通过数据增强的电脑数值控制刀具磨损状态监测和预测系统和方法

HKSAR

32023067677.9

The present invention discloses a tool wear condition prediction and monitoring system based on machine learning, comprising of: a user interface (102) with machine (102a) and scheduling frontends (102b); a software hub (104) for providing data collection (104a), data processing (104b), data storage (104c) and device management (104d); a machine learning prediction model (106), characterized by; a feature extraction module (106a) configured to extract features; a data generation module (404) configured to generate synthetic features (302); and a prediction module (406) that is configured to predict a tool wear condition.

基于物品扫描进行重心评估的方法及机械手抓取物品的方法

HKSAR

32024092278.3

用于分拣精密细粒度物体的多传感器机器人感知与定位系统

HKSAR / PRC

HKSAR: 32024096292.0 / PRC: 2024112757393

Robotic perception and positioning system for sorting precision fine-grained object

CargoFlow: Advanced Congestion Detection and Root Cause Analysis System for Air Cargo Logistics

US

63/689,775

反射式表面缺陷检测装置

HKSAR

32023083911.2

The present invention relates to a system for capturing defects on a surface of an object in a single-camera setup. By using multiple cameras, different perspectives of the object can be obtained, allowing for better coverage and a more comprehensive examination of the surface. As irregular shapes may have varying depths, concavities, or protrusions that cannot be adequately captured by a common single camera setup, multiple cameras are therefore positioned at different angles to enable better depth perception and accurate identification of defects in three-dimensional space.

一种基于一维resunet的电梯振动信号去噪方法

PRC

2410021289.9

本申请涉及电梯技术领域，特别涉及一种电梯振动信号去噪方法、装置、电子设备及存储介质，其中，方法包括：采集电梯的轿厢垂直振动信号，并生成原始一维时间序列信号；将不同类型、不同强度的噪声注入到原始一维时间序列信号，得不同类型的一维含噪混合信号；采用滑动窗口方式分割生成目标长度的数据样本并划分为训练集、验证集和测试集；构建ResUNet深度神经网络并采用训练集对ResUNet训练直至网络收敛，采用验证集对超参数调整，获得训练完成的网络模型；将测试集的含噪振动信号输入到训练完成的网络模型进行预测，输出去噪后的振动信号。由此，解决了相关技术中，由于需要依赖电梯振动信号的先验知识或参数的人为设定，影响去噪的有效性和可靠性等问题。

机械抓手及利用其拿放物体的方法

HKSAR / PRC

HKSAR: 32023075720.7 / PRC: CN 202310853939.1

本发明公开了一种机械抓手，所述机械抓手包括安装支架以及阵列式布置在所述安装支架上的、用于吸取物体的多个吸取部，每一吸取部沿其吸取方向长度可调节。 本发明提供的机械抓手具有良好的普适性，也公开了一种利用机械抓手拿放物体的方法。

自动引导车路径规划方法、电子设备及存储介质

PRC

202410439782.2

本申请实施例提供了一种自动引导车路径规划方法、电子设备及存储介质，属于路径规划技术领域。该方法包括：从网格网络中筛选出初始网格的一跳网格，得到第一候选网格。构建第一候选网格的第一搜索状态信息，并保存到队列中。获取队列中第一最早时间戳最小的第一搜索状态信息，对应的第一候选网格为第一目标网格。若第一目标网格不属于预设的目标位置，和/或当前运动状态为移动状态，则筛选出第一目标网格的一跳网格，得到更新的第一候选网格。重复上述步骤，直至第一目标网格为目标位置，且当前运动状态为静止状态。根据初始网格的第一搜索状态信息和所有选择出的第一搜索状态信息构建自动引导车的运动路径，提高了AGV的实际运行效率。

利用BIM实现机器人自主导航的方法

HKSAR

32023079478.8

A Method for realizing autonomous navigation of robots using BIM, first, the BIM model is used to generate a navigation map, and then the site is optically scanned through 3D scanning to obtain on-site point cloud images and semantic segmentation is performed to obtain a semantic map. The robot uses the semantic map to achieve autonomous navigation. The method of using BIM model to map conversion and semantic understanding to realize autonomous navigation of robots can overcome the obstacles of existing robot platforms in realizing automation and other related fields, and increase the autonomy of robots.

物流中心的运输流程瓶颈检测及预测方法

HKSAR / PRC

HKSAR: 32023070062.9 / PRC: 202310280578.6

用于检测物体表面缺陷的系统及方法

HKSAR / PRC

HKSAR: 32023070552.9 / PRC: CN 202310309532.2

基于少量正常样本数据集训练的缺陷检测方法及装置

HKSAR / PRC

HKSAR : 32022066158.3 / PRC: CN202211689395.1

一种基于机械臂手眼系统的三维重建的物体表面检测方法

HKSAR / PRC

HKSAR: 32022062462.3 / PRC : CN202211288329.3

干扰检测与对策建议系统及其方法

HKSAR

32023083910.4

The present invention relates to a system (100) and a method (200) to detect and classify disturbances and derive countermeasures, characterised by: a data component module (101), a deviation reporting module (1021) consisting of a multi-level data analysis module (1021), a deviation detection module (1022) and a conformance checking module (1023), a disturbance diagnosis module (103) consisting of a classifier module (1031) and a countermeasures module (1032); and a user interface module (104) configured to display disturbances obtained from the countermeasures module (1032), wherein disturbances are detected, diagnosed and classified using the deviation reporting module (102) and the disturbance diagnosis module (103) for automatically suggesting countermeasures.

