Derivation method, derivation device, derivation system, and program

A derivation device, comprising:

• a memory configured to store a program;
• and
• a processor configured to execute the program so as to:
• acquire time-series acceleration data of acceleration generated at a predetermined observation point in a superstructure of a bridge as a response caused by a movement of a railway train including one or more cars on the superstructure, the acceleration being detected by an acceleration sensor disposed at the predetermined observation point;
• acquire a weight of the cars of the railway train based on the time-series acceleration data;
• acquire environment information relating to a structure length of the superstructure, a car length of one of the cars of the railway train, and installation positions of wheels of the railway train contacting the superstructure;
• acquire a deflection model of the superstructure of the bridge based on the time-series acceleration data and the environment information;
• derive a fundamental frequency of a vibration of the superstructure due to the movement of the railway train on the superstructure based on a result of fast Fourier transform of the time-series acceleration data;
• derive a passing period of time during which the railway train passes along the superstructure based on the time-series acceleration data and a predetermined threshold;
• derive a number of the cars included in the railway train based on the environment information, the fundamental frequency, and the passing period of time;
• repeat the acquiring of the time-series acceleration data, the acquiring of the weight, the acquiring of the environment information, the acquiring of the deflection model, the deriving of the fundamental frequency, the deriving of the passing of time, and the deriving the number of the cars to obtain a total number of the cars of the railway trains that move on the superstructure during a predetermined period of time and a total weight of the weight of the cars of the railway trains that move on the superstructure during the predetermined period of time;
• and
• diagnose a state of the superstructure of the bridge based on the derived total number of the cars included in the railway trains, the total weight of the railway trains, and the deflection model in consideration of a risk factor including a resonance phenomenon existing due to vibration of the superstructure caused by the acceleration.

A derivation system comprising:

• an acceleration sensor disposed at a predetermined observation point of a superstructure of a bridge;
• and
• a derivation device including:
• a memory configured to store a program;
• and
• a processor configured to execute the program so as to:
• acquire time-series acceleration data of acceleration generated at the predetermined observation point in the superstructure of the bridge as a response caused by a movement of a railway train including one or more cars on the superstructure, the acceleration being detected by the acceleration sensor;
• acquire a weight of the cars of the railway train based on the time-series acceleration data;
• acquire environment information relating to a structure length of the superstructure, a car length of one of the cars of the railway train, and installation positions of wheels of the railway train contacting the superstructure;
• acquire a deflection model of the superstructure of the bridge based on the time-series acceleration data and the environment information;
• derive a fundamental frequency of a vibration of the superstructure due to the movement of the railway train on the superstructure based on a result of fast Fourier transform of the time-series acceleration data;
• derive a passing period of time during which the railway train passes along the superstructure based on the time-series acceleration data and a predetermined threshold;
• derive a number of the cars included in the railway train based on the environment information, the fundamental frequency, and the passing period of time;
• repeat the acquiring of the time-series acceleration data, the acquiring of the weight, the acquiring of the environment information, the acquiring of the deflection model, the deriving of the fundamental frequency, the deriving of the passing of time, and the deriving the number of the cars to obtain a total number of the cars of the railway trains that move on the superstructure during a predetermined period of time and a total weight of the weight of the cars of the railway trains that move on the superstructure during the predetermined period of time;
• and
• diagnose a state of the superstructure of the bridge based on the derived total number of the cars included in the railway trains, the total weight of the railway trains, and the deflection model in consideration of a risk factor including a resonance phenomenon existing due to vibration of the superstructure caused by the acceleration.

A non-transitory computer-readable storage medium storing a program for causing a computer to execute a process by a processor so as to perform the steps of:

• acquiring time-series acceleration data of acceleration generated at a predetermined observation point in a superstructure of a bridge as a response caused by a movement of a railway train including one or more cars on the superstructure, the acceleration being detected by an acceleration sensor disposed at the predetermined observation point;
• acquiring a weight of the cars of the railway train based on the time-series acceleration data;
• acquiring environment information relating to a structure length of the superstructure, a car length of one of the cars of the railway train, and installation positions of wheels of the railway train contacting the superstructure;
• acquiring a deflection model of the superstructure of the bridge based on the time-series acceleration data and the environment information;
• deriving a fundamental frequency of a vibration of the superstructure due to the movement of the railway train on the superstructure based on a result of fast Fourier transform of the time-series acceleration data;
• deriving a passing period of time during which the railway train passes along the superstructure based on the time-series acceleration data and a predetermined threshold;
• deriving a number of the cars included in the railway train based on the environment information, the fundamental frequency, and the passing period of time;
• repeating the acquiring of the time-series acceleration data, the acquiring of the weight, the acquiring of the environment information, the acquiring of the deflection model, the deriving of the fundamental frequency, the deriving of the passing of time, and the deriving the number of the cars to obtain a total number of the cars of the railway trains that move on the superstructure during a predetermined period of time and a total weight of the weight of the cars of the railway trains that move on the superstructure during the predetermined period of time;
• and
• diagnosing a state of the superstructure of the bridge based on the derived total number of the cars included in the railway trains, the total weight of the railway trains, and the deflection model in consideration of a risk factor including a resonance phenomenon existing due to vibration of the superstructure caused by the acceleration.