technologies should be used to achieve real-time monitoring of personnel identity authentication, operation authorization, and movement trajectories within the work area, forming a comprehensive, three-dimensional safety protection network covering all scenarios. Third, the current level of automation in internal mixing production is generally high, and personnel allocation has been significantly reduced. However, there are gaps in the transmission of emergency instructions between upstream and downstream processes, and a single emergency stop signal cannot trigger cross-unit linkage protection, leading to an increased risk of risk spread. In unmanned workshop scenarios, material abnormalities can also cause equipment failures, exposing the technological gap in existing emergency systems at the levels of proactive perception, intelligent decision-making, and full-domain collaboration. Summary of the Invention

[0003] To overcome the shortcomings of existing technologies, this utility model provides a safety emergency stop device for the tire mixing process based on intelligent AI vision, which realizes comprehensive intelligent monitoring of the tire mixing process.

[0004] The technical solution adopted by this utility model to solve its technical problem is: a safety emergency stop device for tire mixing process based on intelligent AI vision, which is equipped with a tire mixer. The tire mixer is characterized in that the tire mixer is equipped with an infrared camera. The signal output end of the infrared camera communicates with the input end of the AI ​​host through a network. The output end of the AI ​​host is connected to the signal input end of the equipment relay through a signal line. The signal output end of the equipment relay is connected to the input end of the mixer control unit through a signal line. The signal output end of the equipment relay is connected to the alarm light through a signal line.

[0005] The beneficial effects of this utility model are that it realizes comprehensive intelligent monitoring of the tire mixing process, improves the automation level of factory equipment production, and reduces the safety risks to operators. Attached Figure Description

[0006] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0007] Figure 1 The principle block diagram of this utility model.

[0008] In the diagram: 1. Infrared camera, 2. AI host, 3. Equipment relay, 4. Internal mixer control unit, 5. Alarm light. Detailed Implementation

[0009] In the figure, this utility model includes a tire mixer. The output of the infrared camera 1 installed on the tire mixer is networked with the input of the AI ​​host 2. The output of the AI ​​host 2 is connected to the signal input of the equipment relay 3 via a signal line. The signal output of the equipment relay 3 is connected to the input of the mixer control unit 4 via a signal line. The signal output of the equipment relay 3 is connected to the alarm light 5 via a signal line.

[0010] When the infrared camera 1 of the tire mixer detects unauthorized intrusion, unauthorized operation, abnormal tool abandonment, or non-programmed displacement of critical components / materials, it immediately transmits high-definition image data to the AI ​​host 2. The AI ​​host 2, equipped with an edge computing module and learning algorithm, can complete image recognition and risk level assessment within 500ms. After confirming the danger level, it sends an emergency stop command to the equipment relay 3 via a signal line. The equipment relay 3 simultaneously sends a command to the alarm light 5, and the mixer control unit 4 executes the command to immediately cut off the power supply. The alarm light 5 then triggers an audible and visual alarm. The entire system constructs a closed loop of "perception-analysis-decision-execution," achieving millisecond-level risk handling.

[0011] In terms of factory operations, this invention enables the system to identify risks such as material anomalies and equipment component malfunctions in real time, reducing the accident response time from the traditional 5-8 seconds to within 0.5 seconds for automatic emergency stop. This significantly reduces the occurrence of major safety accidents and minimizes ineffective downtime due to misjudgment, increasing the overall equipment utilization rate by 17%. Regarding personnel, intelligent AI vision technology can accurately distinguish between normal operations and violations, avoiding excessive intervention while ensuring operational safety. This reduces worker fatigue intensity by 42%, provides data support, and promotes the digital and intelligent transformation of production management, forming a closed-loop safety system of "perception-analysis-decision-execution".

Claims

1. A safety emergency stop device for tire mixing process based on intelligent AI vision, comprising a tire mixer, characterized in that, The tire mixer is equipped with an infrared camera. The signal output of the infrared camera communicates with the input of the AI ​​host via a network. The output of the AI ​​host is connected to the signal input of the equipment relay via a signal line. The signal output of the equipment relay is connected to the input of the mixer control unit via a signal line. The signal output of the equipment relay is connected to the alarm light via a signal line.

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