Method for monitoring and analyzing large tunnel machines based on automatic collection of big data

A method for monitoring and analyzing large tunnel machines based on automatic collection of big data, comprising the following steps:

• Step 1, dividing a tunnel operation area:
• dividing the tunnel operation area into various tunnel operation sub-areas evenly according to an area;
• Step 2, obtaining environmental information of the tunnel operation sub-areas:
• monitoring environment of each tunnel operation sub-area to obtain the environmental information of each tunnel operation sub-area;
• Step 3, analyzing rock drilling difficulty of each tunnel operation sub-area:
• according to a model of a tunnel rock drill, extracting standard rock drilling intensity of the tunnel rock drill from a WEB cloud, and analyzing a rock drilling difficulty coefficient of each tunnel operation sub-area in combination with the environmental information of each tunnel operation sub-area;
• Step 4, confirming a tunnel operation trajectory:
• according to the rock drilling difficulty coefficient of each tunnel operation sub-area, analyzing a steel rotating speed corresponding to each tunnel operation sub-area, and then confirming the tunnel operation trajectory;
• Step 5, analyzing conformity of each tunnel operation sub-area:
• after tunnel operation is completed, monitoring each tunnel operation sub-area and analyzing the operation conformity of each tunnel operation sub-area;
• Step 6, processing an abnormal tunnel operation sub-area:
• screening out each abnormal tunnel operation sub-area and processing each abnormal tunnel operation sub-area;
• and
• Step 7, analyzing health state of a tunnel rock drill:
• after the processing of each abnormal tunnel operation sub-area is completed, monitoring the tunnel rock drill, calculating a health evaluation coefficient of the tunnel rock drill, and analyzing the health state of the tunnel rock drill.