用于注塑工序的质量预测和根本原因分析系统和方法

HKSAR / PRC

HKSAR: 32022062264.3 / PRC: CN202310827739.9

本发明涉及一种基于AI的系统，其用于分析在先前执行的制造操作中获得的各种数据，用于执行质量预测和根本原因分析，以确定在制造工序中导致生产偏差的一个或多个可能的根本原因。

一种工具磨损状况监测系统

HKSAR / PRC

HKSAR: 32023071003.2 / PRC: 202420628565.3

本申请公开了一种工具磨损状态监测系统，其包括：被配置为安装在工具的主轴处并用于测量主轴的声发射讯号的声发射传感器（102a）；被配置为安装在工具的工件固定装置处并用于测量工件的振动讯号的振动传感器（102b）；被配置为安装在工具的主轴电机处并用于测量主轴电机的电流的电流传感器（102c）；及监控设备。所述监控设备包括：数据采集模块，用于从声发射传感器（102a）、振动传感器（102b）及电流传感器（102c）接收相应讯号；仪表板，用于将工具的磨损状态显示给用户。本实用新型能够适应、安装和调整多个传感器以适应工业中各种计算机化数控机器环境，从而在各种环境下均能较好地监测工具磨损状态。

Method And System Of Cloud-Based Cad Automatic Assembly Sequence Planning

HKSAR

32023070184.1

The present invention discloses a system of automatic assembly sequence planning for cloud-based computer-aided design (CAD), comprising of: a computer device of a CAD model having a processor and non-transient media; a cloud-based computer server having a processor and non-transient media for a cloud-based CAD software program for assembly sequence planning (102); wherein the cloud-based CAD software program for assembly sequence planning (102) includes instructions for: data extraction (302); automatic constraint modelling; optimized assembly sequence generation; visualization of optimal assembly sequence (312); and a user interface for providing an optimal users interaction in the cloud-based CAD software program for assembly sequence planning (102).

用于自动化组装顺序规划的云计算辅助设计的方法与系统

HKSAR

32023070184.1

The present invention discloses a system of automatic assembly sequence planning for cloud-based computer-aided design (CAD), comprising of: a computer device of a CAD model having a processor and non-transient media; a cloud-based computer server having a processor and non-transient media for a cloud-based CAD software program for assembly sequence planning (102); wherein the cloud-based CAD software program for assembly sequence planning (102) includes instructions for: data extraction (302); automatic constraint modelling; optimized assembly sequence generation; visualization of optimal assembly sequence (312); and a user interface for providing an optimal users interaction in the cloud-based CAD software program for assembly sequence planning (102).

列车月台的幕门的故障风险预测系统

HKSAR / PRC

HKSAR : 32023068412.0 / PRC: 202310165356.X

本申请公开了一种列车月台的幕门的故障风险预测系统，包括设置在幕门的多个预定位置的丶用於采集实时数据的多个感测器；位於所述感测器附近的闸道器，用於将所述感测器采集的数据传送到边缘设备;所述边缘设备，用於对所述闸道器传来的数据进行处理，并将处理过的数据传输到服务器，所述处理包括利用深度学习模型对所述幕门进行故障风险预测，所述处理过的数据包括故障风险预测结果；所述服务器，用於储存资料及训练所述深度学习模型；其中，所述深度学习模型根据幕门的日志数据丶幕门环境数据，以及幕门运作数据对所述幕门进行故障风险预测，所述幕门运作数据由所述感测器采集得到。本申请可以针对列车月台的幕门进行预测性维护。

Method and System of Automatic Constraint Modelling for Assembly Sequence Planning

HKSAR

32023067195.2

The present invention discloses a comprehensive assembly sequence planning based on CAD data and a fully automatic pipeline to achieve a reliable assembly sequence. An automatic constraint modelling (100) method for assembly sequence planning is disclosed in the present invention wherein, comprising the steps of: recognizing joining parts of a product data using a feature recognition (102) algorithm to automatically recognize shape and determine assembly features; dividing the product data into subassemblies (104); deriving liaison matrix for parts inside each of the subassemblies (104); deriving interference matrices by analyzing potential collisions (108) of the parts for each of the subassemblies (104); and defining and selecting base component (110) of the subassemblies (104). After the automatic modelling (100), the constraints are introduced to the Optimal Assembly Sequence Generation (112) where assembly sequences are generated based on the constraints and evaluated (114) regarding the optimization criteria.