INTELLIGENT VIBRATION DIGITAL TWIN SYSTEMS AND METHODS FOR INDUSTRIAL ENVIRONMENTS
A platform for updating one or more properties of one or more digital twins including receiving a request for one or more digital twins; retrieving the one or more digital twins required to fulfill the request from a digital twin datastore; retrieving one or more dynamic models corresponding to one or more properties that are depicted in the one or more digital twins indicated by the request; selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models; obtaining data from selected data sources; determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; and updating the one or more properties of the one or more digital twins based on the one or more outputs of the one or more dynamic models.
1 . 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 fulfill the request;
retrieving one or more dynamic models required to fulfill the request, wherein the one or more dynamic models include a dynamic model that predicts when a vibration fault level occurs based on an input dataset;
selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models;
obtaining data from selected data sources;
determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; and
updating one or more vibration fault level states of the one or more digital twins based on the output of the one or more dynamic models.
2 . The method of claim 1 , wherein the request is received from a client application that corresponds to an industrial environment and/or one or more industrial entities within the industrial environment.
3 . The method of claim 1 , wherein the request is received from a client application that supports an Industrial Internet of Things sensor system.
4 . The method of claim 1 , wherein the digital twins are digital twins of at least one of industrial entities and industrial environments.
5 . The method of claim 1 , wherein the dynamic models take data selected from the set 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, lighting level, 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, and organic compound concentration data.
6 . The method of claim 1 , wherein the data source is selected from the set 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 tri-axial vibration sensor, a single axis vibration sensor, an optical vibration sensor, and a cross-point switch.
7 . The method of claim 1 , wherein retrieving the one or more dynamic models includes identifying the one or more dynamic models based on the one or more properties indicated in the request and a respective type of the one or more digital twins.
8 . The method of claim 1 , wherein the one or more dynamic models are identified using a lookup table.