Application Analysis of Artificial Intelligent Neural Network Based on Intelligent Diagnosis

In recent years, computer science and AI have experienced rapid growth. Technologies always aim at reducing human efforts and completing the work with full efficiency. But in the process of scientific and technological development for ensuring the stable implementation of new technologies, the problems faced by different industries and fields are studied. This lays a foundation for the application of artificial intelligence neural networking technology.

The continuous development of AI technology makes the application prospect of AI in fault diagnosis emerge. As a simulation technology of human thinking patterns, intelligent diagnosis technology can help in contributing to checking and managing the monitoring target in real-time to ensure data accuracy.

Artificial intelligent neural networks make use of nervous science as their foundations. They achieve accurate monitoring of targets, providing effective information for staff decisions through three-dimensional monitoring and calculation, with unit nodes as computational modules.  

Keywords: Intelligent diagnosis, Artificial intelligence network, automobile fault diagnosis, the neural network

A recent paper published in Procedia Computer Science analyzes the application status of intelligent diagnosis technology and artificial intelligence network under intelligent diagnosis. It put forward the applications of artificial neural networks in automobile fault diagnosis based on examples. 

For better understanding, consider that in a car fault diagnosis, through a remote fault diagnosis system automobiles can be obtained at this time. The data is then transferred to the data processing center. Then, the information fault is diagnosed, thereby obtaining the best solution. In fault diagnosis, the involvement of artificial intelligence neural networks helps in solving the fault problem smoothly.

Through the artificial intelligence neural network system architecture, the unit distribution is taken as a model, the input unit is analyzed, and the number of units is diagnosed. Application of Artificial intelligence neural network in automobile fault diagnosis includes: 

1. The infrastructure:

 In the automobile fault diagnosis, the database should be established based on the fault system. Also, the maintenance plan of the database should be retrieved in the shortest time. When collecting fault types, one needs to diagnose and rectify each fault for improving user experience. In artificial intelligence neural networks, considering the real-time monitoring of vehicles, the following must be considered:

• Airbag pops ups
• Reading fault code
• Clearing fault code
• Vehicle maintenance reminder
• Collision automatic help

2. The improved scheme:

 The initial step is to analyze the characteristics of various parts of the car, including battery, voltage, pedal position, and so on. Then the intelligent fault diagnosis system is designed based on the analysis of fault components and working principles of the automobile.

3. Build a model:

The data obtained in the system are mapped to the clustering and fusion space for obtaining the parameters and contrast. After adjusting the sub-system constants, the BP neural network model is obtained, and the model is established based on the actual situation.

Conclusion:

In big data systems and the intelligent era, intelligent diagnosis technology has been widely adopted in various societies. This system makes it possible to obtain the fault causes and handling measures. It creates a way for ensuring technical support for fault handling in the information sent to the customers. This leads to achieving a high user experience.