CN115096253A - Roadbed monitoring method and system for high-mobility rescue equipment - Google Patents
Roadbed monitoring method and system for high-mobility rescue equipment Download PDFInfo
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- G—PHYSICS
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- 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
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- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
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- E02D1/00—Investigation of foundation soil in situ
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- 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
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- G—PHYSICS
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- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
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- 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
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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Abstract
The invention provides a method and a system for monitoring a roadbed of high-mobility rescue equipment, which relate to the related technical field of high-mobility rescue, and are characterized in that an image acquisition and processing device is used for acquiring an image of the roadbed of the high-mobility rescue equipment, analyzing the road section type of the image of the roadbed and determining a plurality of road section type information corresponding to the roadbed of the high-mobility rescue equipment; the method comprises the steps that a sensor is arranged on each road section to collect information of a plurality of road section categories, and road section information corresponding to the road section categories is obtained; associating each road section category information with the corresponding road section information according to the corresponding relationship between the plurality of road section category information and the road section information corresponding to the plurality of road section categories; the road section information is compared with the road section test setting parameters, and when the road section information does not meet the preset conditions, the early warning information is generated, so that the current situation of the roadbed is found, the supervision and management level of the roadbed is improved, and the technical effects of early diagnosis and prevention of safety accidents are achieved.
Description
Technical Field
The invention relates to the technical field related to high maneuvering rescue, in particular to a roadbed monitoring method and system for high maneuvering rescue equipment.
Background
The urgent need of corresponding emergency rescue equipment is highlighted by the urgency of emergency rescue tasks in disaster sites such as earthquakes, fire disasters, safety production and the like. The emergency rescue equipment can greatly improve the fighting capacity of rescue teams, rapidly and efficiently treat various disasters, particularly sudden serious disasters, greatly reduce casualties of rescue workers and property loss of China, and is a bottleneck limiting the rescue efficiency of major disasters in China at present, so that the research and development of high-mobility emergency rescue system equipment are urgent.
In order to meet the requirements of new product shaping tests, mandatory inspection tests and the like of high-mobility rescue equipment, various test roads are required to be built in a high-mobility rescue equipment test field, wherein the test roads comprise an annular runway running at high speed, an uneven bad road capable of causing strong jolt of an automobile, a wading and steep up-and-down ramp 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 that a test is smoothly carried out, 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 has the defects of large monitoring error, time and labor waste, incapability of monitoring the roadbed in real time, failure of the roadbed and no monitoring means, how to accurately and comprehensively monitor the state of the roadbed, and realization of real-time monitoring of the state of the roadbed becomes the technical problem which needs to be solved urgently at present.
Disclosure of Invention
The application provides a roadbed monitoring method and a roadbed monitoring system for high maneuvering rescue equipment, which are used for accurately and comprehensively monitoring the state of the roadbed of the high maneuvering rescue equipment aiming at solving the technical problem of realizing the real-time monitoring of the state of the roadbed, achieving the purpose of touching the current state of the roadbed, improving the supervision and management level of the roadbed and realizing the technical effects of advanced diagnosis and prevention of safety accidents.
In view of the above problems, the present application provides a roadbed monitoring method and system for high maneuvering rescue equipment.
In a first aspect, the embodiment of the application provides a roadbed monitoring method for high-mobility rescue equipment, which is applied to a roadbed monitoring system for high-mobility rescue equipment, wherein the system comprises an image acquisition and processing device and a monitoring module, wherein the monitoring module comprises a plurality of sensors, and the method comprises the following steps: acquiring a roadbed image of the high-mobility rescue equipment by using an image acquisition and processing device, analyzing the road section type of the roadbed image of the high-mobility rescue equipment, and determining a plurality of road section type information corresponding to the roadbed of the high-mobility rescue equipment; acquiring information of a plurality of road section categories by arranging a sensor on each road section to obtain road section information corresponding to the road section categories; 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 sending an early warning signal according to the early warning information.
