IoT-enabled process control and predective maintenance using machine wearables

• US 9,826,338 B2
• Filed: 01/17/2015
• Issued: 11/21/2017
• Est. Priority Date: 11/18/2014
• Status: Active Grant

• Current Assignee: Machinesense LLC
• Original Assignee: Prophecy Sensorlytics Llc
• Inventors: Pal, Biplab
• Primary Examiner(s): Butler, Dennis M
• Application Number:
  US14/599,461
• Publication Number:
  US 20160209831A1
• Time in Patent Office: 1,039 Days
• CPC Class Codes: B29B 13/065 of powder or pellets
• CPC Class Codes: B29B 9/16 Auxiliary treatment of granules
• CPC Class Codes: F26B 17/14 the materials moving through a counter-current of gas
• CPC Class Codes: F26B 21/06 Controlling, e.g. regulating, parameters of gas supply F26B21/14 takes precedence; control in general G05
• CPC Class Codes: G05B 19/4185 characterised by the network communication
• CPC Class Codes: G05B 2219/31457 Factory remote control, monitoring through internet
• CPC Class Codes: H04W 4/80 Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

Disclosed is an IoT-based system for overseeing process control and predictive maintenance of a machine or a network of machines by employing machine wearable sensors. The system comprises a plurality of IR temperature sensors, each of which secured to the exterior of the machine; each IR sensor capable of transmitting captured temperature data wirelessly over a communications network, an algorithm engine capable of receiving data from the IR sensors, the algorithm engine for further processing the received data to recognize real-time temperature patterns, deviations, etc., and based on the same issuing control commands pertaining to the machine, and one or more control modules disposed in operative communication with the control panel of the machine, the control module capable of receiving, over a communications network, the control commands and executing the same resulting in accomplishing process control or predictive maintenance of the machine or both.

Claims

1. An Internet of Things (IoT) based system for overseeing process control and predictive maintenance of a machine by employing machine wearable sensors, comprising:

a. a plurality of machine-wearable infrared (IR) temperature sensors, each of which being secured to the exterior of the machine;

each IR sensor transmitting captured temperature data wirelessly over a communications network;

b. an algorithm engine capable of receiving data from the IR sensors, the algorithm engine further processing the received data to recognize real-time temperature pattern deviations, and based on the same and, at times, in combination with other factors, promptly issuing control commands pertaining to the machine; and

c. a control module disposed in operative communication with a control panel of the machine, the control module receiving over a communications network the control commands and executing the same resulting in process control or predictive maintenance of the machine or both;

wherein the machine comprises a hopper dryer comprising an elongate, vertical sight glass;

the plurality of infrared (IR) temperature sensors being secured over the sight glass for capturing the IR radiation therethrough, each of the plurality of IR sensors being vertically disposed over one another, each IR sensor capturing temperature within the hopper dryer at the vertical level thereof.

2. The system of claim 1 wherein each IR sensor is magnetically secured to the hopper dryer.

3. The system of claim 2 wherein each IR sensor is encased within a holder comprising a magnet;

the magnet within which, the IR sensor is encased being attached to the hopper dryer.

4. The system of claim 1 wherein each IR sensor is secured to the hopper dryer by a screw mounting.

5. The system of claim 1 wherein the plurality of IR sensors comprises two IR sensors.

6. The system of claim 1 wherein the plurality of IR sensors comprises three IR sensors.

7. The system of claim 6 wherein a first IR sensor is located at a dry air flow inlet of the machine, a second IR sensor is located at an air flow outlet of the machine, and a third IR sensor is located between the first and second locations.

8. The system of claim 1 wherein the plurality of IR sensors are vertically spaced-apart from one another.

9. An Internet of Things (IoT) based system for overseeing process control and predictive maintenance of a machine by employing machine wearable sensors, comprising:

a. a plurality of machine-wearable infrared (IR) temperature sensors, each of which secured to the exterior of the machine;

each IR sensor transmitting captured temperature data wirelessly over a communications network;

b. an algorithm engine receiving data from the IR sensors, the algorithm engine further processing the received data to recognize real-time temperature pattern deviations, and based on the same and, at times, in combination with other factors, promptly issuing control commands pertaining to the machine; and

c. a control module disposed in operative communication with a control panel of the machine, the control module receiving, over a communications network the control commands and executing the same resulting in process control or predictive maintenance of the machine or both;

wherein the algorithm engine comprises;

(i) a database comprising at least one anomalous temperature pattern, each of which is associated with a control command;

(ii) a mapping module for mapping received temperature data into a real-time temperature pattern;

(iii) a first relational module for comparing the real-time temperature pattern against one or more normal temperature patterns;

(iv) a second relational module for comparing the real-time temperature pattern against the at least one anomalous temperature pattern in the event of the real-time temperature pattern is not matched with any of the one or more normal temperature patterns; and

(v) the command module issuing a corresponding control command upon recognizing an anomalous temperature pattern with which the real-time temperature pattern matches.