Method and apparatus for determining working condition of excavator

Abstract

A method for determining a working condition of an excavator comprises: acquiring a real-time state parameter data of the excavator; inputting the real-time state parameter data into an excavator working condition determination model to obtain the working condition type of the excavator output by the excavator working condition determination model. The excavator working condition determination model is obtained by performing training based on state parameter data samples carrying working condition type labels. In the method, the required data is easy to acquire, and a large amount of data is used when training the excavator working condition determination model, so that the excavator working condition determination model has strong universality and makes it easy to determine the working condition of an excavator. An apparatus for determining a working condition of an excavator is also disclosed.

1 . A method for determining a working condition of an excavator, comprising:
 acquiring real-time state parameter data of an excavator;   inputting the real-time state parameter data into an excavator working condition determination model to obtain a working condition type of the excavator output by the excavator working condition determination model;   wherein, the excavator working condition determination model is obtained by performing training based on state parameter data samples carrying working condition type labels.   
     
     
         2 . The method for determining the working condition of the excavator according to  claim 1 , wherein the step of acquiring the real-time state parameter data of the excavator comprises:
 acquiring the real-time state parameter data of the excavator in each preset time segment in a target time period;   correspondingly, the step of inputting the real-time state parameter data into the excavator working condition determination model to obtain the working condition type of the excavator output by the excavator working condition determination model comprises:   respectively inputting the real-time state parameter data of the excavator in each preset time segment into the excavator working condition determination model to obtain a corresponding working condition type of the excavator in each preset time segment output by the excavator working condition determination model.   
     
     
         3 . The method for determining the working condition of the excavator according to  claim 2 , wherein after respectively inputting the real-time state parameter data of the excavator in each preset time segment into the excavator working condition determination model to obtain the corresponding working condition type of the excavator in each preset time segment output by the excavator working condition determination model, the method further comprises:
 determining a ratio of working condition type corresponding to each preset time segment based on the corresponding working condition type of the excavator in each preset time segment.   
     
     
         4 . The method for determining the working condition of the excavator according to  claim 2 , wherein after respectively inputting the real-time state parameter data of the excavator in each preset time segment into the excavator working condition determination model to obtain the corresponding working condition type of the excavator in each preset time segment output by the excavator working condition determination model, the method further comprises:
 uploading the corresponding working condition type of the excavator in each preset time segment and the real-time state parameter data of the excavator in each preset time segment onto a cloud data platform, performing aggregate calculation on the real-time state parameter data of the excavator in each preset time segment by the cloud data platform to obtain a target state parameter dataset of the excavator in each preset time segment, and storing the corresponding working condition type of the excavator in each preset time segment and the target state parameter dataset of the excavator in each preset time segment into a cloud data warehouse.   
     
     
         5 . The method for determining the working condition of the excavator according to  claim 4 , wherein after uploading the corresponding working condition type of the excavator in each preset time segment and the real-time state parameter data of the excavator in each preset time segment onto the cloud data platform, the method further comprises:
 performing a secondary training on the excavator working condition determination model based on the corresponding working condition type of the excavator in each preset time segment and the target state parameter dataset of the excavator in each preset time segment to obtain a secondarily retrained excavator working condition determination model;   updating the excavator working condition determination model based on the secondarily retrained excavator working condition determination model.   
     
     
         6 . The method for determining the working condition of the excavator according to  claim 1 , wherein the real-time state parameter data comprises at least one of engine speed, pilot pressure, electric current, pump pressure and service time. 
     
     
         7 . (canceled) 
     
     
         8 . An excavator, comprising: n apparatus for determining a working condition of an excavator, which is configured to determine the working condition type of the excavator, the apparatus for determining a working condition of an excavator comprises:
 a parameter data acquisition module, configured to acquire real-time state parameter data of an excavator;   an excavator working condition determining module, configured to input the real-time state parameter data into an excavator working condition determination model to obtain a working condition type of the excavator output by the excavator working condition determination model;   wherein, the excavator working condition determination model is obtained by performing training based on state parameter data samples carrying working condition type labels.   
     
     
         9 . An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the computer program, when executed by the processor, causes the processor to perform the steps of the method for determining the working condition of the excavator according to  claim 1 . 
     
     
         10 . (canceled)