The detection methods of the train control and diagnostic system mainly include the following:

1. Hardware fault detection method
Professional test instrument detection:
Professional test instruments such as sensors, lines, signal equipment, etc., are used to detect hardware devices in the train control and diagnostic system.
Through the reading and analysis of the test instrument, determine the fault point of the hardware equipment, such as line disconnection, sensor damage, etc.
Line detector:
For line faults, line detectors can be used to search for the location of power failure to determine the specific location of the line fault.
Disassembly test:
For hardware devices such as suspected damaged sensors, disassembly tests can be performed to determine whether there is a fault by directly observing or testing their performance.
2. Software fault detection method
Restart the system:
In some cases, software failures may be caused by system anomalies or program errors. At this time, restarting the system may help restore the normal operation of the software.
Software inspection and troubleshooting:
Check the software programs in the train control and diagnostic system and determine the cause of the software failure by eliminating error codes or abnormal behaviors.
This may require professional software engineers or technicians to ensure the accuracy and effectiveness of the inspection.
Combined inspection of hardware and software:
After eliminating software errors, it is also necessary to check the hardware devices related to the software to determine whether there is a hardware failure that causes software abnormalities.
III. Advanced fault diagnosis methods
Fault tree method:
By studying the least desirable events of the system, reverse reasoning the causes of the events, and linking the events and causes together with logical relationships, a fault relationship model is established.
This method helps to systematically analyze the causes and paths of faults, thereby formulating effective troubleshooting strategies.
Neural network method:
Use neural networks to analyze and process previous data and establish a fault model.
Neural network methods have strong learning and fitting capabilities, can handle nonlinear mapping problems, and have significant advantages in complex train control and diagnosis system fault diagnosis.
Expert system method:
The knowledge base formed based on the experience accumulated by experts in their work is used as a diagnostic basis for determining whether a train has a fault.
This method combines the experience and knowledge of experts and can quickly and accurately determine the cause and location of the fault.
Fuzzy theory method:
It is used to deal with some problems that cannot be described definitely in real life and have a certain degree of uncertainty.
In the fault diagnosis of train control and diagnosis systems, fuzzy theory methods can be used to deal with some fault phenomena and problems that are difficult to describe accurately.
4. Other methods
Integration of multiple diagnostic methods:
As train control and diagnostic systems become more complex and sophisticated, it is difficult for a single fault diagnosis method to efficiently and accurately determine the cause and location of the fault. Therefore, it is necessary to integrate multiple system fault diagnosis methods, take advantage of their strengths avoid their weaknesses, and achieve the purpose of accurate and rapid fault diagnosis.
In-machine test technology:
Use the detection, isolation and testing functions of the system or equipment itself to improve the diagnostic and testability of the equipment, avoid the occurrence of unnecessary alarms, and improve the system diagnosis efficiency.
In summary, there are many detection methods for train control and diagnostic systems, including hardware fault detection methods, software fault detection methods, advanced fault diagnosis methods and other methods. In practical applications, it is necessary to select appropriate detection methods according to the specific conditions of the system and the fault phenomenon to ensure the normal operation and safety of the system.