Maintenance road segment dividing method based on multisource detection data
A technology for detecting data and road sections, applied in data processing applications, electrical digital data processing, special data processing applications, etc., can solve the lack of pertinence in the guidance of road section division results, the continuity of road section division results is not considered, and the main road diseases are not involved. type, etc.
Inactive Publication Date: 2015-01-07
CHANGAN UNIV
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There are few studies on the selection of indicators in road section division and the application of the minimum unit length. Most studies use 1 mile as the smallest unit of road section division. Only a few researchers collect 10m or 100m data to divide road sections, but they have not studied the smallest unit. The influence of length on division results
The selection of indicators is mostly rating, SFC and roughness (these data are obtained through regular testing data), etc., which do not involve the main disease types of the road, and cannot distinguish road sections with similar road surface conditions but different dominant diseases, which may easily cause road section division results to affect maintenance measures. Selection guidance lacks focus
The domestic research is relatively late, the research method is relatively simple, and many clustering methods do not consider the limitation of the continuity of the road segment division results
Although some researchers have realized that the simple average value of 1 km of road conditions has weakened the specificity and meticulousness of the original actual measurement work to a certain extent, but because they have not fully grasped the content of the existing detection data, the average value of 1 km is still used to represent the value of 100m As the smallest unit for dividing road sections, on the one hand, the result of maintenance division is subject to the limit of the average value of the road surface condition per kilometer;
[0004] In summary, most of the existing research methods use regular inspection data (the frequency of regular inspection is once a year or once every two years (anti-skid performance)) for road condition clustering (averaging 1km inspection data), this method cannot distinguish Road sections with similar road surface conditions but different dominant diseases, and the average 1km detection data will optimize the road conditions. More importantly, the existing methods ignore the daily inspection data (the detection frequency of daily inspection data is once a day, which can reflect road diseases from The time sequence from occurrence to maintenance, the characteristics of the disease at different stages, the historical situation of minor repairs and maintenance (time, measures, service life (effect)), etc., for the judgment of the cause of the later disease, the judgment of the road section where the disease occurs frequently, and the treatment measures for the disease It has important reference significance for the selection of road maintenance) on the division of maintenance road sections
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[0083] The present invention takes the regular inspection results and daily inspection data of a certain section of expressway in Shaanxi Province in June 2012 as an example. 1) The daily inspection data module collects the daily inspection record table of the section in 2011 and the first half of 2012 to summarize the road section The occurrence frequency, location, maintenance history of different diseases, etc., summarize the dominant diseases at different mileages in June 2012, and select targeted maintenance measures in the auxiliary maintenance section. Due to the imperfect method of daily inspection records, only the dominant disease types of the road can be obtained, and the severity of the disease is lacking. 2) The regular inspection data module can obtain the values of PSSI, PCI, RQI, RDI, SRI per kilometer, as well as the ten-meter flatness, ten-meter rut and ten-meter road damage value according to the annual inspection. Due to the limited data collected, there is...
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The invention relates to a road maintenance technology, in particular to a maintenance road segment dividing method based on multisource detection data. The maintenance road segment dividing method based on multisource detection data includes extracting favorable road segment dividing information from sufficient digging of daily patrol data, regular detection data and special detection data to obtain the optimum road segment demarcation points of different classification numbers; on this basis, obtaining the optimum classification number after considering the correspondence of maintenance funds and the road segment conditions; finally, analyzing the type and severity of daily patrol data diseases to improve the road segment dividing pertinency. The maintenance road segment dividing method overcomes the defect of the existing road segment dividing method of being incapable of distinguishing road segments with similar road conditions but different dominant diseases, obtains the road segment dividing results with similar road performance, disease types and severity, and guides selection of maintenance measures.
Description
Technical field [0001] The invention relates to a road maintenance technology, in particular to a maintenance road section division method based on multi-source detection data. Background technique [0002] Due to differences in traffic conditions and maintenance history, the pavement conditions of each section of the road may be different, and it is expensive to implement the same maintenance measures on different sections. In order to meet the needs of dividing sections with different structures and functions, section division technology came into being. Reasonable maintenance section division can classify the units with similar pavement properties into one segment, and the maintenance design based on reasonable section division can formulate reasonable maintenance plans and save maintenance funds. [0003] Regarding the division method of maintenance road sections, through domestic and foreign research, it can be found that foreign research on road section division is relativel...
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Login to View More IPC IPC(8): G06F17/30
CPCG06Q10/04
Inventor 惠冰燕姣丁梦华崔卜心李甜甜王雪
Owner CHANGAN UNIV