Method and system for track traffic fault monitoring and intelligent warning
A fault monitoring and rail transit technology, applied in the field of rail transit safety, can solve the problems of high work intensity, fault diagnosis accuracy easily interfered by personnel factors, and low efficiency
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Embodiment 1
[0125] Such as Figure 9 shown, including the following steps:
[0126] S11. The compound eye high-definition camera collects real-time status data of tunnel cracks;
[0127] S12. The data comparison module 200 performs comparison according to the corresponding data in the database module, and judges whether the tunnel crack exceeds the set threshold. If it does not exceed the set threshold, go to step S18. If it exceeds the set threshold, go to step S13;
[0128] S13. Generate fault information or early warning information, and locate and rate the fault information or early warning information;
[0129] S14, the data transmission module 300 transmits the real-time status data, fault information or early warning information to the regional processing module 400;
[0130] S15, the area processing module 400 classifies the real-time status data, fault information or early warning information, transmits the classification information, location information and rating information...
Embodiment 2
[0138] Such as Figure 10 shown, including the following steps:
[0139] S21. The compound eye high-definition camera collects real-time state data of rail deformation;
[0140] S22, the data comparison module 200 compares according to the corresponding data in the database module, and judges whether the deformation of the rail exceeds the set threshold, if it does not exceed the set threshold, enters step S28, and if exceeds the set threshold, enters step S23;
[0141] S23. Generate fault information or early warning information, and locate and rate the fault information or early warning information;
[0142] S24, the data transmission module 300 transmits the real-time status data, fault information or early warning information to the regional processing module 400;
[0143] S25, the area processing module 400 classifies the real-time status data, fault information or early warning information, transmits the classification information, location information and rating infor...
Embodiment 3
[0151] Such as Figure 11 shown, including the following steps:
[0152] S31, the sound collector collects the real-time status data of the abnormal sound during the train operation;
[0153] S32, the data comparison module 200 compares according to the corresponding data in the database module, and judges whether the category of the abnormal sound is a suspicious abnormal sound of a fault or an early warning, if it is not a suspicious abnormal sound, then enters step S39, and if it is a possible abnormal sound, then enters step S33;
[0154] S33. Judging the suspicious abnormal sound according to the preset threshold, if it does not exceed the set threshold, go to step S39, if it exceeds the set threshold, go to step S34;
[0155] S34. Generate fault information or early warning information, and locate and rate the fault information or early warning information;
[0156] S35, the data transmission module 300 transmits the real-time status data, fault information or early wa...
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