CN115096253B - Roadbed monitoring method and system for high-mobility rescue equipment - Google Patents
Roadbed monitoring method and system for high-mobility rescue equipment Download PDFInfo
- Publication number
- CN115096253B CN115096253B CN202210630402.4A CN202210630402A CN115096253B CN 115096253 B CN115096253 B CN 115096253B CN 202210630402 A CN202210630402 A CN 202210630402A CN 115096253 B CN115096253 B CN 115096253B
- Authority
- CN
- China
- Prior art keywords
- road section
- information
- parameter
- road
- roadbed
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 65
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000012360 testing method Methods 0.000 claims abstract description 113
- 238000012545 processing Methods 0.000 claims abstract description 33
- 238000004458 analytical method Methods 0.000 claims abstract description 16
- 238000001514 detection method Methods 0.000 claims description 29
- 238000000605 extraction Methods 0.000 claims description 16
- 238000010219 correlation analysis Methods 0.000 claims description 9
- 238000003709 image segmentation Methods 0.000 claims description 8
- 238000004891 communication Methods 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 2
- 230000011218 segmentation Effects 0.000 claims description 2
- 230000000694 effects Effects 0.000 abstract description 5
- 239000002689 soil Substances 0.000 description 18
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 11
- 238000003745 diagnosis Methods 0.000 description 4
- 239000011148 porous material Substances 0.000 description 4
- 230000002265 prevention Effects 0.000 description 3
- 238000004062 sedimentation Methods 0.000 description 3
- 241000510097 Megalonaias nervosa Species 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000000638 solvent extraction Methods 0.000 description 2
- 239000004575 stone Substances 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000003708 edge detection Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000007493 shaping process Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
-
- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02D—FOUNDATIONS; EXCAVATIONS; EMBANKMENTS; UNDERGROUND OR UNDERWATER STRUCTURES
- E02D1/00—Investigation of foundation soil in situ
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K13/00—Thermometers specially adapted for specific purposes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L11/00—Measuring steady or quasi-steady pressure of a fluid or a fluent solid material by means not provided for in group G01L7/00 or G01L9/00
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/24—Earth materials
- G01N33/246—Earth materials for water content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
-
- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02D—FOUNDATIONS; EXCAVATIONS; EMBANKMENTS; UNDERGROUND OR UNDERWATER STRUCTURES
- E02D2600/00—Miscellaneous
- E02D2600/10—Miscellaneous comprising sensor means
Abstract
The application provides a method and a system for monitoring a roadbed of high-mobility rescue equipment, which relate to the technical field of high-mobility rescue, and are characterized in that an image acquisition processing device is used for acquiring a roadbed image of the high-mobility rescue equipment, road section type analysis is carried out on the roadbed image, and a plurality of road section category information corresponding to the roadbed of the high-mobility rescue equipment is determined; acquiring information of a plurality of road section categories by arranging sensors on each road section, and acquiring road section information corresponding to the road section categories; according to the corresponding relation between the plurality of road section category information and the road section information corresponding to the plurality of road section categories, associating each road section category information with the corresponding road section information; and comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions, so as to reach the purpose of fuzzing the current state of the road foundation, improve the supervision and management level of the road foundation and lead the technical effects of diagnosing and preventing the occurrence of safety accidents.
Description
Technical Field
The application relates to the technical field related to high-mobility rescue, in particular to a roadbed monitoring method and system for high-mobility rescue equipment.
Background
In disaster sites such as earthquake, fire disaster, safe production and the like, urgent demands of corresponding emergency rescue equipment are highlighted by the urgency of emergency rescue tasks. The use of the emergency rescue equipment can greatly improve the fight force of rescue teams, rapidly and efficiently treat various disasters, especially sudden serious disasters, greatly reduce casualties of rescue personnel and property loss of the country, and the current rescue equipment becomes a bottleneck for restricting the rescue efficiency of serious disasters in China, so that the development of high-mobility emergency rescue system equipment is urgent.
In order to meet the requirements of the high-mobility rescue equipment on the aspects of new product shaping test, mandatory test and the like, various test roads are required to be built in a high-mobility rescue equipment test field, including a ring runway which runs at a high speed, a rough and uneven bad road which can cause strong jolt of an automobile, wading, steep slopes and the like, and various road conditions and use conditions encountered by the high-mobility rescue equipment in the running process are reproduced.
In order to ensure smooth performance of a test, stable pavement test conditions are provided for high-mobility rescue equipment, the requirement on the roadbed of the high-mobility rescue equipment is higher and higher, the existing roadbed monitoring method is large in monitoring error, time and labor are wasted, the roadbed cannot be monitored in real time, roadbed failure is caused, monitoring of the roadbed state is accurately and comprehensively carried out, and the technical problem to be solved is urgent at present.
Disclosure of Invention
The application provides a roadbed monitoring method and a roadbed monitoring system for high-mobility rescue equipment, which are used for realizing the technical problem of real-time monitoring of the state of a roadbed aiming at solving the technical problem of accurately and comprehensively monitoring the state of the roadbed of the high-mobility rescue equipment, achieving the purpose of backing the current state of the roadbed, improving the supervision and management level of the roadbed and leading diagnosis and prevention of safety accidents.
In view of the above problems, the application provides a method and a system for monitoring a roadbed of high-mobility rescue equipment.