In a second aspect, the present application provides a roadbed monitoring system for high-mobility rescue equipment, the system including: the image acquisition and processing device is used for acquiring a roadbed image of the high-mobility rescue equipment, analyzing the road section type of 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; the monitoring module comprises a plurality of sensors, and the sensors are arranged on each road section to acquire information of the road sections, so that road section information corresponding to the road sections of the road sections is acquired; 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 relationship 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 solutions provided in the present application have at least the following technical effects or advantages:
according to the building method and system of the typical control method modularization simulation model, the image acquisition and processing device is used for acquiring the roadbed image of the high mobility rescue equipment, the roadbed image of the high mobility rescue equipment is subjected to road section type analysis, and a plurality of road section type information corresponding to the roadbed of the high mobility rescue equipment is determined; setting a sensor at each road section to acquire information of a plurality of road section categories to obtain road section information corresponding to the road section categories; associating each road section category information with the corresponding road section information according to the corresponding relationship 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 sending an early warning signal according to the early warning information. The method solves the technical problem of accurately and comprehensively monitoring the roadbed state of the high-mobility rescue equipment and realizing real-time monitoring of the roadbed state, and achieves the technical effects of touching the current state of the roadbed, improving the supervision and management level of the roadbed and preventing safety accidents in advance.
Drawings
Fig. 1 is a schematic flow chart of a roadbed monitoring method for high-mobility rescue equipment provided by the application;
fig. 2 is a schematic flow chart for obtaining information of multiple road section categories in a roadbed monitoring method of high maneuvering rescue equipment provided by the application;
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 for the high mobility rescue equipment provided by the application;
fig. 4 is a schematic flow chart illustrating a matching degree analysis of road section correlation information and parameter information to be tested on road surface information in a roadbed monitoring method for high maneuvering rescue equipment according to the application;
fig. 5 is a schematic structural diagram of a roadbed monitoring system for high-mobility rescue equipment;
description of reference numerals: the system comprises an image acquisition and processing device 11, a monitoring module 12, a data processing module 13 and an early warning module 14.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method and the system for monitoring the roadbed of the high-mobility rescue equipment are used for accurately and comprehensively monitoring the state of the roadbed of the high-mobility rescue equipment, so that the technical problem of monitoring the state of the roadbed in real time is solved, the current state of the roadbed is thoroughly known, the supervision and management level of the roadbed is improved, and the technical effects of advanced diagnosis and prevention of safety accidents are achieved.
Example one
As shown in fig. 1, the present application provides a roadbed monitoring method for high-mobility rescue equipment, which is applied to a roadbed monitoring system for high-mobility rescue equipment, the system includes an image acquisition and processing device and a monitoring module, wherein the monitoring module includes a plurality of sensors, and the method includes:
s100: acquiring a roadbed image of the high-mobility rescue equipment by using an image acquisition and processing device, analyzing the road section type of the roadbed image of the high-mobility rescue equipment, and determining a plurality of road section type information corresponding to the roadbed of the high-mobility rescue equipment;
specifically, in order to ensure smooth running of different test tests, the roadbed needs to have good integrity and sedimentation uniformity in the whole service process, provide stable pavement test conditions for high-mobility rescue equipment, and reproduce various road conditions and use conditions encountered by the high-mobility rescue equipment in the running process.
The image acquisition and processing device is used for acquiring the roadbed image of the high-mobility rescue equipment, the image is converted into a digital image after quantization and is input and stored into the frame memory, the image processing module in the image acquisition and processing device is used for analyzing and processing the roadbed image of the high-mobility rescue equipment, and a plurality of road section category information corresponding to the roadbed 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 and steep slopes. In the embodiment of the application, the road section type information is obtained by analyzing the road bed image, the road bed is monitored based on the road section type information, the data is classified and processed in a partition mode, and the data processing capacity and speed are improved.
As shown in fig. 2, step S100 in the method provided in the embodiment of the present application includes:
s110: carrying out feature extraction on the roadbed image of the high maneuvering rescue equipment;
s120: carrying out feature identification on the roadbed image of the high maneuvering rescue equipment according to the feature extraction result, and determining feature change position nodes according to the feature identification;
s130: and carrying out image segmentation on the acquired roadbed image based on the characteristic change position node to obtain a plurality of road section category information.
Specifically, in order to partition the roadbed, the obtained roadbed image is analyzed. In order to prevent a noisy image from possibly existing in an acquired roadbed image and further influence a subsequent data processing result, preferably, before feature extraction is carried out on the acquired roadbed image, denoising pretreatment is carried out on the acquired roadbed image, irrelevant information in the image is eliminated, and useful real information is recovered, so that the image is clearer and softer in smoothing effect, and more effective and accurate data support is provided for data processing on a target product production image set subsequently; furthermore, in order to facilitate image processing, display color space conversion is performed on the road bed image subjected to denoising, the image is converted from an RGB space to a gray scale space, threshold calculation is performed on each pixel in the gray scale image point by using image binarization, and detail information of the image is stored.
