Integrated detection truck for road tunnel defects

Abstract

The invention discloses an integrated detection truck for road tunnel defects. The integrated detection truck comprises a truck head and a carriage connected to the rear of the truck head. The carriage is further provided with an infrared camera detecting mechanism, a radar-linear-array camera detecting mechanism, a cantilever crane assembly, a lighting lamp, a main control chamber and a generator. The infrared camera detecting mechanism is installed at the front end of the carriage, the main control chamber is arranged at the rear end of the carriage, the cantilever crane assembly is fixed in the carriage and located between the infrared camera detecting mechanism and the main control chamber, the radar-linear-array camera detecting mechanism is installed on the cantilever crane assembly, the lighting lamp is installed on the radar-linear-array camera detecting mechanism, and the generator is arranged on one side of the cantilever crane assembly. A linear array camera detection device, an infrared camera detection device and a radar detection device are integrated, and the three defects including lining crack, water leakage and cavities of a tunnel are detected at the same time. The integrated detection truck has the advantages of being high in detecting efficiency, free of contact, high in safety and the like, and has very good application prospects in the road tunnel defect detection aspect.

Description

technical field [0001] The invention belongs to the field of road tunnel disease detection equipment, and in particular relates to a road tunnel disease integrated detection vehicle. Background technique [0002] In recent years, as the country strengthens investment in infrastructure facilities, my country's transportation construction has achieved rapid development, and the construction and research of highway tunnels, especially long tunnels, have also achieved rapid development. At present, my country has become the world's largest tunnel The country with the largest number of projects, the most complex and the fastest developing. However, because tunnels are semi-concealed projects built in underground rock-soil media, and tunnels in our country were built in different periods, under different geological conditions and at different technical levels, after years of operation, many tunnels have suffered from various diseases. In terms of: deformation encroachment, cracks,...

AI Technical Summary

Problems solved by technology

However, because tunnels are semi-concealed projects built in underground rock-soil media, and tunnels in our country were built in different periods, under different geological conditions and at different technical levels, after years of operation, many tunnels have suffered from various diseases. In terms of: deformation encroachment, cracks, water leakage, wrong platform, falling blocks, collapse, basement muddying, subsidence, bottom heaving, voids behind the lining, etc. The hidden dangers formed by these diseases pose a certain threat to the safety of tunnel operation. Among them, cracks, water leakage and voids are the three most common and serious diseases in tunnels.

[0003] At present, the detection of road tunnel cracks, water leakage and cavity diseases in our country is mainly carried out by manual on-site records and disease marks, and finally manually draws the expansion diagram of the disease along the tunnel vault. This kind of detection method requires a lot of manpower and material resources, and is dangerous To a high degree, special lifting equipment is required for tunnel vault inspection, and the inspection results are highly subjective, and different inspectors will obtain different inspection results, and most of the safety evaluations for tunnel lining structures are qualitative descriptions

Although foreign research institutions have developed different types of tunnel defect detection vehicles, the detection indicators are single, and most of them can only detect one or two diseases at the same time, and cannot realize the simultaneous detection of multiple diseases

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