Method and system for monitoring track tension in construction machinery

1. A method of monitoring track tension in construction machinery, the method comprising:

receiving data on predetermined major factors for monitoring track tension;

performing a machine learning algorithm based on the data to determine a track tension state; and

displaying information on the track tension state,

wherein the data on the major factors includes at least one of percent load at current speed, actual engine torque rate, or discharge pressure of hydraulic pump, and

wherein the major factors are factors remaining after removing data on factors having a learning contribution value lower than a predetermined learning contribution threshold value to the machine learning algorithm from operating characteristic factors.

2. The method of claim 1 , further comprising:

performing an operating mode for monitoring track tension.

3. The method of claim 1 , wherein the data on the major factors further include fuel consumption rate,

wherein the data on the major factors are obtained when an engine and a hydraulic pump installed in an upper swing body of the construction machinery are operated.

4. The method of claim 1 , wherein performing the machine learning algorithm to determine the track tension state comprises,

performing the machine learning algorithm based on the data to calculate a short-term value for monitoring track tension; and

comparing the short-term value with a predetermined threshold value to determine the track tension state.

5. The method of claim 1 , further comprising:

providing the information on the track tension state to a server through a remote management device installed in the construction machinery.

6. The method of claim 1 , further comprising:

predicting and providing a lifespan of track-related components by using the information on the track tension state.

7. The method of claim 1 , further comprising:

adjusting tension of the track based on the information on the track tension state.