In a first aspect, an embodiment of the present application provides a method for monitoring a roadbed of high mobility rescue equipment, where the method is applied to a roadbed monitoring system of high mobility rescue equipment, the system includes an image acquisition processing device and a monitoring module, where the monitoring module includes a plurality of sensors, and the method includes: acquiring a roadbed image of the high-mobility rescue equipment by using an image acquisition and processing device, performing road section category analysis on the roadbed image of the high-mobility rescue equipment, and determining a plurality of road section category information corresponding to the roadbed of the high-mobility rescue equipment; acquiring information of a plurality of road section categories by setting sensors on each road section, and acquiring road section information corresponding to the road section categories; according to the corresponding relation between the road section category information and the road section information corresponding to the road section categories, associating the road section category information with the corresponding road section information; comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions; and sending an early warning signal according to the early warning information.
In a second aspect, embodiments of the present application provide a roadbed monitoring system for high mobility rescue equipment, the system comprising: the image acquisition processing device is used for acquiring road bed images of the high mobility rescue equipment, carrying out road section category analysis on the road bed images of the high mobility rescue equipment and determining a plurality of road section category information corresponding to the road bed of the high mobility rescue equipment; the monitoring module comprises a plurality of sensors, and the sensors are arranged on each road section to acquire information of a plurality of road section categories, so that road section information corresponding to the road section categories is obtained; the data processing module is in communication connection with the image acquisition device and the monitoring module and is used for associating each road section category information with the corresponding road section information according to the corresponding relation between the road section category information and the road section information corresponding to the road section categories; comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions; and the early warning module is connected with the data processing module, receives the early warning information and sends an early warning signal.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the method and the system for constructing the modularized simulation model of the typical control method provided by the embodiment of the application acquire the roadbed image of the high-mobility rescue equipment by utilizing the image acquisition and processing device, perform road section category analysis on the roadbed image of the high-mobility rescue equipment, and determine a plurality of road section category information corresponding to the roadbed of the high-mobility rescue equipment; acquiring information of a plurality of road section categories by setting sensors on each road section, and acquiring road section information corresponding to the road section categories; according to the corresponding relation between the road section category information and the road section information corresponding to the road section categories, associating the road section category information with the corresponding road section information; comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions; and sending an early warning signal according to the early warning information. The method solves the technical problems of accurately and comprehensively monitoring the state of the roadbed of the high-mobility rescue equipment, realizing the real-time monitoring of the state of the roadbed, achieving the purpose of backing the current state of the roadbed, improving the supervision and management level of the roadbed and leading the diagnosis and the prevention of the occurrence of safety accidents.
Drawings
FIG. 1 is a schematic flow chart of a method for monitoring a roadbed of high mobility rescue equipment;
FIG. 2 is a schematic flow chart of obtaining a plurality of road section category information in a method for monitoring a roadbed of high-mobility rescue equipment;
FIG. 3 is a schematic flow chart of comparing the road section information with road section test setting parameters in the road bed monitoring method of the high mobility rescue equipment;
FIG. 4 is a schematic flow chart of the application for analyzing the matching degree of road information by the road section correlation information and the parameter information to be tested in the road bed monitoring method of the high-mobility rescue equipment;
FIG. 5 is a schematic diagram of a roadbed monitoring system for high mobility rescue equipment;
reference numerals illustrate: the system comprises an image acquisition processing device 11, a monitoring module 12, a data processing module 13 and an early warning module 14.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The application provides a roadbed monitoring method and a roadbed monitoring system for high-mobility rescue equipment, which are used for solving the technical problem of accurately and comprehensively monitoring the roadbed state of the high-mobility rescue equipment, realizing the real-time monitoring of the roadbed state, achieving the purpose of backing the current state of the roadbed, improving the supervision and management level of the roadbed and leading the diagnosis to prevent the occurrence of safety accidents.
Example 1
As shown in fig. 1, the present application provides a method for monitoring a roadbed of high-mobility rescue equipment, which is applied to a roadbed monitoring system of high-mobility rescue equipment, the system comprises an image acquisition processing device and a monitoring module, wherein the monitoring module comprises a plurality of sensors, and the method comprises:
s100: acquiring a roadbed image of the high-mobility rescue equipment by using an image acquisition and processing device, performing road section category analysis on the roadbed image of the high-mobility rescue equipment, and determining a plurality of road section category information corresponding to the roadbed of the high-mobility rescue equipment;
in particular, in order to ensure the smooth execution of different test tests, the roadbed is required to have good integrity and sedimentation uniformity in the whole service process, stable pavement test conditions are provided for high-mobility rescue equipment, and various road conditions and use conditions encountered by the high-mobility rescue equipment in the running process are reproduced.
The method comprises the steps of collecting road bed images of high-mobility rescue equipment through an image collecting and processing device, quantifying, converting into digital images, inputting the digital images into a frame memory, and storing the digital images into the frame memory, wherein analysis processing of the road bed images of the high-mobility rescue equipment is realized through an image processing module in the image collecting and processing device, and a plurality of road section category information corresponding to the road bed of the high-mobility rescue equipment is obtained, wherein the road section category information comprises road section category information such as washboard roads, stone roads, long wave roads, pebble roads, steep slopes and the like. According to the road bed classification information processing method and device, road bed class information is obtained through analysis of the road bed image, road bed monitoring is achieved based on the plurality of road bed class information, classification processing of data is achieved through partitioning of the road bed, and processing capacity and speed of the data are improved.
