CN-121974113-A - Intelligent sensor conveying system

CN121974113ACN 121974113 ACN121974113 ACN 121974113ACN-121974113-A

Abstract

The invention relates to an intelligent sensor conveying system, which relates to the technical field of precision manufacturing and industrial automation, and comprises a plurality of intelligent conveying units with embedded sensing and edge computing capabilities, a global environment sensing unit which is formed by intelligent sensing anchor points distributed on fixed nodes, and a central collaborative decision platform, wherein the platform fuses multi-source data through a global digital twin body construction module to form a virtual mapping model, a risk simulation prediction module carries out advanced motion state deduction on the conveying units based on a physical simulation model to predict risks such as instability and collision, a dynamic collaborative planning module dynamically re-plans paths, speeds and multi-unit collaborative time sequences according to the results, and the spanning from passive reaction to active prediction and single machine control to global dynamic collaborative is realized, so that the problems of safety, efficiency and adaptability of a conveying process in a complex scene are solved.

Inventors

CHEN SHISHEN
XIAO JUN
Zeng Gaosheng

Assignees

广州景研智能科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260130

Claims (9)

1. A sensor intelligent transportation system, comprising: The intelligent conveying units comprise a bearing platform for bearing a sensor, an embedded sensing module for acquiring data, a first environment sensing sub-module for acquiring local obstacle information of the whole body of the unit, an edge computing control module for processing the original data of the embedded sensing module and the first environment sensing sub-module and further computing unit state data, and a first communication module for transmitting the unit state data; The global environment sensing unit is composed of a plurality of intelligent sensing anchor points which are distributed at fixed nodes in the conveying space, and each anchor point comprises a second environment sensing sub-module, a road surface state sensing module and a second communication module, wherein the second environment sensing sub-module is used for acquiring vibration frequency spectrums, temperature and humidity of positions of the anchor points and original data of multi-view visual information, the road surface state sensing module is used for detecting the flatness or bearing capacity change of a road surface at the anchor points, and the second communication module is used for generating data of the second environment sensing sub-module and the road surface state sensing module in a fitting mode to form environment sensing data; The central collaborative decision-making platform is used for being in communication connection with a plurality of intelligent delivery units and a plurality of intelligent perception anchor points of the global environment perception unit, and comprises: The global digital twin body construction module is used for fusion construction and continuous updating of a virtual mapping model containing dynamic attributes of a plurality of intelligent conveying units and global environment static/dynamic attributes based on the unit state data and the environment perception data received in real time; The risk simulation prediction module is used for carrying out deduction calculation on the motion states of a plurality of intelligent conveying units in a future preset time window through a preset physical simulation model based on the virtual mapping model, predicting potential instability, collision or path failure risks and outputting risk types, risk probabilities and risk positions; And the dynamic collaborative planning module is used for responding to the output data of the risk simulation prediction module, taking the optimal overall throughput efficiency of the system and the lowest comprehensive risk as multiple targets, and dynamically re-planning a subsequent path section for the intelligent conveying unit affected by the risk, wherein the re-planning comprises path geometry adjustment, speed curve optimization and traffic time sequence collaboration among all units.
2. The intelligent sensor delivery system of claim 1, wherein the embedded sensing module comprises: the micro-pressure sensing array is embedded in the lower surface or the inside of the bearing platform in an M multiplied by N matrix form and is used for acquiring pressure distribution original data of a load on the bearing platform in real time; and the gesture sensing array is integrated in the intelligent conveying unit and is used for acquiring acceleration, angular speed and inclination angle data of the bearing platform in a three-dimensional space in real time.
3. The intelligent sensor transportation system according to claim 2, wherein the edge calculation control module is specifically configured to: calculating a two-dimensional static pressure center coordinate of the load on the plane of the bearing platform based on the pressure distribution original data acquired by the micro pressure sensing array; based on the inclination angle data acquired by the gesture sensing array, performing inclination angle compensation calculation on the two-dimensional static pressure center coordinate, and further calculating a three-dimensional dynamic gravity center estimated coordinate of the load under the current gesture; Based on the calculated three-dimensional dynamic gravity center estimated coordinates, the real-time attitude data and the local obstacle abstract information processed by the first environment perception submodule, fitting and packaging the three-dimensional dynamic gravity center estimated coordinates, the real-time attitude data and the local obstacle abstract information into the unit state data.
