Defect Detection Method And Device Based On The Training Of The Dataset With Few Normal Samples

HKSAR

32022066158.3

A 3D-Reconstructed Object Surface Inspection Method Based On A Robotic Arm And Eye System

HKSAR

32022062462.3

Disturbance Detection And Countermeasure Suggestion System And The Method Therefor

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

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

PRC

202420628565.3

The present invention discloses a multi-sensor (102) tool wear condition prediction and monitoring system, comprising of: a plurality of sensors (102) for processing analogue signals of the sensors (102); wherein the plurality of sensors (102) comprises an acoustic emission sensor (102a), a vibration sensor (102b) and a current sensor (102c); an IOT enabled remotely accessible user interface (118) with machine (118a) and scheduling frontends (118b); a software hub (202), characterized by: a data acquisition module (108) connected to the plurality of sensors (102), a data pre-processing module (114), a data storage module (202a) and a device management module (202b); and a machine learning prediction model (116).

A Multi-Sensor Tool Wear Condition Prediction And Monitoring System

HKSAR

32023071003.2

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).

System And Method For Cnc Tool Wear Conditions Monitoring And Prediction By Data Augmentation

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

32023068412.0

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.

一种用于注塑工序的质量预测和根本原因分析系统

PRC

202222999357.8

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。

Device for the Optical Inspection of Ultrasonic Welds

HKSAR

32022058921.4

The present invention relates to a device for the optical inspection of ultrasonic welds, particularly for the inspection of welds about the periphery of thermoplastic parts forming an envelope.

A Quality Prediction and Root Cause Analysis System for Injection Molding Processes

HKSAR

32022062264.3

The present invention relates to a quality prediction and root cause analysis system. In particular, the invention pertains to an AI-based system for analysing various data obtained in previously executed manufacturing operations for performing quality prediction and root cause analysis to determine one or more possible root causes for production deviation resulted in a manufacturing process.

基于混合元启发式算法的自动配送中心

PRC

202210700734.5