As shown in fig. 2, step S100 in the method provided by the embodiment of the present application includes:
s110: extracting the characteristics of the roadbed image of the high-mobility rescue equipment;
s120: carrying out feature identification on the roadbed image of the high maneuver rescue equipment according to the feature extraction result, and determining feature change position nodes according to the feature identification;
s130: and performing image segmentation on the acquired roadbed image based on the characteristic change position node to acquire a plurality of road section category information.
Specifically, in order to realize the partition of the roadbed, the obtained roadbed image is analyzed and processed. In order to prevent noise images possibly existing in the collected roadbed images and further influence the subsequent data processing results, the collected roadbed images are preferably subjected to denoising pretreatment before feature extraction, irrelevant information in the images is eliminated, useful real information is recovered, the images are clearer and smoother, and more effective and more accurate data support is provided for the subsequent data processing of the target product production image set; further, in order to facilitate image processing, the denoised roadbed image is subjected to display color space conversion, the image is converted into a gray space from an RGB space, threshold value calculation is performed point by point for each pixel in the gray image by utilizing image binarization, and detail information of the image is stored.
The method for image segmentation comprises the steps of performing feature extraction on the processed high mobility rescue equipment roadbed image, dividing the image into a plurality of mutually disjoint areas according to the features such as gray scale, color, space texture and geometric shape, performing feature identification on the high mobility rescue equipment roadbed image according to feature extraction results, wherein the feature identification is the boundary of different areas, determining feature change position nodes according to the feature identification, and performing image segmentation on the acquired roadbed image based on the feature change position nodes, wherein the method for image segmentation can comprise the following steps: the method based on edge detection, the method based on region generation and the like are used for realizing image segmentation, so that a plurality of road section category information are obtained, and the roadbed image is partitioned.
S200: acquiring information of a plurality of road section categories by setting sensors on each road section, and acquiring road section information corresponding to the road section categories;
specifically, the road section information is a parameter of a road section corresponding to a plurality of road section categories, and the road section information may include information such as a settlement size of the road section, a temperature of a roadbed, a soil moisture content, a roadbed soil pressure, a pore water pressure, and the like. In order to obtain road segment information, various sensors, such as a displacement sensor, a temperature sensor, a soil moisture sensor, and a soil pressure sensor, are provided on different types of road segments. And the pore water pressure sensor is used for collecting data information of a plurality of road section categories to obtain road section information corresponding to the road section categories, each road section category corresponds to a plurality of road section parameters, and accurate monitoring of roadbed is ensured by collecting a plurality of parameters of each road section category.
S300: according to the corresponding relation between the road section category information and the road section information corresponding to the road section categories, associating the road section category information with the corresponding road section information;
specifically, in the previous step, the road section information is collected for each road section category, each road section category has the corresponding road section information, the collected road section information and the road section category corresponding to the road section information are associated, so that the road section category information and the road section information corresponding to the road section category are in one-to-one correspondence, and the classification processing of the data is realized.
S400: comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions;
s500: and sending an early warning signal according to the early warning information.
Specifically, when the road section test setting parameters are performance parameters required to be provided by the roadbed for reliability test of high-speed motor rescue equipment, road section information corresponding to a plurality of road section categories is compared with the road section test setting parameters one by one, when any parameter in the road section information does not meet the road section setting parameters, the road section cannot complete normal test, early warning information is generated, early warning signals are sent according to the early warning information, workers are prompted that a certain road section cannot complete test requirements, the current situation of the roadbed is reached, the supervision and management level of the roadbed is improved, and the technical effect of preventing safety accidents is diagnosed in advance.
As shown in fig. 3, step S400 in the method provided in the embodiment of the present application includes:
s410: identifying the road section information corresponding to the plurality of road section categories, wherein the identifying information comprises the road section category, the road section information and the road section quality grade;
s420: comparing the road section information corresponding to the road section categories with road section test setting parameters one by one to obtain parameter comparison results, wherein the parameter comparison results comprise multi-parameter comparison results;
s430: judging whether the multi-parameter comparison result meets the set threshold of each parameter or not respectively;
s440: and when the parameter is not satisfied, determining the road section information according to the identification information identification of the road section information corresponding to the parameter.
Specifically, in the process of comparing the road section information with the road section test setting parameters, in order to quickly identify the road section which does not meet the road section test setting parameters, identifying the road section information corresponding to the road section categories, wherein the identifying information comprises the road section category, the road section information and the road section quality grade, and the road section quality grade is obtained by comparing the road section information with the road section test setting parameters; comparing the road section information corresponding to the road section categories with road section test setting parameters one by one to obtain parameter comparison results, wherein the parameter comparison results comprise multi-parameter comparison results; for example, the comparison result of the sedimentation size of the road section, the temperature of the roadbed, the water content of the soil, the soil pressure of the roadbed and the pore water pressure; respectively judging whether the multi-parameter comparison result meets the set threshold of each parameter, and determining the road section information according to the identification information mark of the road section information corresponding to the parameter when the multi-parameter comparison result does not meet the set threshold of each parameter; and further, the road section information which does not meet the requirements is rapidly acquired, and further, corresponding measures are taken to avoid accidents.
