US 10,598,520 B2Granted

Method and apparatus for pneumatically conveying particulate material including a user-visible IoT-based classification and predictive maintenance system noting maintenance state as being acceptable, cautionary, or dangerous

AssigneeMachineSense, LLC

InventorsBiplab Pal, Amit Purohit

Life of this patent

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Abstract

A method and system of a predictive maintenance IoT system comprises receiving a plurality of sensor data over a communications network and determining one or more clusters from the sensor data based on a pre-determined rule set. Further, the sensor data is classified through a machine learning engine and the sensor data is further base-lined through a combination of database architecture, data training architecture, and a base-lining algorithm. Intensity or degree of fault state is mapped to a fuel gauge to be depicted on a user interface and a predictive maintenance state is predicted through a regression model and appropriate alarm is raised for user action.

Claims16

Dependent claims

A method of pneumatically conveying particulate material while providing a user visible IoT-based classification and predictive maintenance reading respecting performance of the method as being acceptable, cautionary or dangerous on a numerical scale ranging from 0 to 100, comprising:

a) providing a vacuum pump comprising:
i) a motor;
ii) a blower;
and
iii) a plurality sensors for measuring vibration, magnetic filed, pressure, and temperature at various positions on the vacuum pump;
b) by operation of the vacuum pump, drawing a vacuum through a conduit leading from the vacuum pump to a material receiver and on to a particulate material pickup device thereby picking up and transporting particulate material from a source thereof to the receiver;
c) providing data from the sensors to a communications network;
d) receiving in mobile middleware a plurality of sensor data from the communications network;
e) determining one or more clusters from the sensor data based on a pre-determined rule set;
f) classifying the sensor data through a machine learning engine connected to the middleware;
g) base-lining the sensor data, in a real time data processing system communicating with the machine learning engine, using a combination of database architecture, data training architecture, and a base-lining algorithm;
h) using a regression model calculating the predictive maintenance state of the vacuum pump;
and
i) presenting the maintenance state of the method on a fuel gauge representation based on a predictive maintenance state calculated by the regression model.

11 more elements

Apparatus for pneumatically conveying particulate material including a user visible IoT-based classification and predictive maintenance system noting apparatus maintenance state as being acceptable, cautionary, or dangerous, comprising:

a) a vacuum pump comprising:
i) a motor;
ii) a blower;
and
iii) a plurality of sensors mounted on the pump for measuring vibration, magnetic field, pressure, power factor, and temperature, and supplying data indicative of such measurements;
b) a communications network communicating with the sensors;
c) mobile middleware receiving a plurality of the sensor data of the communications network;
d) a real time data processing system connected to the mobile middleware and including associated distributed databases, the data processing system further comprising:
i) a clustering module for determining presence of one or more data clusters from the sensor data based on a pre-determined rule set;
ii) a computer database for storing the pre-determined rule set;
iii) a machine learning engine for classifying the sensor data according to the predetermined rule set;
iv) a base-lining architecture for base-lining the sensor data, the base-lining architecture comprising:
(1) a combination of database architecture, data training architecture, and a base-lining algorithm;
and
(2) a regression module associated with a processor to predict a predictive maintenance state;
e) a receiver for storage of conveyed material received pneumatically from the pick-up device;
f) tubular segments for pneumatically connecting the receiver to the vacuum pump and for pneumatically connecting the pickup device to the receiver for pneumatic conveyance of the particulate material from the pickup device to the receiver through the tubing in response to vacuum drawn by the pump;
g) a user interface, connected to the pump, for visibly displaying the determined state of maintenance of the pneumatic conveying apparatus;
h) the real-time data processing system mapping the predicted maintenance state of the pneumatic conveying apparatus as a depiction on the user interface.

16 more elements

Dependencies are inferred from the claim text.

Facts

Application: 16/253,925Filed 22 Jan 2019 · continuation in part
Priority: 23 Feb 2015
Published: US 2019/0154032 A123 May 2019
Granted: 24 Mar 2020
Term ends: Not estimatedThe source records don’t support an estimate.

Classification13 codes

G01D 7/005
Indicating measured values: indication of measured value by colour change
B23Q 17/0971
During machining: by measuring mechanical vibrations of parts of the machine
B65G 53/66
Details: use of indicator or control devices, e.g. for controlling gas pressure, for controlling proportions of material and gas, for indicating or…
G05B 19/0428
Using digital processors: safety, monitoring

Family

Application14/628,322Parent of this continuation-in-part · filed 23 Feb 2015
Application14/696,402Parent of this continuation-in-part · filed 25 Apr 2015
Application14/790,084Parent of this continuation · filed 2 Jul 2015
Application16/253,462Parent of this continuation-in-part · filed 22 Jan 2019
US 2019/0154469 A1Pre-grant publication · published 23 May 2019
Application16/253,462Parent of this continuation
Application14/790,084Parent of this continuation-in-part
US 10,599,982 B2Related patent
US 11,002,269 B2Related patent
US 2016/0245279 A1Published application
US 2016/0313216 A1Published application
US 2017/0011298 A1Published application
US 2019/0154032 A1Published application
US 10,598,520 B2This patent

From the US filing history. Foreign family members aren’t listed.