The method comprises the steps of extracting the features of the processed roadbed image of the high-mobility rescue equipment, dividing the image into a plurality of mutually disjoint areas according to the features such as gray scale, color, spatial texture and geometric shape, identifying the features of the roadbed image of the high-mobility rescue equipment according to the feature extraction result, determining feature change position nodes according to the feature identification, and segmenting the image of the roadbed image acquired by the acquisition based on the feature change position nodes, wherein the image segmentation method comprises the following steps: the image segmentation is realized based on an edge detection method, an area generation method and the like, and then a plurality of road section category information is obtained, so that the roadbed image is partitioned.
S200: acquiring information of a plurality of road section categories by arranging a sensor on each road section to obtain 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 water content, a roadbed soil pressure, and a pore water pressure. In order to obtain the road section information, various sensors, for example, a displacement sensor, a temperature sensor, a soil moisture content sensor, and a soil pressure sensor, are provided on different types of road sections. And the pore water pressure sensor is used for acquiring data information of a plurality of road section types to obtain road section information corresponding to the road section types, each road section type corresponds to a plurality of road section parameters, and accurate monitoring of the roadbed is ensured by acquiring the parameters of each road section type.
S300: associating each road section category information with the corresponding road section information according to the corresponding relationship between the road section category information and the road section information corresponding to the road section categories;
specifically, in the previous step, the road section information is collected for each road section type, each road section type has the corresponding road section information, and the collected road section information is associated with the road section type corresponding to the road section information, so that the road section type information and the road section information corresponding to the road section types are in one-to-one correspondence, and the data classification processing 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 used for carrying out reliability test on the high-speed motor rescue equipment, the road bed needs to provide performance parameters, 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 be normally tested, early warning information is generated, an early warning signal is sent according to the early warning information, a worker is prompted that a certain road section cannot meet the test requirement, the current situation of the road bed is met, the supervision and management level of the road bed is improved, and the technical effects of preventing safety accidents through advanced diagnosis are achieved.
As shown in fig. 3, step S400 in the method provided in the embodiment of the present application includes:
s410: identifying information identification of the road section information corresponding to the road section types, wherein the identification information comprises road section types, road section information and 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: respectively judging whether the multi-parameter comparison result meets the set threshold of each parameter;
s440: and when the road section information does not meet the requirement, 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, identification information identification is carried out on the road section information corresponding to the road section types, wherein the identification information comprises the road section types, the road section information and the road section quality levels, and the road section quality levels are 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 results of the settlement 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 each parameter setting threshold, and if not, determining road section information according to the identification information identification of the road section information corresponding to the parameter; and then the road section information which does not meet the requirements is quickly acquired, and corresponding measures are taken to avoid the occurrence of accidents.
For example, it is assumed that the identification information is identified according to the sequence of the road section type, the road section information and the road section quality grade, wherein the road section type is identified according to the sequence of a washboard road, a stone road, a long wave road, a pebble road and a steep slope road; the road section information is marked by forbidden according to the sequence of the settlement size of the road section, the temperature of the roadbed, the soil water content, the roadbed soil pressure and the pore water pressure, the quality grade can be represented by A, B, C, for example, the identification information 34B represents the roadbed soil pressure 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 type can be quickly found according to the head position in the road section identification information, and then the roadbed soil pressure of the road section type is pre-warned and maintained.
The method for determining the road section test setting parameters in step S400 in the method provided in the embodiment of the present application includes:
s421: obtaining field test parameter information and a vehicle parameter set;
s422: performing test requirement correlation analysis based on the field 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 present application, field test parameter information of a test field is obtained, where the field test parameter information includes parameter information corresponding to each road section type, for example, parameter information such as a slope size corresponding to a steep slope section, a wading depth corresponding to a wading section, and a water flow speed; the vehicle parameter set can comprise information sets such as the model of the vehicle, the number of the vehicles, vehicle test parameters and the like; the road segment test parameter range is determined by combining the field test parameter information and the vehicle parameter information. For example, assuming a steep slope section as an example, obtaining parameter information such as a rescue vehicle with a large volume or a relatively small rescue vehicle, the driving speed of the rescue vehicle and the like, and obtaining the bearable range of the roadbed to determine as a section test parameter range, wherein the obtained gradient angle of the steep slope section is combined with the model of the vehicle; the road section test setting parameters are the minimum requirements in the road section test parameter range, namely the minimum requirements for smooth vehicle test can be met. And further the road section test setting parameters are determined.