For example, it is assumed that the identification information is identified according to the order of road section category, road section information and road section quality grade, wherein the road section category is identified according to the order of washboard road, stone road, long wave road, pebble road and steep slope road; the quality grade of the road section information can be represented by A, B, C according to the sequence forbidden identification of the sedimentation size of the road section, the temperature of the road bed, the soil water content, the soil pressure of the road bed and the pore water pressure, for example, the identification information 34B represents the soil pressure of the road bed of a long slope road, and the quality grade of the road section is B; when the roadbed soil pressure in the road section information does not meet the road section test setting parameters, the corresponding road section category can be quickly found according to the first position in the road section identification information, and then the roadbed soil pressure of the road section category is pre-warned and maintained.
The method for determining the road section test setting parameters in the step S400 in the method provided by the embodiment of the application comprises the following steps:
s421: obtaining site test parameter information and a vehicle parameter set;
s422: performing test requirement correlation analysis based on the site test parameter information and the vehicle parameter set, and determining a road section test parameter range;
s423: and determining the road section test setting parameters based on the road section test parameter range, wherein the road section test setting parameters are the minimum requirements in the road section test parameter range.
Specifically, in order to determine road section test setting parameters, in the embodiment of the application, field test parameter information of a test field is obtained, wherein the field test parameter information comprises parameter information corresponding to each road section category, for example, parameter information such as gradient corresponding to a steep slope section, wading depth corresponding to a wading section, water flow speed and the like; the vehicle parameter set can comprise information sets such as the model number of the vehicles, the number of the vehicles, vehicle test parameters and the like; the road segment test parameter range is determined in combination with the site test parameter information and the vehicle parameter information. For example, assume that taking a steep slope road section as an example, obtaining a slope angle of the steep slope road section and combining the model of a vehicle, for example, whether parameter information such as a larger rescue vehicle or a relatively smaller rescue vehicle, a traveling speed of the rescue vehicle and the like is obtained, and determining a road bed bearable range as a road section test parameter range; the road section test setting parameters are the minimum requirements in the road section test parameter range, and the minimum requirements of the vehicle for smoothly testing can be met. And further, the determination of the road segment test setting parameters is achieved.
Further, the method provided by the embodiment of the application further comprises the following steps:
s600: obtaining road surface information of a plurality of road section categories through feature extraction;
s700: the road surface information and the multi-parameter comparison result are combined to monitor the state of the road bed;
s800: and analyzing the monitoring result to obtain early warning information.
Specifically, in order to improve accuracy of roadbed monitoring results, in this embodiment, road surface information of multiple road section categories is obtained through an image feature extraction method; the feature extraction can adopt methods such as color histogram, image feature extraction based on color moment and the like; the road surface information is a surface feature of the road surface, for example, a pebble road, whether pebbles are ground flat or not; the gradient of the steep slope road is destroyed or not, and the road surface information such as gradient requirements is not met; and under the condition that the road section information corresponding to the road section categories is compared with the road section test setting parameters one by one to obtain a multi-parameter comparison result, the road base state is monitored by combining the road surface information, so that the aim of improving the accuracy of the road base state monitoring result is fulfilled.
As shown in fig. 4, step S800 in the method provided in the embodiment of the present application includes:
s810: obtaining historical detection data of a sensor and corresponding roadbed images of historical high-mobility rescue equipment, wherein the roadbed images of the historical high-mobility rescue equipment correspond to the acquisition time of the historical detection data one by one;
s820: constructing a change curve of the detection parameters based on the sensor history detection data;
s830: obtaining a road section road surface change curve based on the historical high-mobility rescue equipment roadbed image;
s840: carrying out correlation analysis according to the change curve of the detection parameter and the road surface change curve of the road section to obtain road section correlation information;
s850: obtaining parameter information to be tested;
s860: and carrying out matching degree analysis on the road surface information according to the road section correlation information and the parameter information to be tested, and obtaining early warning information when the road surface information is not matched.
Specifically, in order to fully utilize the historical data and achieve the purpose of improving the accuracy of the monitoring result of the roadbed state by using the historical data as a reference, the historical detection data and roadbed images of each road section sensor are obtained, and the time for acquiring the sensor historical detection data is the same as the time for acquiring the roadbed images; constructing a change curve of detection parameters based on the sensor history detection data, for example, taking a soil moisture content parameter in a long slope as an example, and changing the soil moisture content of the long slope along with time; obtaining a road section road surface change curve based on the historical high-mobility rescue equipment roadbed image, for example, taking a long slope road as an example, and changing a height change curve of the road section road surface along the direction vertical to the ground along time; carrying out correlation analysis according to the change curve of the detection parameter and the road section road surface change curve to obtain the correlation between the multi-parameter change curve corresponding to each road section and the road section road surface change curve; by way of example, taking a long-slope road as an example, obtaining a road section road surface change curve obtained by obtaining a long-slope road historical settlement size, a road bed temperature, a soil water content, a road foundation soil pressure, a gap water pressure change curve and road section road surface change curves obtained by corresponding time-collected road bed images, obtaining a relation between any time settlement size, the road bed temperature, the soil water content, the road foundation soil pressure, the gap water pressure and road section road surface conditions, and obtaining road section correlation information, wherein the road section correlation information is correlation between a change curve of detection parameters and the road section road surface change curve. And carrying out matching degree analysis on the road information according to the road section correlation information and the parameter information to be tested, and obtaining early warning information when the road section correlation information and the parameter information to be tested are not matched, so as to reach the technical effects of fuzzing the current state of the road foundation, improving the supervision and management level of the road foundation and diagnosing and preventing the occurrence of safety accidents in advance.
