Intelligent anti-collision management system for hardware area

Abstract

The invention discloses an intelligent anti-collision management system for a hardware area. The intelligent anti-collision management system comprises a receiving unit, a processing unit, an analysis unit, a judgment unit, an execution unit and an emergency unit, the receiving unit is used for receiving data information of various sensors in a hardware area, the processing unit adopts a specific data processing algorithm to carry out deep processing and data fusion on the received data, the analysis unit carries out collision risk assessment and path planning analysis according to the processed data, and the judgment unit makes decision judgment according to an analysis result. The execution unit generates a control instruction according to a decision result of the judgment unit and drives the hardware equipment to execute corresponding operation; the emergency unit can rapidly start an independent emergency processing mechanism to guarantee the safety of hardware equipment and personnel, the invention relates to the technical field of data processing, and through multi-dimensional real-time monitoring and risk assessment and countermeasures, the probability of occurrence of collision accidents is effectively reduced, and reliable safety guarantee is provided for the hardware equipment and personnel.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an intelligent anti-collision management system for a hardware area. Background Art

[0002] In areas where various hardware devices are densely populated, such as factory workshops, logistics storage centers, etc., collision accidents between hardware devices frequently occur, which not only causes equipment damage, production interruptions, and increased operating costs, but may also pose a serious threat to the safety of workers. Most of the existing anti-collision measures have limited effects and low intelligence levels, and cannot meet the needs of efficient and safe management in complex hardware areas. Therefore, an innovative intelligent anti-collision management system is urgently needed to solve these problems. Summary of the invention

[0003] The purpose of the present invention is to provide an efficient, accurate and reliable intelligent anti-collision management system that can monitor the status and operating parameters of hardware equipment in real time, accurately assess the risk of collision, and take effective avoidance measures and emergency treatment in a timely manner to maximize the safety of hardware equipment and personnel.

[0004] In view of the shortcomings of the prior art, the present invention solves the technical problems by adopting the following technical solutions: an intelligent anti-collision management system for a hardware area, comprising a receiving unit, a processing unit, an analyzing unit, a judging unit, an executing unit and an emergency unit;

[0005] The receiving unit is used to receive data information from various sensors in the hardware area, and obtain a fusion signal after preliminary sorting and encoding, and then transmit the fusion signal to the processing unit;

[0006] The processing unit uses a specific data processing algorithm to perform in-depth processing and data fusion on the received data, and transmits the results to the analysis unit;

[0007] The analysis unit performs collision risk assessment and path planning analysis based on the processed data, and transmits the analysis results to the judgment unit;

[0008] The judgment unit makes a decision based on the analysis results, determines whether avoidance measures need to be taken, sets priorities when there is a risk of collision between multiple devices, and generates a decision result;

[0009] The execution unit generates a control instruction according to the decision result of the judgment unit and drives the hardware device to perform a corresponding operation;

[0010] When the risk of collision is extremely high and the system fails, the emergency unit can quickly activate an independent emergency response mechanism to ensure the safety of hardware equipment and personnel.

[0011] Preferably, the sensors in the receiving unit include a distance sensor, a position sensor and an acceleration sensor. The distance sensor adopts infrared or ultrasonic technology, and the monitoring frequency is not less than 2000 times per second. The position sensor includes a comprehensive position sensor composed of a photoelectric encoder and a photoelectric displacement sensor.

[0012] Preferably, the processing unit uses a Kalman filter algorithm to optimize the position data, and adopts a specific data fusion algorithm to perform secondary fusion on the data of different types of sensors, and assigns corresponding weights according to the accuracy and reliability of different sensors.

[0013] Preferably, the analysis unit establishes a collision risk model, combines the speed, distance, acceleration parameters of the device and historical collision data to perform machine learning training, calculates the risk assessment index and level, and obtains the risk assessment result. The specific grading method is as follows:

[0014] Set the speed safety threshold range S1;

[0015] Speed ​​parameters: Level 1 high risk, when the relative speed of multiple hardware devices is S'1>1.5S1, Level 2 medium risk, relative speed is 1.2S1≤S"1≤1.5S1, Level 3 low risk, relative speed is S1<S"'1<1.2S1, unit is m / s, output speed danger index V;

[0016] Set the distance safety threshold range S2;

[0017] Distance parameters: Level 3 low risk, when the straight-line distance between multiple hardware devices is S'2>1.5S2; Level 2 medium risk, when the straight-line distance is S2≤S"2≤1.5S2; Level 1 high risk, when the straight-line distance is S'2<S2 in centimeters, and the output distance danger index is L;

[0018] Set the acceleration safety threshold range S3;