4. The intelligent sensor transportation system according to claim 3, wherein when the risk simulation prediction module performs deduction calculation on the risk of instability, the intelligent sensor transportation system is specifically configured to: Aiming at a target intelligent conveying unit, extracting corresponding current motion parameters, the three-dimensional dynamic gravity center estimated coordinates and curvature and gradient information of a planned path from the virtual mapping model; And iteratively calculating the deviation track of the three-dimensional dynamic gravity center estimated coordinates relative to the bearing platform and the attitude angle change of the intelligent conveying unit in a future preset time window based on the preset physical simulation model by taking the information as input, and judging that the dynamic instability risk exists when the predicted maximum deviation exceeds a first safety threshold or the predicted maximum attitude angle change rate exceeds a second safety threshold.
5. The intelligent sensor delivery system according to claim 4, wherein the dynamic collaborative planning module is configured to, when rescheduling a path for an intelligent delivery unit determined to be at risk of dynamic instability: And in the selectable path set, preferentially screening paths with the comprehensive stability index higher than a preset value, wherein the comprehensive stability index is comprehensively calculated according to the average curvature and the maximum gradient of the path section and the road surface vibration spectrum energy of the path section provided by the global environment sensing unit, and matching corresponding deceleration motion parameters for the screened paths, wherein the deceleration motion parameters comprise a maximum allowable speed and a maximum allowable acceleration lower than the original plan.
6. The intelligent sensor transportation system according to claim 1, wherein the dynamic collaborative planning module is configured to: When the planned paths of the intelligent conveying units have crossed or overlapped conflict areas in time and space, calculating a dynamic priority value for each related unit, wherein the dynamic priority value is obtained by weighting and fusing based on the preset priority of the goods loaded by the unit, the instant risk level output by the risk simulation prediction module and the remaining time urgency of the task; And based on the height of the dynamic priority value, a differentiated passing time window is allocated for the conflict area, and an avoidance scheme comprising a deceleration waiting area or a miniature detour path is generated for the unit with low priority value.
7. The sensor intelligent transportation system of claim 1, wherein the central collaborative decision-making platform further comprises: The strategy evaluation self-learning module is used for continuously collecting historical data, wherein the historical data comprises a risk prediction record, an executed re-planning strategy, and an actually-occurring conveying result and a system state; and analyzing the historical data based on a machine learning algorithm, establishing a correlation model of a prediction result and actual risks, and dynamically adjusting parameters of a physical simulation model in the risk simulation prediction module and/or decision weight factors in the dynamic collaborative planning module based on the model.
8. The sensor intelligent transportation system of any one of claims 1-7, wherein said edge calculation control module is further configured with autonomous emergency control logic that is triggered when a communication link of said first communication module with a central collaborative decision-making platform is broken, said autonomous emergency control logic comprising: Based on the data of the local embedded perception module and the first environment perception sub-module, calculating a local safety index in real time; And if the local safety index is deteriorated to an emergency threshold, independently deciding to execute hierarchical braking operation or enter a safe parking state, and executing local static obstacle avoidance based on the information of the first environment-aware submodule before communication is restored.
9. A sensor intelligent transportation method based on the sensor intelligent transportation system of any one of claims 1-8, comprising: Step S1, a plurality of intelligent conveying units collect local original data through an embedded sensing module and a first environment sensing submodule, generate unit state data after being processed by an edge calculation control module and send the data; S2, the central collaborative decision-making platform receives unit state data and environment perception data, and updates a virtual mapping model through a global digital twin body building module; step S3, a risk simulation prediction module performs motion state deduction and risk prediction in a rolling time window on all the on-the-way intelligent conveying units based on the updated virtual mapping model; Step S4, if the risk is not predicted, each intelligent conveying unit continuously operates according to the original instruction, and if the risk is predicted, the dynamic collaborative planning module generates a re-planning instruction set comprising a path, a speed and a collaborative time sequence aiming at a unit set of the affected intelligent conveying unit and aiming at global optimization; S5, the central collaborative decision-making platform issues a re-planning instruction set to a corresponding intelligent conveying unit; and S6, the intelligent conveying unit executes a new instruction, feeds back an execution state to the central collaborative decision-making platform, and finally returns to the step S1 to form a closed-loop control flow.