Step S860 in the method provided by the embodiment of the present application includes:
s861: obtaining a test plan;
s862: obtaining vehicle information to be tested based on the test plan, wherein the vehicle information to be tested comprises: the vehicle model number, the vehicle number and the test parameters, and further obtaining the parameter information to be tested;
s863: comparing the road section correlation information with parameter information to be tested, and obtaining early warning information when the road section correlation information does not meet the parameter information to be tested;
s864: and when the road section correlation information meets the parameter information to be tested, performing vehicle testing.
Specifically, a test plan of each road section is obtained, the test plan includes information of a vehicle to be tested, test time schedule, test road section category and the like, the information of the vehicle to be tested is obtained based on the test plan, and the information of the vehicle to be tested includes: the method comprises the steps of obtaining parameter information to be tested by vehicle types, number and test parameters, comparing the parameter information to be tested with the road section correlation information, judging whether the road section correlation information meets the parameter information to be tested, and when the road section correlation information does not meet the parameter information to be tested, for example, if the road foundation soil pressure parameter of a certain road section does not meet the requirement of the parameter information to be tested, obtaining early warning information, reminding a worker that the road section cannot be tested, and avoiding the safety accident from damaging operators and rescue equipment; when the road section correlation information meets the parameter information to be tested, continuing to perform vehicle testing according to a test plan; by monitoring the road base state in real time, stable road surface test conditions are provided for high-mobility rescue equipment.
In summary, the method for monitoring the roadbed of the high-mobility rescue equipment provided by the embodiment of the application has the following technical effects:
1. according to the road bed monitoring method for the high-mobility rescue equipment, provided by the embodiment of the application, the road bed image of the high-mobility rescue equipment is acquired by utilizing the image acquisition and processing device, road section category analysis is carried out on the road bed image of the high-mobility rescue equipment, a plurality of road section category information corresponding to the road bed of the high-mobility rescue equipment is determined, and the purpose of improving the data processing speed and accuracy is achieved by partitioning the road bed; acquiring information of a plurality of road section categories by setting sensors on each road section, and acquiring road section information corresponding to the road section categories; according to the corresponding relation between the road section category information and the road section information corresponding to the road section categories, associating the road section category information with the corresponding road section information; comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions; and sending an early warning signal according to the early warning information. The method solves the technical problems of accurately and comprehensively monitoring the state of the roadbed of the high-mobility rescue equipment, realizing the real-time monitoring of the state of the roadbed, achieving the purpose of backing the current state of the roadbed, improving the supervision and management level of the roadbed and leading the diagnosis and the prevention of the occurrence of safety accidents.
2. According to the embodiment of the application, the information identification is carried out on the road section information corresponding to the plurality of road section categories, if the parameters do not meet the requirements in the parameter comparison process, the road section information is determined according to the identification information identification of the road section information corresponding to the parameters, so that the road section information which does not meet the requirements is rapidly acquired, and further corresponding measures are taken to avoid accidents.
3. In the embodiment of the application, the detection of the road base state is realized from multiple aspects by collecting the historical data of the sensor and combining the historical information of the road surface of the road section, so that the full utilization of the historical data is realized, and the aim of improving the accuracy of the road base state monitoring result by using the historical data as a reference is fulfilled.
Example two
Based on the same inventive concept as one of the aforementioned embodiments for a high mobility rescue equipment subgrade monitoring method, as shown in fig. 5, the present application provides a subgrade monitoring system for high mobility rescue equipment, wherein the system comprises:
the image acquisition processing device 11 acquires road bed images of the high mobility rescue equipment by utilizing the image acquisition processing device, performs road section category analysis on the road bed images of the high mobility rescue equipment, and determines a plurality of road section category information corresponding to the road bed of the high mobility rescue equipment;
the monitoring module 12 includes a plurality of sensors, and acquires road section information corresponding to a plurality of road section categories by setting a sensor on each road section to acquire information of the plurality of road section categories;
the data processing module 13 is in communication connection with the image acquisition device and the monitoring module, and is used for associating each road section category information with the corresponding road section information according to the corresponding relation between the road section category information and the road section information corresponding to the road section categories;
comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions;
and the early warning module 14 is connected with the data processing module, receives the early warning information and sends an early warning signal.
Further, the image acquisition processing device in the system further comprises:
the feature extraction module is used for extracting features of the roadbed image of the high-mobility rescue equipment;
the feature identification module is used for carrying out feature identification on the roadbed image of the high maneuver rescue equipment according to the feature extraction result and determining a feature change position node according to the feature identification;
and the feature segmentation module is used for carrying out image segmentation on the acquired roadbed images based on the feature change position nodes to obtain a plurality of road section category information.