[0019] Acceleration parameters: Level 1 high risk, when the acceleration of a single hardware device S'3>1.5S3, Level 2 medium risk 1.2S3≤S"3≤1.5S3, Level 3 low risk 1.2S3≤S"3≤1.5S3, unit meter per second squared, output acceleration hazard index α;

[0020] If V, L and α are all level 1 high risk, the risk assessment result is urgent; if any two of V, L and α are high risk, the risk assessment result is dangerous; if any one of V, L and α is high risk, the risk assessment result is general. Except for the above three cases, the rest are controllable parameters and the default risk assessment result is low risk;

[0021] Based on the risk assessment results, the collision risk assessment model uses a path planning algorithm to calculate the optimal avoidance path based on the terrain and obstacle factors in the hardware area, and obtains path planning suggestions; based on the data and feedback information accumulated during the system operation, the collision risk assessment model and path planning algorithm are continuously optimized to improve the performance and accuracy of the system.

[0022] Strengthen integration and collaboration with other equipment management systems, realize information sharing and collaborative work, and improve the management level of the entire hardware area.

[0023] Preferably, the judgment unit makes a decision based on the collision risk assessment results and the path planning suggestions, and sets priorities based on the importance and urgency of the devices when there is a collision risk for multiple devices at the same time.

[0024] Preferably, the execution unit generates control instructions including acceleration, deceleration, stopping and steering operations, and drives the execution mechanism to implement corresponding operations by connecting with the hardware device control system.

[0025] Preferably, the emergency unit has an independent power supply and control system, and can quickly sound an alarm and take emergency measures such as emergency braking and activating safety protection devices in an emergency.

[0026] Preferably, the photoelectric encoder is composed of a code disk and a photoelectric detection device. The code disk has regularly arranged light-transmitting and light-impermeable areas. When the code disk rotates with the object to be measured, the photoelectric detection device, i.e., the photodiode, receives the light signal transmitted through the code disk and converts it into an electrical signal. According to the change rule of the light signal, the rotation angle and displacement of the code disk can be determined, thereby obtaining the position information of the object;

[0027] The photoelectric displacement sensor consists of a light source, a light detector and a reflective surface. The light emitted by the light source shines on the reflective surface and is then reflected back. The light detector receives the reflected light. When the position of the reflective surface changes, parameters such as the intensity, angle or time of the reflected light will also change accordingly. By measuring the changes in these parameters, the displacement of the reflective surface, that is, the object being measured, can be calculated.

[0028] The beneficial effects of the present invention are as follows:

[0029] Improve safety: Through multi-dimensional real-time monitoring and accurate risk assessment and response measures, the probability of collision accidents is effectively reduced, providing reliable safety protection for hardware equipment and personnel.

[0030] Ensure production continuity: Reduce equipment damage and production interruptions caused by collisions, improve the operating stability and reliability of hardware equipment, and help ensure continuous production.

[0031] Intelligent management: It realizes automated monitoring, analysis and decision-making, reduces reliance on human intervention, and improves management efficiency and accuracy.

[0032] Strong adaptability: It can adapt to different types of hardware areas and devices and has a wide range of application prospects BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a system block diagram of the present invention;

[0034] Figure 2 is a block diagram of a receiving unit of the present invention;

[0035] Figure 3 It is a data flow diagram of the present invention. DETAILED DESCRIPTION

[0036] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0037] refer to Figure 1-Figure 3 The intelligent anti-collision management system of the present invention is mainly composed of a receiving unit, a processing unit, an analyzing unit, a judging unit, an executing unit and an emergency unit.

[0038] The detailed functions and implementation methods of each unit are as follows:

[0039] Receiving unit:

[0040] The receiving unit is responsible for receiving data information from various sensors in the hardware area, including distance sensors, position sensors (combined position sensors composed of photoelectric encoders and photoelectric displacement sensors) and acceleration sensors;

[0041] The distance sensor uses infrared or ultrasonic technology, with a monitoring frequency of no less than 2000 times per second, and can accurately measure the relative distance between devices;

[0042] The photoelectric encoder consists of a code disk and a photoelectric detection device. The rotation angle and displacement of the code disk are determined by the change law of the light signal, and then the position information of the object is obtained. The photoelectric displacement sensor calculates the displacement of the measured object by measuring the change of the reflected light parameters;

[0043] The receiving unit preliminarily organizes and encodes the received data to obtain a fused signal, and transmits it to the processing unit.

[0044] Processing Unit:

[0045] The processing unit uses the Kalman filter algorithm to optimize the position data, reduce the position data error, and improve the data accuracy;

[0046] At the same time, a specific data fusion algorithm is used to perform secondary fusion of data from different types of sensors, and corresponding weights are assigned according to the accuracy and reliability of different sensors, providing a stable data basis for subsequent analysis.