Further, the method provided by the embodiment of the present application further includes:
s600: obtaining road surface information of a plurality of road section categories through feature extraction;
s700: monitoring the roadbed state by combining the road surface information and the multi-parameter comparison result;
s800: and analyzing the monitoring result to obtain early warning information.
Specifically, in order to improve the accuracy of the roadbed monitoring result, in this embodiment, road surface information of a plurality of road section categories is obtained by an image feature extraction method; the characteristic extraction can adopt methods such as color histogram, image characteristic extraction based on color moment and the like; the road surface information is surface characteristics of the road surface, such as pebbles, whether pebbles are ground flat or not; the slope of the steep slope road is not damaged and does not meet the road surface information such as the slope requirement and the like; and comparing the road section information corresponding to the plurality of road section categories with the road section test setting parameters one by one to obtain a multi-parameter comparison result, and monitoring the roadbed state by combining the road surface information to achieve the purpose of improving the accuracy of the roadbed state monitoring result.
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 historical roadbed images of high-mobility rescue equipment, wherein the historical roadbed images of the high-mobility rescue equipment correspond to the historical detection data acquisition time one by one;
s820: constructing a variation curve of a detection parameter based on the historical detection data of the sensor;
s830: obtaining a road section and road surface change curve based on the historical high maneuvering rescue equipment roadbed image;
s840: performing correlation analysis according to the change curve of the detection parameters and the road section and road surface change curve to obtain road section correlation information;
s850: obtaining parameter information to be tested;
s860: and analyzing the matching degree of the road information according to the road section correlation information and the to-be-tested parameter information, and acquiring early warning information when the road section correlation information and the to-be-tested parameter information are not matched.
Specifically, in order to fully utilize historical data and achieve the purpose of improving the accuracy of a roadbed state monitoring result by using the historical data as a reference, historical detection data and roadbed images of sensors at various road sections are obtained, and the time for acquiring the historical detection data of the sensors is the same as the time for acquiring the roadbed images; constructing a change curve of a detection parameter based on the historical detection data of the sensor, for example, a change curve of the soil water content of the long slope along with the change of time, for example, the soil water content parameter of the long slope is taken as an example; obtaining a road section and road surface change curve based on the historical roadbed image of the high-mobility rescue equipment, for example, a height change curve of the road section and the road surface along the direction vertical to the ground along with time change by taking a long slope as an example; performing 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; illustratively, taking a long slope road as an example, obtaining a road section and road surface variation curve obtained by obtaining a long slope road historical settlement size, a roadbed temperature, a soil water content, a roadbed soil pressure, a void water pressure variation curve and a roadbed image acquired corresponding to time, obtaining a relation between the settlement size at any time, the roadbed temperature, the soil water content, the roadbed soil pressure, the void water pressure and the road section and road surface condition, and obtaining road section correlation information, wherein the road section correlation information is a correlation between a variation curve of a detection parameter and the road section and road surface variation curve. And analyzing the matching degree of 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 that the current situation of the roadbed is found, the supervision and management level of the roadbed is improved, and the technical effects of early diagnosis and prevention of safety accidents are achieved.
Step S860 in the method provided in 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 and test parameters are obtained, and then parameter information to be tested is obtained;
s863: comparing the road section correlation information with the parameter information to be tested, and acquiring 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 to-be-tested parameter information, carrying out vehicle testing.
Specifically, a test plan of each road section is obtained, the test plan includes information of vehicles to be tested, test time arrangement, types of test road sections and the like, information of the vehicles to be tested is obtained based on the test plan, and the information of the vehicles to be tested includes: the method comprises the steps of obtaining the model number and the number of vehicles and test parameters, further obtaining parameter information to be tested, comparing the parameter information to be tested with 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 section correlation information does not meet the requirement of the parameter information to be tested, obtaining early warning information to remind a worker that the road section can not be tested, so that the safety accident is avoided from damaging operators and rescue equipment; when the road section correlation information meets the to-be-tested parameter information, vehicle testing is continued according to a testing plan; by monitoring the roadbed state in real time, stable pavement test conditions are provided for high maneuvering rescue equipment.
In summary, the roadbed monitoring method for the high-mobility rescue equipment provided by the embodiment of the application has the following technical effects:
1. according to the method for monitoring the roadbed of the high-mobility rescue equipment, the image of the roadbed of the high-mobility rescue equipment is acquired by the image acquisition and processing device, the roadbed image of the high-mobility rescue equipment is subjected to road section type analysis, a plurality of road section type information corresponding to the roadbed of the high-mobility rescue equipment is determined, and the purpose of improving the data processing speed and accuracy is achieved by partitioning the roadbed; acquiring information of a plurality of road section categories by arranging a sensor on each road section to obtain road section information corresponding to the road section categories; associating each road section category information with the corresponding road section information according to the corresponding relationship 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 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 maneuvering rescue equipment and realizing the real-time monitoring of the state of the roadbed, achieves the technical effects of touching the current state of the roadbed, improving the supervision and management level of the roadbed and diagnosing and preventing safety accidents in advance.
2. According to the embodiment of the application, the information identification is carried out on the road section information corresponding to the road section types, in the parameter comparison process, if the parameters do not meet the requirements, 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 can be quickly acquired, corresponding measures are taken, and accidents are avoided.
3. In the embodiment of the application, the detection of the roadbed state is realized from multiple aspects by collecting the historical data of the sensor and combining the historical information of the road section and the road surface, so that the historical data is fully utilized, and the purpose of improving the accuracy of the roadbed state monitoring result by using the historical data as a reference is achieved.
Example two
Based on the same inventive concept as that of the roadbed monitoring method for the high-mobility rescue equipment in the previous embodiment, as shown in fig. 5, the application provides a roadbed monitoring system for the high-mobility rescue equipment, wherein the system comprises:
the image acquisition and processing device 11 is used for acquiring a roadbed image of the high-mobility rescue equipment, analyzing the road section type of 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;
the monitoring module 12 comprises a plurality of sensors, and acquires information of a plurality of road section categories by arranging the sensors on each road section to acquire road section information corresponding to the 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 relationship 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 and 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 characteristic identification module is used for carrying out characteristic identification on the roadbed image of the high maneuvering rescue equipment according to the characteristic extraction result and determining a characteristic change position node according to the characteristic identification;
and the characteristic segmentation module is used for carrying out image segmentation on the acquired roadbed image based on the characteristic change position node to obtain a plurality of road section category information.
Further, the system further comprises:
the information identification module identifies the road sections corresponding to the road section types by identification information, wherein the identification information comprises the road section types, the road section information and the road section quality grades;
the parameter comparison module compares road section information corresponding to a plurality of 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;
the judging module is used for respectively judging whether the multi-parameter comparison result meets each parameter setting threshold value;
and the information determining module is used for determining the road section information according to the identification information identifier of the road section information corresponding to the parameter when the road section information does not meet the identification information identifier.
Further, the system further comprises:
the system comprises an information acquisition module, a data acquisition module and a data processing module, wherein the information acquisition module acquires field test parameter information and vehicle parameter sets;
the road section test parameter determining module is used for carrying out test requirement correlation analysis based on the field test parameter information and the vehicle parameter set to determine a road section test parameter range;
the road section testing and setting parameter determining module determines the road section testing and setting parameters based on the road section testing parameter range, wherein the road section testing and setting parameters are the minimum requirements in the road section testing parameter range.
Further, the system further comprises:
the road information acquisition module acquires road 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 is used for acquiring historical detection data of the sensor and corresponding historical high-mobility rescue equipment roadbed images, wherein the historical high-mobility rescue equipment roadbed images correspond to the historical detection data acquisition time one by one;
the detection parameter curve construction module is used for constructing a change curve of a detection parameter based on the historical detection data of the sensor;
the road section and road surface obtaining module is used for obtaining a road section and road surface change curve based on the historical high-mobility rescue equipment road bed image;
the road section correlation information acquisition module is used for carrying out correlation analysis according to the change curve of the detection parameters and the road section pavement change curve to acquire road section correlation information;
the device comprises a to-be-tested parameter information obtaining module, a to-be-tested parameter information obtaining module and a to-be-tested parameter information obtaining module, wherein the to-be-tested parameter information obtaining module obtains to-be-tested parameter information;
and the early warning module analyzes the matching degree of the road information according to the road section correlation information and the to-be-tested parameter information, and obtains early warning information when the road section correlation information and the to-be-tested parameter information are not matched.
Further, the system further comprises:
the test plan obtaining module is used for obtaining a test plan;
a parameter information to be tested obtaining submodule, wherein the parameter information to be tested obtaining module obtains vehicle information to be tested based on the test plan, and the vehicle information to be tested comprises: the vehicle model, number and test parameters are obtained, and then parameter information to be tested is obtained;
the early warning module compares the road section correlation information with the parameter information to be tested, and when the road section correlation information does not meet the parameter information to be tested, early warning information is obtained;
and the testing module is used for testing the vehicle when the road section correlation information meets the to-be-tested parameter information.
For a specific working process of the module disclosed in the above embodiment of the present application, reference may be made to the content of the corresponding method embodiment, which is not described herein again.
Those skilled in the art can make or use the present 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 (8)
1. A roadbed monitoring method for high-mobility rescue equipment is applied to a roadbed monitoring system for the high-mobility rescue equipment, the system comprises an image acquisition and processing device and a monitoring module, wherein the monitoring module comprises a plurality of sensors, and the method comprises the following steps:
acquiring a roadbed image of the high-mobility rescue equipment by using an image acquisition and processing device, analyzing the road section type of the roadbed image of the high-mobility rescue equipment, and determining a plurality of road section type information corresponding to the roadbed of the high-mobility rescue equipment;
acquiring information of a plurality of road section categories by arranging a sensor on each road section to obtain road section information corresponding to the road section categories;
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 sending an early warning signal according to the early warning information.
2. The method of claim 1, wherein the road segment type analysis is performed on the high mobility rescue equipment roadbed image, and the determining a plurality of road segment class information corresponding to the high mobility rescue equipment roadbed comprises:
carrying out feature extraction on the roadbed image of the high maneuvering rescue equipment;
carrying out feature identification on the roadbed image of the high maneuvering rescue equipment according to the feature extraction result, and determining feature change position nodes according to the feature identification;
and carrying out image segmentation on the acquired roadbed image based on the characteristic change position node to obtain a plurality of road section category information.
3. The method of claim 2, wherein the comparing the road segment information to road segment test setup parameters comprises:
identifying information identification of the road sections corresponding to the road section types, wherein the identification information comprises the road section types, the road section information and the road section quality grades;
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;
respectively judging whether the multi-parameter comparison result meets each parameter setting threshold value;
and when the road section information does not meet the requirement, determining the road section information according to the identification information identification of the road section information corresponding to the parameter.
4. The method of claim 3, wherein the method further comprises:
obtaining field test parameter information and a vehicle parameter set;
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;
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.
5. The method of claim 3, wherein the method further comprises:
obtaining road surface information of a plurality of road section categories through feature extraction, and comparing the road surface information with standard road surface information to obtain a road surface comparison result;
and judging the roadbed state by combining the road surface comparison result and the multi-parameter comparison result to obtain a judgment result.
6. The method of claim 5, wherein the method comprises:
obtaining historical detection data of a sensor and corresponding historical roadbed images of high-mobility rescue equipment, wherein the historical roadbed images of the high-mobility rescue equipment correspond to the historical detection data acquisition time one by one;
constructing a variation curve of a detection parameter based on the historical detection data of the sensor;
obtaining a road section and road surface change curve based on the historical high maneuvering rescue equipment roadbed image;
carrying out correlation analysis according to the change curve of the detection parameters and the road section and road surface change curve to obtain road section correlation information;
obtaining parameter information to be tested;
and analyzing the matching degree of the road information according to the road section correlation information and the to-be-tested parameter information, and acquiring early warning information when the road section correlation information and the to-be-tested parameter information are not matched.
7. The method of claim 6, wherein the matching degree analysis of the road surface information according to the road section correlation information and the parameter information to be tested comprises:
obtaining a test plan;
obtaining vehicle information to be tested based on a test plan, wherein the vehicle information to be tested comprises: the vehicle model, the number and the test parameters, and further to obtain the information of the parameters to be tested;
comparing the road section correlation information with the 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;
and when the road section correlation information meets the to-be-tested parameter information, carrying out vehicle testing.
8. A roadbed monitoring system for high maneuvering rescue equipment, characterized in that the system comprises:
the image acquisition and processing device is used for acquiring a roadbed image of the high-mobility rescue equipment, analyzing the road section type of 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;
the monitoring module comprises a plurality of sensors, and the sensors are arranged on each road section to acquire information of the road sections, so that road section information corresponding to the road sections of the road sections is acquired;
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 relationship 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.
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Citations (7)
| 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 |
| US20210010809A1 (en) * | 2019-07-11 | 2021-01-14 | Zhejiang University | Method for monitoring ground settlement based on computer vision |
| 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 |
-
2022
- 2022-06-06 CN CN202210630402.4A patent/CN115096253B/en active Active
Patent Citations (7)
| 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 |
| US20210010809A1 (en) * | 2019-07-11 | 2021-01-14 | Zhejiang University | Method for monitoring ground settlement based on computer vision |
| 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》", pages: 163 - 173 * |
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