Further, the system further comprises:
the information identification module is used for identifying the road sections corresponding to the plurality of road section categories, wherein the identification information comprises the road section categories, the road section information and the road section quality grades;
the parameter comparison module is used for comparing the road section information corresponding to the road section categories with road section test setting parameters one by one to obtain a parameter comparison result, wherein the parameter comparison result comprises a multi-parameter comparison result;
the judging module is used for judging whether the multi-parameter comparison result meets the set threshold value of each parameter or not;
and the information determining module is used for determining the road section information according to the identification information identification of the road section information corresponding to the parameter when the road section information is not satisfied.
Further, the system further comprises:
the information acquisition module is used for acquiring site test parameter information and a vehicle parameter set;
the road section test parameter determining module is used for carrying out test requirement correlation analysis based on the site test parameter information and the vehicle parameter set and determining a road section test parameter range;
and the road section test setting parameter determining module is used for determining the road section test setting parameter based on the road section test parameter range, wherein the road section test setting parameter is the minimum requirement in the road section test parameter range.
Further, the system further comprises:
the road surface information acquisition module acquires road surface information of a plurality of road section categories through feature extraction;
the roadbed state monitoring module is used for monitoring the roadbed state by combining the road surface information and the multi-parameter comparison result;
and the early warning module analyzes the monitoring result to obtain early warning information.
Further, the system further comprises:
the historical data acquisition module acquires historical detection data of the sensor and corresponding roadbed images of the high-mobility rescue equipment, wherein the roadbed images of the high-mobility rescue equipment correspond to the acquisition time of the historical detection data one by one;
the detection parameter curve construction module is used for constructing a change curve of the detection parameters based on the historical detection data of the sensor;
the road section road surface obtaining module is used for obtaining a road section road surface change curve based on the historical high-mobility rescue equipment roadbed image;
the road section correlation information obtaining module is used for carrying out correlation analysis according to the change curve of the detection parameter and the road section road surface change curve to obtain road section correlation information;
the parameter information obtaining module to be tested obtains parameter information to be tested;
and the early warning second sub-module is used for carrying out matching degree analysis on the road surface information according to the road section correlation information and the parameter information to be tested, and acquiring early warning information when the road surface information is not matched.
Further, the system further comprises:
the test plan obtaining module is used for obtaining a test plan;
the to-be-tested parameter information obtaining sub-module obtains to-be-tested vehicle information based on the test plan, wherein the to-be-tested vehicle information comprises: the vehicle model number, the vehicle number and the test parameters, and further obtaining the parameter information to be tested;
the pre-warning module compares the road section correlation information with parameter information to be tested, and when the road section correlation information does not meet the parameter information to be tested, pre-warning information is obtained;
and the test module is used for carrying out vehicle test when the road section correlation information meets the parameter information to be tested.
The specific working process of the module disclosed in the above embodiment of the present application can be referred to the corresponding method embodiment content, and will not be described herein.
Those skilled in the art will be able to make or use the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (2)
1. A method for monitoring a roadbed of high-mobility rescue equipment, which is applied to a roadbed monitoring system of high-mobility rescue equipment, wherein the system comprises an image acquisition and processing device and a monitoring module, and the monitoring module comprises a plurality of sensors, and is characterized in that the method comprises the following steps:
s100: acquiring a roadbed image of the high-mobility rescue equipment by using an image acquisition and processing device, performing road section category analysis on the roadbed image of the high-mobility rescue equipment, and determining a plurality of road section category information corresponding to the roadbed of the high-mobility rescue equipment;
s200: acquiring information of a plurality of road section categories by setting sensors on each road section, and acquiring road section information corresponding to the road section categories;
s300: according to the corresponding relation between the road section category information and the road section information corresponding to the road section categories, associating the road section category information with the corresponding road section information;
s400: comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions;
s500: sending an early warning signal according to the early warning information;
the step S100 includes:
s110: extracting the characteristics of the roadbed image of the high-mobility rescue equipment;
s120: carrying out feature identification on the roadbed image of the high maneuver rescue equipment according to the feature extraction result, and determining feature change position nodes according to the feature identification;
s130: image segmentation is carried out on the collected roadbed images based on the characteristic change position nodes, and a plurality of road section category information is obtained;
the step S400 includes:
s410: identifying the road sections corresponding to the plurality of road section categories, wherein the identification information comprises the road section categories, the road section information and the road section quality grades;
s420: comparing the road section information corresponding to the road section categories with road section test setting parameters one by one to obtain parameter comparison results, wherein the parameter comparison results comprise multi-parameter comparison results;
s430: judging whether the multi-parameter comparison result meets the set threshold of each parameter or not respectively;
s440: when the parameter is not satisfied, determining the road section information according to the identification information identification of the road section information corresponding to the parameter;
the method for determining the road segment test setting parameters in the step S400 includes:
s421: obtaining site test parameter information and a vehicle parameter set;
s422: performing test requirement correlation analysis based on the site test parameter information and the vehicle parameter set, and determining a road section test parameter range;
s423: determining the road section test setting parameters based on the road section test parameter range, wherein the road section test setting parameters are the minimum requirements in the road section test parameter range;
the method further comprises the steps of:
s600: obtaining road surface information of a plurality of road section categories through feature extraction;
s700: the road surface information and the multi-parameter comparison result are combined to monitor the state of the road bed;
s800: analyzing the monitoring result to obtain early warning information;
the step S800 includes:
s810: obtaining historical detection data of a sensor and corresponding roadbed images of historical high-mobility rescue equipment, wherein the roadbed images of the historical high-mobility rescue equipment correspond to the acquisition time of the historical detection data one by one;
s820: constructing a change curve of the detection parameters based on the sensor history detection data;
s830: obtaining a road section road surface change curve based on the historical high-mobility rescue equipment roadbed image;
s840: carrying out correlation analysis according to the change curve of the detection parameter and the road surface change curve of the road section to obtain road section correlation information;
s850: obtaining parameter information to be tested;
s860: carrying out matching degree analysis on the road surface information according to the road section correlation information and the parameter information to be tested, and obtaining early warning information when the road section correlation information and the parameter information to be tested are not matched;
the step S860 includes:
s861: obtaining a test plan;
s862: obtaining vehicle information to be tested based on a test plan, wherein the vehicle information to be tested comprises: the vehicle model number, the vehicle number and the test parameters, and further obtaining the parameter information to be tested;
s863: comparing the road section correlation information with parameter information to be tested, and obtaining early warning information when the road section correlation information does not meet the parameter information to be tested;
s864: and when the road section correlation information meets the parameter information to be tested, performing vehicle testing.