[0047] Analysis unit:

[0048] The analysis unit performs collision risk assessment and path planning analysis based on the processed data;

[0049] Collision risk assessment establishes a collision risk model, combines the speed, distance, acceleration parameters of the device and historical collision data for machine learning training, and calculates the risk assessment index and level;

[0050] In terms of speed parameters, the speed safety threshold range is set, which is divided into level 1 high risk, level 2 medium risk and level 3 low risk according to the relative speed, and the speed danger index (unit: m / s) is output;

[0051] In terms of distance parameters, the distance safety threshold range is also set, which is divided into three levels of low risk, two levels of medium risk and one level of high risk (unit: centimeters) according to the straight-line distance between multiple hardware devices, and the distance danger index is output;

[0052] In terms of acceleration parameters, the acceleration safety threshold range is set, which is divided into level 1 high risk, level 2 medium risk and level 3 low risk (unit: meters per second squared) according to the acceleration of individual hardware devices, and the acceleration hazard index is output;

[0053] Based on the comprehensive judgment of the risk level of speed, distance and acceleration, if all three are level one high risk, the risk assessment result is urgent; if any two are high risk, the risk assessment result is dangerous; if any one is high risk, the risk assessment result is general; except for the above three situations, the default risk assessment result is low risk;

[0054] Based on the risk assessment results, the collision risk assessment model uses a path planning algorithm to fully consider the terrain and obstacle factors in the hardware area, calculate the optimal avoidance path, and obtain path planning suggestions.

[0055] Judgment unit:

[0056] The judgment unit makes a decision based on the collision risk assessment results and path planning suggestions provided by the analysis unit to determine whether avoidance measures need to be taken.

[0057] When multiple devices are at risk of collision, set priorities based on the importance and urgency of the devices.

[0058] Execution Unit:

[0059] The execution unit generates control instructions according to the decision results of the judgment unit, including acceleration, deceleration, stopping and steering operations, and drives the actuator to perform corresponding operations by connecting with the hardware device control system to avoid collision accidents.

[0060] Emergency Unit:

[0061] The emergency unit comes into play in situations where the risk of a collision is extremely high or there is a system failure;

[0062] It has an independent power supply and control system, can quickly sound an alarm, and take emergency measures such as emergency braking and activating safety protection devices to ensure the safety of hardware equipment and personnel.

[0063] Install various sensors in the hardware area to ensure that the connection between the sensor and the receiving unit is stable and reliable. Install and configure the processing unit, analysis unit, judgment unit, execution unit and emergency unit according to the characteristics of the equipment and environmental requirements, and adjust the parameters and algorithms of each unit to adapt it to the specific application scenario.

[0064] Before use, the power supply and control system of the emergency unit shall be independently installed and tested to ensure that it can work normally in an emergency;

[0065] After the system is started, the receiving unit receives sensor data in real time, and the data is processed by the processing unit, analysis unit and judgment unit in turn. The execution unit controls the operation of the hardware device according to the decision results.

[0066] The monitoring system in the emergency unit displays the location, status, collision risk information and system operation status of the equipment in real time, so that the management personnel can understand the operation of the system at any time, so that the emergency unit can timely discover and handle abnormal situations. When the judgment unit determines that there is no collision risk, the receiving unit re-transmits the data to the processing unit. When the judgment unit determines that there is a collision risk, the execution unit drives the driving actuator to adjust the speed and angle of the hardware equipment, and then feeds back the control results to the analysis unit for secondary analysis and subsequent risk assessment and judgment until the feedback results are at a normal level. In this process, in the case of extremely high collision risk, system failure or extremely dangerous sensor parameters, the execution unit may not be able to perform protective actions in time. At this time, the emergency unit, through its independently set power supply, driven by its internal control system, drives the safety protection device to start by receiving the action instructions of the execution unit, and assists the driving actuator to work. When the sensor parameters are extremely dangerous, in order to avoid the redundancy of subsequent data analysis calculations, resulting in data output delays and execution lags, the emergency unit can directly bypass the processing unit, analysis unit, judgment unit and execution unit, and directly issue execution instructions to its internal safety protection device to improve efficiency.

