The integrated pipe gallery is the main mode of the urban pipe network in Xiongan New Area and the operating environment is complex. With the exponential increase in the number of operation and inspections

the serious discretization and the islanding of state data

the traditional operation inspection mode based on manpower cannot support the operation and maintenance requirement of the power grid. To this end

in this paper

a new type of operation condition diagnosis system of integrated pipeline gallery power cabin cable lines based on mobile sensing is designed

which uses wavelet decomposition to compress the sensing data and performs algorithm design based on the front and back data characteristics and application scenarios. A set of cable line status analysis and prediction based on front-end short-term data and a multi-dimensional fusion analysis and decision-making system based on big data back-end is formed so to comprehensively achieve the seamless connection of equipment identification

status perception

data interaction and intelligent diagnosis as well as multi-level cable operation reliability evaluation. The system in the application can successfully set the defect factor level of the cable line

find the hidden dangers of the same kind of risk and give maintenance suggestions

which strengthens further the control power of equipment status and optimizes operation and maintenance strategy of the equipment.