Intelligent vibration digital twin system and method for industrial environments
Through the intelligent digital twin system, the multi-layer data processing platform is integrated, and the problems of low data utilization efficiency and expert knowledge loss in the industrial environment are solved, real-time monitoring and optimization are achieved, and the system's intelligence and automation level is improved.
Patent Information
- Application Number
- CN202080094528.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Priority Date
- 2020-11-09
- Filing Date
- 2020-11-25
- Publication Date
- 2025-08-19
- Estimated Expiration
- 2040-11-25
AI Technical Summary
In complex industrial environments, it is difficult for the existing technology to effectively utilize vibration sensors and IoT sensor data for real-time monitoring, intelligent diagnosis and optimization operations, and there is a lack of an effective inheritance mechanism for expert knowledge.
An intelligent digital twin system has been developed, including a multi-layer data processing platform, integrating industrial monitoring, data storage, adaptive intelligent systems and management applications. Real-time monitoring and optimization of the industrial environment is achieved by receiving requests, identifying dynamic models, selecting data sources, acquiring data and updating digital twin attributes.
Real-time monitoring and optimization of the industrial environment is achieved, problem diagnosis efficiency is improved, the impact of expert knowledge loss is reduced, and the system's intelligence and automation capabilities are enhanced.
Smart Images
Figure CN115039045B_ABST
Abstract
Claims
1. A method for updating one or more attributes of one or more digital twins, comprising: receiving a request for one or more digital twins, the request being any one of a request for updating one or more vibration severity unit values, a request for a failure probability value, a request for a shutdown probability value, a request for a shutdown probability value, a request for a shutdown cost value, a request for a manufacturing KPI value, a request for a fluid dynamics-related value, a request for a radiation value, a request for a quantum mechanics value, a request for a position value, a request for a metal concentration value, a request for an organic compound concentration value, and a request for a biological compound concentration value of the one or more digital twins; retrieving the one or more digital twins required to satisfy the request from a digital twin data store; retrieving one or more dynamic models corresponding to one or more properties described in the one or more digital twins indicated by the request; selecting a data source from a set of available data sources based on one or more inputs of the one or more dynamic models; Obtaining data from the selected data source; determining one or more outputs of the one or more dynamic models using the retrieved data as one or more inputs; as well as Based on the one or more outputs of the one or more dynamic models, the one or more properties of the one or more digital twins are updated. 2 . The method of claim 1 , wherein the request is received from a client application corresponding to an industrial environment and / or one or more industrial entities in the industrial environment.
3. The method of claim 1 , wherein the request is received from a client application supporting an Industrial Internet of Things sensor system.
4. The method of claim 1, wherein the digital twin is a digital twin of at least one of an industrial entity and an industrial environment.
5. The method of claim 1 , wherein the one or more dynamic models are based on data selected from the group consisting of: temperature, pressure, humidity, wind, rainfall, tide, storm surge, cloud cover, snowfall, visibility, radiation, audio, video, image, water level, quantum, flow rate, signal power, signal frequency, motion, velocity, acceleration, illumination, analyte concentration, biological compound concentration, metal concentration, or organic compound concentration data. The method of claim 1 , wherein the selected data source comprises an Internet of Things connected device. The method of claim 1 , wherein the selected data source comprises a machine vision system.
8. The method of claim 1 , wherein retrieving the one or more dynamic models comprises: The one or more dynamic models are identified based on the one or more properties described in the digital twin indicated by the request and the corresponding types of the one or more digital twins. The method of claim 8 , wherein the one or more dynamic models are identified using a lookup table.
10. A method for updating one or more vibration fault level states of one or more digital twins, comprising: receiving a request from a client application to update one or more vibration fault level states of one or more digital twins; retrieving the one or more digital twins required to satisfy the request; retrieving one or more dynamic models required to satisfy the request, wherein the one or more dynamic models include a dynamic model that predicts when a vibration fault level will occur based on an input data set; selecting a data source from a set of available data sources based on one or more inputs of the one or more dynamic models; Obtaining data from the selected data source; determining one or more outputs of the one or more dynamic models using the retrieved data as one or more inputs; as well as Based on the outputs of the one or more dynamic models, one or more vibration fault level states of the one or more digital twins are updated. 11 . The method of claim 10 , wherein the request is received from a client application corresponding to an industrial environment and / or one or more industrial entities in the industrial environment.
12. The method of claim 10, wherein the request is received from a client application supporting an Industrial Internet of Things sensor system.
13. The method of claim 10, wherein the digital twin is a digital twin of at least one of an industrial entity and an industrial environment.
14. The method of claim 10, wherein the dynamic model is based on data selected from the group consisting of at least one of vibration, temperature, pressure, humidity, wind, rainfall, tide, storm surge, cloud cover, snowfall, visibility, radiation, audio, video, image, water level, quantum, flow rate, signal power, signal frequency, motion, displacement, velocity, acceleration, illumination, financial, cost, stock market, news, social media, revenue, worker, maintenance, productivity, asset performance, worker performance, worker response time, analyte concentration, biological compound concentration, metal concentration, or organic compound concentration data.
15. The method of claim 10, wherein the data source is based on a group consisting of at least one of: an Internet of Things connected device, a machine vision system, an analog vibration sensor, a digital vibration sensor, a fixed digital vibration sensor, a three-axis vibration sensor, a single-axis vibration sensor, an optical vibration sensor, or a crosspoint switch.
16. The method of claim 10, wherein retrieving the one or more dynamic models comprises: The one or more dynamic models are identified based on the one or more properties indicated in the request and the corresponding types of the one or more digital twins. The method of claim 10 , wherein the one or more dynamic models are identified using a lookup table.
Citation Information
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