Description

Intelligent sensor conveying system Technical Field The invention relates to the technical field of precision manufacturing and industrial automation, in particular to an intelligent sensor conveying system. Background In the manufacturing process of high-end sensors, such as high-performance MEMS inertial sensors, high-resolution optical sensors and precision pressure sensors, the transportation of wafers, bare chips or packaged finished products among packaging, testing, calibrating and assembling procedures is a key weak link affecting the performance and yield of the final products. The sensor has the characteristics of high value, fine internal structure, extremely sensitive mechanical stress and micro vibration, strict requirement on the cleanliness of the production environment and the like; The existing material conveying scheme in the production line mainly depends on a traditional conveyor belt, an air floating platform or a universal automatic guided vehicle. These solutions have the inherent drawback of not meeting the specific requirements of highly sensitive sensor delivery, firstly, in terms of vibration control, the existing systems lack the ability to monitor in real time and actively suppress the micro-vibrations conducted to the sensor body. Secondly, in terms of state sensing and coordination, the existing system can only realize basic positioning and obstacle avoidance, can not sense six-degree-of-freedom micro-gesture, stress distribution and local micro-environment change of a sensor carrier in the conveying process in real time, can not perform advanced prediction and dynamic optimization based on the data, and cooperative scheduling among multiple devices only aims at preventing physical collision and can not realize vibration phase staggering and undisturbed engagement meeting the precision assembly time sequence requirement; At present, although an independent precise vibration isolation platform is used for static test or a clean transfer box is used locally, the comprehensive challenges faced by a sensor in long-distance, multi-node and dynamic continuous production circulation cannot be solved, so that a special conveying system integrating micro-vibration active management, cleanliness dynamic maintenance, high-precision state sensing and intelligent collaborative decision is urgently needed in the field of sensor manufacturing, and the transition from simple transportation to controllable, measurable and nondestructive precise transportation is realized, and the high performance and high yield of products are ensured. Disclosure of Invention Aiming at the defects existing in the prior art, the invention aims to provide an intelligent sensor conveying system for solving the problems existing in the background art. The technical aim of the invention is achieved by the following technical scheme that the intelligent sensor conveying system comprises: The intelligent conveying units comprise a bearing platform for bearing a sensor, an embedded sensing module for acquiring data, a first environment sensing sub-module for acquiring local obstacle information of the whole body of the unit, an edge computing control module for processing the original data of the embedded sensing module and the first environment sensing sub-module and further computing unit state data, and a first communication module for transmitting the unit state data; The global environment sensing unit is composed of a plurality of intelligent sensing anchor points which are distributed at fixed nodes in the conveying space, and each anchor point comprises a second environment sensing sub-module, a road surface state sensing module and a second communication module, wherein the second environment sensing sub-module is used for acquiring vibration frequency spectrums, temperature and humidity of positions of the anchor points and original data of multi-view visual information, the road surface state sensing module is used for detecting the flatness or bearing capacity change of a road surface at the anchor points, and the second communication module is used for generating data of the second environment sensing sub-module and the road surface state sensing module in a fitting mode to form environment sensing data; The central collaborative decision-making platform is used for being in communication connection with a plurality of intelligent delivery units and a plurality of intelligent perception anchor points of the global environment perception unit, and comprises: The global digital twin body construction module is used for fusion construction and continuous updating of a virtual mapping model containing dynamic attributes of a plurality of intelligent conveying units and global environment static/dynamic attributes based on the unit state data and the environment perception data received in real time; The risk simulation prediction module is used for carrying out deduction calculation on the motion states of a