[0067] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. An intelligent anti-collision management system for a hardware area, characterized in that: It includes a receiving unit, a processing unit, an analyzing unit, a judging unit, an executing unit and an emergency unit; The receiving unit is used to receive data information from various sensors in the hardware area, and obtain a fusion signal after preliminary sorting and encoding, and then transmit the fusion signal to the processing unit; The processing unit uses a specific data processing algorithm to perform in-depth processing and data fusion on the received data, and transmits the results to the analysis unit; The analysis unit performs collision risk assessment and path planning analysis based on the processed data, and transmits the analysis results to the judgment unit; The judgment unit makes a decision based on the analysis results, determines whether avoidance measures need to be taken, sets priorities when there is a risk of collision between multiple devices, and generates a decision result; The execution unit generates a control instruction according to the decision result of the judgment unit and drives the hardware device to perform a corresponding operation; When the risk of collision is extremely high and the system fails, the emergency unit can quickly activate an independent emergency response mechanism to ensure the safety of hardware equipment and personnel.

2. The intelligent anti-collision management system for hardware area according to claim 1, characterized in that: The sensors in the receiving unit include a distance sensor, a position sensor and an acceleration sensor. The distance sensor uses infrared or ultrasonic technology, and the monitoring frequency is not less than 2000 times per second. The position sensor includes a comprehensive position sensor composed of a photoelectric encoder and a photoelectric displacement sensor.

3. The intelligent anti-collision management system for hardware area according to claim 1, characterized in that: The processing unit uses a Kalman filter algorithm to optimize the position data, and adopts a specific data fusion algorithm to perform secondary fusion on the data of different types of sensors, and assigns corresponding weights according to the accuracy and reliability of different sensors.

4. The intelligent anti-collision management system for hardware area according to claim 1, characterized in that: The analysis unit establishes a collision risk model, combines the speed, distance, acceleration parameters of the device and historical collision data to perform machine learning training, calculates the risk assessment index and level, and obtains the risk assessment result. The specific grading method is as follows: Set the speed safety threshold range S1; Speed ​​parameters: Level 1 high risk, when the relative speed of multiple hardware devices is S'1>1.5S1, Level 2 medium risk, relative speed is 1.2S1≤S"1≤1.5S1, Level 3 low risk, relative speed is S1<S"'1<1.2S1, unit is m / s, output speed danger index V; Set the distance safety threshold range S2; Distance parameters: Level 3 low risk, when the straight-line distance between multiple hardware devices is S'2>1.5S2; Level 2 medium risk, when the straight-line distance is S2≤S"2≤1.5S2; Level 1 high risk, when the straight-line distance is S'2<S2 in centimeters, and the output distance danger index is L; Set the acceleration safety threshold range S3; Acceleration parameters: Level 1 high risk, when the acceleration of a single hardware device S'3>1.5S3, Level 2 medium risk 1.2S3≤S"3≤1.5S3, Level 3 low risk 1.2S3≤S"3≤1.5S3, unit meter per second squared, output acceleration hazard index α; If V, L and α are all level 1 high risk, the risk assessment result is urgent; if any two of V, L and α are high risk, the risk assessment result is dangerous; if any one of V, L and α is high risk, the risk assessment result is general. Except for the above three cases, the rest are controllable parameters and the default risk assessment result is low risk; Based on the risk assessment results, the collision risk assessment model uses a path planning algorithm to calculate the optimal avoidance path based on the terrain and obstacle factors in the hardware area and obtain path planning recommendations.

5. The intelligent anti-collision management system for hardware area according to claim 4, characterized in that: The judgment unit makes a decision based on the collision risk assessment result and the path planning suggestion, and sets the priority according to the importance and urgency of the equipment when multiple equipments have collision risks at the same time.

6. The intelligent anti-collision management system for hardware area according to claim 1, characterized in that: The execution unit generates control instructions including acceleration, deceleration, stopping and steering operations, and drives the execution mechanism to implement corresponding operations by connecting with the hardware device control system.

7. The intelligent anti-collision management system for hardware area according to claim 2, characterized in that: The emergency unit is equipped with an independent power supply and control system, and can quickly sound an alarm and take emergency measures such as emergency braking and starting safety protection devices in an emergency.

8. The intelligent anti-collision management system for hardware area according to claim 7, characterized in that: The photoelectric encoder is composed of a code disk and a photoelectric detection device. The code disk has regularly arranged light-transmitting and light-impermeable areas. When the code disk rotates with the object being measured, the photoelectric detection device, i.e., the photodiode, receives the light signal transmitted through the code disk and converts it into an electrical signal. According to the change rule of the light signal, the rotation angle and displacement of the code disk can be determined, thereby obtaining the position information of the object. The photoelectric displacement sensor consists of a light source, a light detector and a reflective surface. The light emitted by the light source shines on the reflective surface and is then reflected back. The light detector receives the reflected light. When the position of the reflective surface changes, parameters such as the intensity, angle or time of the reflected light will also change accordingly. By measuring the changes in these parameters, the displacement of the reflective surface, that is, the object being measured, can be calculated.

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