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Method for diagnosing engine integrated faults based on fuzzy semanteme network

A technology of fuzzy semantics and diagnostic methods, applied in the field of engine comprehensive fault diagnosis based on fuzzy semantic network, can solve problems such as single reasoning mode, failure to fully utilize fault information, and difficulty in obtaining fault knowledge

Inactive Publication Date: 2010-03-10
NAVAL AERONAUTICAL & ASTRONAUTICAL UNIV PLA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This patented technology describes a system that helps identify problems or issues related to engines by analyzing them through various techniques like databases and applications programs. It involves building up a repository called the Acquirement Base (AB) from previous generations of vehicles into a more complex structure containing different components including sensors, actuators, controllers, etc., along with associated software modules and algorithms. These assets help improve vehicle performance while reducing its risk of failure during use. Overall, this approach provides valuable insights about how well these technologies work together to make informed decisions when troubleshootings occur.

Problems solved by technology

The technical problem addressed by this patented method relates to improving the efficiency with which an aircraft's computer system can detect issues such as hardware failures or software bugs that may occur during flight operations due to factors like vibrations caused from turbulence (a phenomenon where airplanes move around).

Method used

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  • Method for diagnosing engine integrated faults based on fuzzy semanteme network
  • Method for diagnosing engine integrated faults based on fuzzy semanteme network
  • Method for diagnosing engine integrated faults based on fuzzy semanteme network

Examples

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Embodiment 1

[0024] Example 1, see figure 1 , 2 , 3, 4, first establish an embedded platform based on ARM embedded microprocessor and a data acquisition module based on field programmable gate array FPGA, the embedded platform is composed of ARM embedded processor S3C2410, power supply circuit, FLASH memory, SDRAM memory, LCD interface, USB interface, Ethernet interface, serial interface, data acquisition module interface, bus and reserved expansion interface, etc.; the data acquisition module is composed of main controller FPGA, AD converter and multi-channel analog switch, etc., ARM The embedded processor S3C2410 is connected with the data acquisition module through the data acquisition module interface connected by the bus, and the relevant components are connected by conventional technology;

[0025] Set the acquisition subroutine in the data acquisition module, set up the database and application program in the memory of the embedded platform, and the fault diagnosis program in the a...

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Abstract

The invention discloses a method for diagnosing engine integrated faults based on a fuzzy semanteme network. The method is characterized by comprising the following steps: establishing an embedded platform based on an ARM embedded microprocessor and a data acquiring module based on a field programmable gate array (FPGA), and establishing a fault knowledge acquiring method based on a fuzzy semanteme network model, a case-based reasoning subsystem and a guided interactive reasoning subsystem on the embedded platform, wherein the fault knowledge acquiring method based on a fuzzy semanteme networkmodel constructs an engine fault knowledge base; the case-based reasoning subsystem is used for quickly diagnosing frequent faults; and the guided interactive reasoning subsystem adopts a man-machineinteraction mode to carry out fuzzy searching and reasoning and can carry out deep diagnosis of the faults. After the data acquiring module automatically detects a fault symptom or a user inputs a fault symptom, an subsystem can be started independently, and two subsystems can also be started and operated together. Each subsystem can realize fault diagnosis independently, and diagnosis results oftwo subsystems can also be combined to carry out integrated diagnosis so as to improve the accuracy of the diagnosis.

Description

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Claims

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Application Information

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Owner NAVAL AERONAUTICAL & ASTRONAUTICAL UNIV PLA
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