Automatically optimized combustion control

• US 5,971,747 A
• Filed: 12/30/1998
• Issued: 10/26/1999
• Est. Priority Date: 06/21/1996
• Status: Expired due to Term

• Current Assignee: Jerome H. Lemelson, John H. Hiett, Robert D. Pedersen
• Original Assignee: Jerome H. Lemelson, John H. Hiett, Robert D. Pedersen
• Inventors: Lemelson, Jerome H., Hiett, John H., Pedersen, Robert D.
• Primary Examiner(s): Jones, Larry
• Application Number:
  US09/223,639
• Time in Patent Office: 300 Days
• Field of Search: 431/12, 431/75, 431/76, 340/578, 356/45, 364/148.02, 706/23, 706/16, 382/100, 703/25, 110/185
• US Class Current: 431/12
• CPC Class Codes: F23N 2223/52 Fuzzy logic
• CPC Class Codes: F23N 2229/20 Camera viewing
• CPC Class Codes: F23N 5/082 using electronic means
• CPC Class Codes: Y02T 50/60 Efficient propulsion technologies, e.g. for aircraft

Abstract

Systems and methods are disclosed that optimize the combustion process in various reactors, furnaces, and internal combustion engines. Video cameras are used to evaluate the combustion flame grade. Depending on the desired form, standard or special video devices, or beam scanning devices, are used to image the combustion flame and by-products. The video device generates and outputs image signals during various phases of, and at various locations in, the combustion process. Other forms of sensors monitor and generate data signals defining selected parameters of the combustion process, such as air flow, fuel flow, turbulence, exhaust and inlet valve openings, etc. In a preferred form, a neural networks initially processes the image data and characterizes the combustion flame. A fuzzy logic controller and associated fuzzy logic rule base analyzes the image data from the neural network, along with other sensor information. The fuzzy logic controller determines and generates control signals defining adjustments necessary to optimize the combustion process.

Claims

1. A method for controlling parameters of a combustion process comprising the acts of:

(a) directing an imaging device at the combustion process;

(b) activating the imaging device to view the combustion process and generate an imaging output signal that varies in accordance with variations in the combustion process;

(c) operating additional sensors to monitor other parameters of the combustion process and to generate sensor outputs that vary in accordance with variations in the combustion process;

(d) inputting the output signal from the imaging device to a computer processor having at least a part thereof configured as a neural network;

(e) operating the neural network to process the output signal and to generate a combustion classification signal defining a parameter of the combustion process;

(f) inputting the combustion classification signal and the sensor outputs to a decision analysis computer having at least a part thereof configured as a fuzzy logic controller with associated fuzzy inference rules defining combustion control actions depending on various combinations of sensor outputs and flame grade classification;

(g) operating the decision analysis computer to;

(i) analyze the combustion classification signal and sensor outputs in accordance with the fuzzy inference rules to determine appropriate combustion control actions to optimize the combustion process depending on various combinations of the sensor outputs and combustion classification signals; and

(ii) generate combustion control signals defining adjustments to at least one combustion parameter; and

(i) applying the combustion control signals to adjust at least one combustion parameter.

2. The method of claim 1 wherein the imaging device is selected from the group composed of a video camera;

a beam scanner; and

a laser scanner with an associated detector.

3. The method of claim 1 further comprising:

(a) directing an additional imaging device at the combustion process;

(b) activating the additional imaging device to view the combustion process and generate an additional output signal that varies in accordance with variations in the combustion process;

(c) inputting the additional output signal to a computer processor configured to analyze image data and storing in the computer processor, image data obtained from the output signal; and

(d) operating the computer processor to analyze the image data and to generate digital output signals characterizing a parameter of the combustion process;

(e) inputting the digital output signal to the decision analysis computer;

(f) operating the decision analysis computer to additionally analyze the digital output signal.

4. The method of claim 3 wherein the additional imaging device is infrared camera.

5. The method of claim 3 wherein the additional scanning device is a spectral photodetector.

6. The method of claim 1 wherein the act of operating additional sensors to monitor other parameters of the combustion process and to generate sensor outputs that vary in accordance with variations in the combustion process, includes the acts of:

(a) positioning a temperature sensor so that it can sense the temperature of at least one parameter of the combustion process;

(b) activating the temperature sensor; and

(c) generating an output signal indicative the sensed temperature.

7. The method of claim 1 wherein the act of operating additional sensors to monitor other parameters of the combustion process and to generate sensor outputs that vary in accordance with variations in the combustion process, includes the acts of:

(a) positioning a pressure sensor so that it can sense the pressure of at least one parameter of the combustion process;

(b) activating the pressure sensor; and

(c) generating an output signal indicative the sensed pressure.

8. The method of claim 1 wherein the act of operating the neural network to process the output signal and to generate a combustion classification signal defining the combustion process includes the acts of:

(a) processing the output signal in first and second hidden layers of parallel processing elements, which elements are weighted and trained to recognize different flame classification grades; and

(b) generating an output signal that defines a flame grade classification for the combustion process at the time it was scanned.