2. A roadbed monitoring system for high mobility rescue equipment, the system comprising:
the image acquisition processing device is used for acquiring road bed images of the high mobility rescue equipment, carrying out road section category analysis on the road bed images of the high mobility rescue equipment and determining a plurality of road section category information corresponding to the road bed of the high mobility rescue equipment;
the monitoring module comprises a plurality of sensors, and the sensors are arranged on each road section to acquire information of a plurality of road section categories, so that road section information corresponding to the road section categories is obtained;
the data processing module is in communication connection with the image acquisition device and the monitoring module and is used for associating each road section category information with the corresponding road section information according to the corresponding relation between the road section category information and the road section information corresponding to the road section categories;
comparing the road section information with road section test setting parameters, and generating early warning information when the road section information does not meet preset conditions;
the early warning module is connected with the data processing module, receives the early warning information and sends an early warning signal;
the feature extraction module is used for extracting features of the roadbed image of the high-mobility rescue equipment;
the feature identification module is used for carrying out feature identification on the roadbed image of the high maneuver rescue equipment according to the feature extraction result and determining a feature change position node according to the feature identification;
the feature segmentation module is used for carrying out image segmentation on the collected roadbed images based on the feature change position nodes to obtain a plurality of road section category information;
the information identification module is used for identifying the road sections corresponding to the plurality of road section categories, wherein the identification information comprises the road section categories, the road section information and the road section quality grades;
the parameter comparison module is used for comparing the road section information corresponding to the road section categories with road section test setting parameters one by one to obtain a parameter comparison result, wherein the parameter comparison result comprises a multi-parameter comparison result;
the judging module is used for judging whether the multi-parameter comparison result meets the set threshold value of each parameter or not;
the information determining module is used for determining the road section information according to the identification information identification of the road section information corresponding to the parameter when the information is not satisfied;
the information acquisition module is used for acquiring site test parameter information and a vehicle parameter set;
the road section test parameter determining module is used for carrying out test requirement correlation analysis based on the site test parameter information and the vehicle parameter set and determining a road section test parameter range;
the road section test setting parameter determining module is used for determining the road section test setting parameter based on the road section test parameter range, wherein the road section test setting parameter is the minimum requirement in the road section test parameter range;
the road surface information acquisition module acquires road surface information of a plurality of road section categories through feature extraction;
the roadbed state monitoring module is used for monitoring the roadbed state by combining the road surface information and the multi-parameter comparison result;
the early warning module analyzes the monitoring result to obtain early warning information;
the historical data acquisition module acquires historical detection data of the sensor and corresponding roadbed images of the high-mobility rescue equipment, wherein the roadbed images of the high-mobility rescue equipment correspond to the acquisition time of the historical detection data one by one;
the detection parameter curve construction module is used for constructing a change curve of the detection parameters based on the historical detection data of the sensor;
the road section road surface obtaining module is used for obtaining a road section road surface change curve based on the historical high-mobility rescue equipment roadbed image;
the road section correlation information obtaining module is used for carrying out correlation analysis according to the change curve of the detection parameter and the road section road surface change curve to obtain road section correlation information;
the parameter information obtaining module to be tested obtains parameter information to be tested;
the early warning second sub-module is used for carrying out matching degree analysis on the road surface information according to the road section correlation information and the parameter information to be tested, and acquiring early warning information when the road surface information is not matched;
the test plan obtaining module is used for obtaining a test plan;
the to-be-tested parameter information obtaining sub-module obtains to-be-tested vehicle information based on the test plan, wherein the to-be-tested vehicle information comprises: the vehicle model number, the vehicle number and the test parameters, and further obtaining the parameter information to be tested;
the pre-warning module compares the road section correlation information with parameter information to be tested, and when the road section correlation information does not meet the parameter information to be tested, pre-warning information is obtained;
