Engine control system using a cascaded neural network
First Claim
1. A method for monitoring an engine using a cascaded neural network that includes a plurality of neural networks, the method comprising:
- storing in a memory, data corresponding to the cascaded neural network;
inputting signals generated by a plurality of engine sensors into the cascaded neural network;
updating at a first rate, a second neural network with an output of a first neural network, wherein said output is based on the inputted signals; and
outputting at a second rate, at least one engine control signal from the second neural network,wherein the second rate is faster than the first rate.
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Abstract
A method, system and machine-readable storage medium for monitoring an engine using a cascaded neural network that includes a plurality of neural networks is disclosed. In operation, the method, system and machine-readable storage medium store data corresponding to the cascaded neural network. Signals generated by a plurality of engine sensors are then inputted into the cascaded neural network. Next, a second neural network is updated at a first rate, with an output of a first neural network, wherein the output is based on the inputted signals. In response, the second neural network outputs at a second rate, at least one engine control signal, wherein the second rate is faster than the first rate.
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Citations
27 Claims
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1. A method for monitoring an engine using a cascaded neural network that includes a plurality of neural networks, the method comprising:
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storing in a memory, data corresponding to the cascaded neural network; inputting signals generated by a plurality of engine sensors into the cascaded neural network; updating at a first rate, a second neural network with an output of a first neural network, wherein said output is based on the inputted signals; and outputting at a second rate, at least one engine control signal from the second neural network, wherein the second rate is faster than the first rate. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for monitoring an engine, comprising:
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storing in a memory, data corresponding to at least two neural networks; inputting signals generated by a plurality of engine sensors into a first neural network; outputting at least one engine control signal from the first neural network at a first rate; and outputting at least a second engine control signal from the second neural network at a second rate, wherein the at least second signal is dependent on a second output from the first neural network and the second rate is faster than the first rate. - View Dependent Claims (10)
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11. A method for monitoring an engine, comprising:
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storing in a memory, data corresponding to at least one neural network and data corresponding to a polynomial; inputting signals generated by a plurality of engine sensors into a first neural network; updating a polynomial with an output of the first neural network at a first rate; and outputting at least one engine control signal from the polynomial at a second rate, wherein the second rate is faster than the first rate.
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12. A machine-readable storage medium having stored thereon machine executable instructions, the execution of said instructions adapted to implement a method for monitoring an engine using a cascaded neural network that includes a plurality of neural networks, the method comprising:
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storing in a memory, data corresponding to the cascaded neural network; inputting signals generated by a plurality of engine sensors into the cascaded neural network; updating at a first rate, a second neural network with an output of a first neural network, wherein said output is based on the inputted signals; and outputting at a second rate, at least one engine control signal from the second neural network, wherein the second rate is faster than the first rate. - View Dependent Claims (13, 14, 15, 16, 17)
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18. A machine-readable storage medium having stored thereon machine executable instructions, the execution of said instructions adapted to implement a method for monitoring an engine, the method comprising:
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storing in a memory, data corresponding to at least two neural networks; inputting signals generated by a plurality of engine sensors into a first neural network; outputting at least a first engine control signal from the first neural network at a first rate; and outputting at least a second engine control signal from the second neural network at a second rate, wherein the at least second signal is dependent on a second output from the first neural network and the second rate is faster than the first rate. - View Dependent Claims (19, 20)
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21. A machine-readable storage medium having stored thereon machine executable instructions, the execution of said instructions adapted to implement a method for monitoring an engine, the method comprising:
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storing in a memory, data corresponding to at least one neural network and data corresponding to a polynomial; inputting signals generated by a plurality of engine sensors into a first neural network; updating a polynomial with an output of the first neural network at a first rate; and outputting at least one engine control signal from the polynomial at a second rate, wherein the second rate is faster than the first rate.
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22. An apparatus for monitoring an engine using a cascaded neural network that includes a plurality of neural networks, the apparatus comprising:
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a microprocessor that includes data corresponding to the cascaded neural network; a module configured to receive signals generated by a plurality of engine sensors into the cascaded neural network; a module configured to update at a first rate, a second neural network with an output of a first neural network, wherein said output is based on the inputted signals; and a module configured to output at a second rate, at least one engine control signal from the second neural network, wherein the second rate is faster than the first rate. - View Dependent Claims (23)
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24. An apparatus for monitoring an engine, the apparatus comprising:
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a microprocessor that includes data corresponding to at least two neural networks; a module configured to receive signals generated by a plurality of engine sensors into a first neural network; a module configured to output at least a first engine control signal from the first neural network at a first rate; and a module configured to output at least a second engine control signal from the second neural network at a second rate, wherein the at least second signal is dependent on a second output from the first neural network and the second rate is faster than the first rate. - View Dependent Claims (25)
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26. An apparatus for monitoring an engine, the apparatus comprising:
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a microprocessor that includes data corresponding to at least one neural network and data corresponding to a polynomial; a module configured to store in a memory, data corresponding to at least one neural network and data corresponding to a polynomial; a module configured to receive signals generated by a plurality of engine sensors into a first neural network; a module configured to update a polynomial with an output of the first neural network at a first rate; and a module configured to output at least one engine control signal from the polynomial at a second rate, wherein the second rate is faster than the first rate. - View Dependent Claims (27)
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Specification