9. The method of claim 1 wherein the act of operating the decision analysis computer to analyze the combustion classification signal and sensor outputs and to generate combustion control signals and includes the acts of:

(a) programming the decision analysis computer as a fuzzy logic controller with associated fuzzy inference rules established to monitor and adjust a ratio of air to fuel for the combustion process within a predetermined range;

(b) operating the decision analysis computer to evaluate the combustion classification and sensor outputs in accordance with the programmed fuzzy inference rules to determine whether the ratio of air to fuel needs to be changed to optimize combustion process while also minimizing pollutants, and if so, the amount that the ratio needs to be changed; and

(c) operating the decision analysis computer to generate combustion control signals defining required changes to the air-to-fuel ratio.

10. The method of claim 9 wherein the act of operating the decision analysis computer to generate combustion control signals defining required changes to the air-to-fuel ratio includes generating signals that alter the flow of air so that it is maintained within a range of defined by a preset minimum and a preset maximum.

11. The method of claim 9 wherein the act of operating the decision analysis computer to generate combustion control signals defining required changes to the air-to-fuel ratio includes generating signals that alter the flow of fuel so that it is maintained within a range defined by a preset minimum and a preset maximum.

12. The method of claim 9 wherein the act of operating the decision analysis computer to generate combustion control signals defining required changes to the air-to-fuel ratio includes generating signals that maintain the air-to-fuel ration with a range defined by a preset minimum and a preset maximum.

13. The method of claim 12 wherein both the flow of air and the flow of fuel are changed within defined minimum and maximum values.

14. The method of claim 1 wherein the act of operating the decision analysis computer to analyze the combustion classification signal and sensor outputs and to generate combustion control signals and includes the acts of:

(a) programming the decision analysis computer as a fuzzy logic controller with associated fuzzy inference rules established to monitor and adjust a ratio of air to fuel for the combustion process within a predetermined range designed to both optimize combustion efficiency and minimize resulting pollutants;

(b) operating the decision analysis computer to evaluate the combustion classification and sensor outputs in accordance with the programmed fuzzy inference rules to determine whether the ratio of air to fuel needs to be changed to optimize combustion process while also minimizing pollutants, and if so, the amount that the ratio needs to be changed; and

(c) operating the decision analysis computer to generate combustion control signals defining required changes to the air-to-fuel ratio.

15. The method of claim 14 wherein the act of operating the decision analysis computer to generate combustion control signals defining required changes to the air-to-fuel ratio includes generating signals that control a device for treating pollutants.

16. A system for controlling a combustion process in a reaction chamber comprising:

(a) a scanning device positioned to scan the combustion flame and including an output that generates scanning signals that vary with variations in the combustion flame;

(b) a spectral radiation detector positioned to image the combustion process and generate variable output signals defining variations in the spectral content of the combustion process;

(c) a decision analysis computer configured to receive the scanning signals and spectral information signals and including a fuzzy logic controller with associated fuzzy inference rules defining combustion control actions depending on various combinations of sensor outputs and flame grade classification;

(d) the fuzzy logic controller being configured to;

(i) analyze the scanning signals and spectral information signals in accordance with the fuzzy inference rules to determine appropriate combustion control actions to optimize the efficiency of the combustion process and reduce pollutants; and

(ii) generate on an output of the decision analysis computer combustion control signals defining adjustments to at least one combustion parameter.

17. A system for controlling parameters of a combustion process taking place within a combustion chamber, comprising:

(a) an imaging device mounted proximate to the combustion chamber in a manner so that it is capable of viewing the combustion process, the imaging device including a detection circuit coupled to an output circuit, and configured to generate electrical image signals on the output circuit that vary with variations in the combustion process;

(b) a control circuit coupled to and configured to activate the imaging device to begin imaging the combustion process;

(c) a plurality of additional sensors configured to monitor other parameters of the combustion process, each sensor including an output circuit that generates sensor outputs that vary in accordance with variations in sensed parameters of the combustion process;

(d) a computer processor having (i) an input coupled to the output of the imaging device, (ii) logic configured as a neural network, and (iii) memory storing a program that, when executed by the network, processes the imaging output signal to generate a combustion classification signal defining a parameter of the combustion process;

(e) a decision analysis computer having (i) an input coupled to the computer processor that receives the combustion classification signals;

(ii) logic configured as a fuzzy controller;

(iii) memory storing a fuzzy inference rule program that, when executed by the fuzzy controller, analyzes the combustion classification signals and the sensor outputs to determine and generate combustion control signals defining combustion control actions that vary depending on various combinations of sensor outputs and flame grade classification;

(f) a plurality of combustion control devices configured to vary parameters of the combustion process, each combustion control device including a signal input; and

(g) wherein the decision analysis computer includes an output coupled to the inputs of the combustion control devices and is configured to communicate the combustion control signals from the fuzzy controller to the combustion control devices to adjust combustion parameters and optimize the combustion process.