and the test module is used for carrying out vehicle test when the road section correlation information meets the parameter information to be tested.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210630402.4A CN115096253B (en) | 2022-06-06 | 2022-06-06 | Roadbed monitoring method and system for high-mobility rescue equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210630402.4A CN115096253B (en) | 2022-06-06 | 2022-06-06 | Roadbed monitoring method and system for high-mobility rescue equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115096253A CN115096253A (en) | 2022-09-23 |
| CN115096253B true CN115096253B (en) | 2023-11-07 |
Family
ID=83289935
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210630402.4A Active CN115096253B (en) | 2022-06-06 | 2022-06-06 | Roadbed monitoring method and system for high-mobility rescue equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115096253B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103616011A (en) * | 2013-12-06 | 2014-03-05 | 天津大学 | Automatic remote monitoring system for underground engineering deformation |
| CN104655639A (en) * | 2014-12-23 | 2015-05-27 | 北京恒达锦程图像技术有限公司 | Pavement crack detection method capable of accurately acquiring crack characteristics and pavement crack detection system capable of accurately acquiring crack characteristics |
| CN110631547A (en) * | 2019-09-26 | 2019-12-31 | 成都理工大学 | Roadbed monitoring and early warning system based on Internet of things |
| CN112378373A (en) * | 2020-11-02 | 2021-02-19 | 中山大学 | Road surface settlement and accumulated water monitoring system and method based on intelligent lamp pole |
| CN112964219A (en) * | 2021-02-05 | 2021-06-15 | 四川九通智路科技有限公司 | Pavement deformation monitoring method |
| CN114413832A (en) * | 2021-12-02 | 2022-04-29 | 中国通信建设第三工程局有限公司 | Road monitoring system and method based on optical fiber sensing |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110411408A (en) * | 2019-07-11 | 2019-11-05 | 浙江大学 | A kind of surface subsidence monitoring method based on computer vision |
-
2022
- 2022-06-06 CN CN202210630402.4A patent/CN115096253B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103616011A (en) * | 2013-12-06 | 2014-03-05 | 天津大学 | Automatic remote monitoring system for underground engineering deformation |
| CN104655639A (en) * | 2014-12-23 | 2015-05-27 | 北京恒达锦程图像技术有限公司 | Pavement crack detection method capable of accurately acquiring crack characteristics and pavement crack detection system capable of accurately acquiring crack characteristics |
| CN110631547A (en) * | 2019-09-26 | 2019-12-31 | 成都理工大学 | Roadbed monitoring and early warning system based on Internet of things |
| CN112378373A (en) * | 2020-11-02 | 2021-02-19 | 中山大学 | Road surface settlement and accumulated water monitoring system and method based on intelligent lamp pole |
| CN112964219A (en) * | 2021-02-05 | 2021-06-15 | 四川九通智路科技有限公司 | Pavement deformation monitoring method |
| CN114413832A (en) * | 2021-12-02 | 2022-04-29 | 中国通信建设第三工程局有限公司 | Road monitoring system and method based on optical fiber sensing |
Non-Patent Citations (1)
| Title |
|---|
| 成兴保.《电子设计工程》.2022,163-173. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115096253A (en) | 2022-09-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kim et al. | Review and analysis of pothole detection methods | |
| US9365217B2 (en) | Mobile pothole detection system and method | |
| Lekshmipathy et al. | Vibration vs. vision: Best approach for automated pavement distress detection | |
| CN111797669A (en) | Road abnormality detection apparatus, road abnormality detection method, and computer-readable medium | |
| CN112488995B (en) | Intelligent damage judging method and system for automatic maintenance of train | |
| CN116110012B (en) | Dangerous violation identification method and system for intelligent construction site | |
| CN116416401B (en) | Polluted site assessment method and system based on unmanned aerial vehicle aerial photography | |
| CN105761305A (en) | Vehicle driving detection method and system | |
| CN112633722A (en) | Vehicle-mounted road safety risk assessment system and method | |
| Benmhahe et al. | Automated pavement distress detection, classification and measurement: A review | |
| Leizerovych et al. | IoT-complex for monitoring and analysis of motor highway condition using artificial neural networks | |
| CN111610191B (en) | Road detection and repair system | |
| CN113139410B (en) | Pavement detection method, device, equipment and storage medium | |
| Kyriakou et al. | Roadway pavement anomaly classification utilizing smartphones and artificial intelligence | |
| CN107622656B (en) | Cross-region data processing method and system for key operation vehicle | |
| CN115096253B (en) | Roadbed monitoring method and system for high-mobility rescue equipment | |
| CN114971166A (en) | Lightweight road pavement service quality inspection system | |
| Kaushik et al. | Pothole Detection System: A Review of Different Methods Used for Detection | |
| Shtayat et al. | Using supervised machine learning algorithms in pavement degradation monitoring | |
| CN112637553B (en) | Bridge structure modal analysis method based on monitoring video | |
| Doycheva et al. | Computer vision and deep learning for real-time pavement distress detection | |
| CN111881566B (en) | Landslide displacement detection method and device based on live-action simulation | |
| Pooja et al. | An early warning system for traffic and road safety hazards using collaborative crowd sourcing | |
| CN112329858A (en) | Image recognition method for breakage fault of anti-loosening iron wire of railway motor car | |
| Hadjidemetriou et al. | Patch defects detection for pavement assessment, using smartphones and support vector machines |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |