Intelligent delineator and information acquisition control system and method and storage medium thereof

Abstract

The application relates to an intelligent profile marker and an information acquisition control system and method thereof and a storage medium thereof, which comprises an acquisition module for acquiring data of an environment where the profile marker is located, obtaining environment data and outputting; an angle module for detecting an inclination angle of the profile marker, obtaining an inclination angle signal and outputting; a photovoltaic module for photovoltaic power generation and electric energy storage, and supplying power to the acquisition module and the angle module; a distance module for acquiring a distance between profile markers, obtaining distance detection data and outputting; and a processing module for receiving the environment data, the distance detection data and the inclination angle signal, performing data calculation and processing, obtaining an alarm signal and outputting. The application has the effect of automatically judging whether the profile marker is in a normal working state.

Description

Technical Field

[0001] This application relates to the field of delineators, and in particular to an intelligent delineator, an information acquisition and control system, a method, and a storage medium thereof. Background Technology

[0002] On highways or other long-distance roads, delineators are often used instead of streetlights. They use reflections to help drivers see the location of the road edge, while also saving costs.

[0003] However, if the guardrail along the roadside is damaged by an impact and twisted or falls down, the delineator will not be able to reflect the car's lights properly. If it is not repaired in time, it will make it difficult for drivers to accurately and clearly judge the position of the roadside at night. Summary of the Invention

[0004] To address the problem that failure to maintain road delineators in a timely manner can make it difficult for drivers to accurately and clearly determine the location of road edges at night, this application provides an intelligent road delineator and information acquisition control system, method, and storage medium.

[0005] This application provides an intelligent delineator and information acquisition and control system, which adopts the following technical solution: An intelligent delineator and information acquisition and control system, comprising: The data acquisition module is used to collect data on the environment in which the contour marker is located, acquire environmental data, and output it. Angle module is used to detect the tilt angle of the delineator, acquire the tilt angle signal and output it; A photovoltaic module is used for photovoltaic power generation and energy storage, and supplies power to the acquisition module and the angle module; The distance module is used to collect the distance between delineators, acquire distance detection data, and output it. The processing module receives the environmental data, the distance detection data, and the tilt angle signal, performs data calculation and processing, obtains an alarm signal, and outputs it.

[0006] By adopting the above technical solution, automatic charging is achieved, and the status of the delineator is automatically determined. When the delineator is in an abnormal state and cannot function properly, the staff is promptly reminded to carry out maintenance.

[0007] This application provides an intelligent delineator and information acquisition and control method, which adopts the following technical solution: A smart delineator and information acquisition and control method, comprising: Obtain the tilt angle signal; The tilt angle data is determined by comparing the tilt angle signal with a preset tilt angle threshold. The alarm signal is determined and output by comparing the tilt angle data with a preset alarm threshold. The associated signal is determined by the alarm signal, the tilt angle data and the preset associated threshold, and the associated signal is included in the alarm signal and output simultaneously.

[0008] By adopting the above technical solution, the tilt status of the delineator can be automatically determined, and staff can be promptly reminded to carry out maintenance.

[0009] Optional, including: Acquire the distance detection data; Distance data is determined by comparing the distance detection data with a preset distance threshold; The breakage signal is determined and output by comparing the distance data with a preset interval threshold.

[0010] By adopting the above technical solution, the system can automatically determine whether the guardrail where the delineator is located is broken, and promptly remind staff to carry out repairs.

[0011] Optional, including: Acquire humidity detection signals and timing data; Humidity detection data is determined by comparing the humidity detection signal with a preset humidity detection threshold. Humidity change data is determined by combining the humidity detection data and the timing data. Environmental interference data is determined by comparing the humidity change data with a preset environmental judgment threshold. The distance data is determined using the environmental interference data and the distance detection data.

[0012] By adopting the above technical solution, the detected distance is automatically corrected according to the ambient humidity, thereby improving accuracy.

[0013] Optional, including: The detection change data is determined by combining the distance detection data and the timing data; The occlusion data is determined by comparing the detected change data with a preset occlusion threshold. By backtracking the distance detection data involved in the calculation using the occlusion data and the timing data, the distance detection data preceding the occlusion data is replaced with the current distance detection data.

[0014] By adopting the above technical solution, the system can automatically determine whether there is any obstruction that causes abnormal distance detection, eliminate the abnormality of obstruction, and make distance detection more accurate.

[0015] Optional, including: The drying environment data is determined by comparing the environmental interference data with a preset drying environment threshold. The dust collection data is determined by the drying environment data, the detected change data, and the preset dust collection threshold. The distance detection data is corrected by using the dust accumulation data to obtain corrected detection data, which is then used to replace the original distance detection data.

[0016] By adopting the above technical solution, the system automatically adapts to dry and sandy environments, making the detection more accurate.

[0017] Optional, including: The humid environment data is determined by comparing the environmental interference data with a preset humid environment threshold. Fogging data is determined by the humid environment data, the detected change data, and the preset fogging threshold. The distance detection data is corrected by using the fogging data to obtain the corrected detection data, which is then used to replace the original distance detection data.

[0018] By adopting the above technical solution, the system automatically adapts to humid and foggy environments, making the detection more accurate.

[0019] Optional, including: Rainfall data is determined by combining the humid environment data, the detected change data, and a preset rainfall threshold. The critical data for drying is determined by the environmental interference data, the humid environment threshold, the dry environment threshold, and the timing data. The post-wash data is determined by the drying critical data, the environmental interference data, the drying environment threshold, and the preset dust threshold. The maximum distance data is determined by the rainfall data, the timing data, and a preset rainfall time threshold. The estimated rainfall intensity is determined using the highest distance data and the post-wash data. The environmental disturbance data is corrected using the estimated rainfall data to be used in the calculation of the distance data.

[0020] By adopting the above technical solution, the system automatically adapts to rainy environments, making the detection more accurate.

[0021] This application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a smart delineator and information acquisition control method.

[0022] By adopting the above technical solution, computer programs are stored using computer-readable storage media.

[0023] In summary, this application includes at least one of the following beneficial technical effects: The system automatically determines the status of the delineator and promptly alerts staff to perform repairs when the delineator is in an abnormal state and cannot function properly.

[0024] It automatically adapts to dry, sandy, foggy, and rainy environments, making the detection more accurate. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of a module of an intelligent delineator and information acquisition and control system according to an embodiment of this application.

[0026] Figure 2 This is a flowchart illustrating an intelligent delineator and information acquisition control method in an embodiment of this application.

[0027] Figure 3 This is a flowchart of steps S2-S22.

[0028] Figure 4 This is a flowchart of steps S3-S34.

[0029] Figure 5 This is a flowchart illustrating steps S4-S42.

[0030] Figure 6 This is a flowchart of steps S5-S52.

[0031] Figure 7 This is a flowchart illustrating steps S6-S62.

[0032] Figure 8 This is a flowchart of steps S7-S75.

[0033] Explanation of reference numerals in the attached diagram: 1. Acquisition module; 2. Angle module; 3. Photovoltaic module; 4. Distance module; 5. Processing module. Detailed Implementation

[0034] The following is in conjunction with the appendix Figure 1-8 This application will be described in further detail.

[0035] This application discloses an intelligent delineator and information acquisition and control system. (Refer to...) Figure 1The intelligent delineator and information acquisition control system includes a data acquisition module 1, an angle module 2, a photovoltaic module 3, a distance module 4, and a processing module 5. Data acquisition module 1 collects environmental data, such as humidity, and outputs this data. Angle module 2 detects the delineator's tilt angle, using, for example, a tilt sensor, to obtain and output the tilt signal. Distance module 4 uses a sensor with distance detection capabilities, such as a module employing RSSI, TOF, or other distance measurement technologies, to detect the distance between adjacent delineators, obtain distance detection data, and output it. Photovoltaic module 3 includes at least a photovoltaic power generation unit and an energy storage unit, such as a combination of photovoltaic panels and batteries. Photovoltaic module 3 supplies power to data acquisition module 1, angle module 2, distance module 4, and processing module 5. Processing module 5 includes a processor and a database. The database stores various threshold data, such as tilt thresholds. The processor receives environmental data, distance detection data, and tilt signals, retrieves the corresponding threshold data from the database, performs data calculations, obtains alarm signals, and outputs them to the user, enabling timely reminders for maintenance when the delineator is tilted or malfunctions.

[0036] A processor can include a central processing unit such as a CPU or MPU, or a host system built around a CPU or MPU, encompassing both hardware and software. With a processor, a measuring instrument can be freely controlled by programming, allowing it to operate according to user intentions. The processor can control local measurement transmission, remote measurement transmission, and remote communication through internal protocols. Internal protocols broadly refer to all protocols that enable communication or linking within the same measuring instrument or system, including: human-machine interface protocols, software / hardware (interface) protocols, chip bus (C-Bus) protocols, internal bus (I-Bus) protocols, and some or all of these protocols. With the development of integrated circuit technology, some protocols that belong to external bus (E-Bus) have also been integrated into the chip and thus become internal protocols.

[0037] This application discloses an intelligent delineator and an information acquisition and control method. (Refer to...) Figure 2 The intelligent delineator and information acquisition control method includes the following steps: S1. Obtain the tilt angle signal; S11. Determine the tilt angle data by comparing the tilt angle signal with the preset tilt angle threshold; S12. Determine and output the alarm signal by comparing the tilt angle data with the preset alarm threshold; S13. Determine the associated signal by using the alarm signal, tilt angle data and preset associated threshold, include the associated signal in the alarm signal and output it simultaneously.

[0038] In detail: The tilt angle signal is data detected by the tilt sensor, used to detect the tilt angle of the delineator. Specifically, the data detected by the tilt sensor is calculated against a tilt angle threshold, converting the detected data into the required angle data. This tilt angle data is then compared with an alarm threshold. If the tilt angle data exceeds the alarm threshold, it indicates that the tilt angle is too large. For example, if the delineator tilts too much, it may not be illuminated by car headlights at night, thus failing to reflect light to indicate the location of the road edge to drivers. In this case, an alarm signal is output to the user to remind them to repair it. When one delineator tilts, it often causes other nearby delineators to tilt along with the adjacent guardrails. The associated tilt angle can be calculated using an associated threshold. For example, if the middle delineator tilts at 60°, let the associated threshold be... 'a' is a coefficient, 'x' is the tilt angle, and the exponential function indicates that when the tilting first occurs, the impact on adjacent contour markers is very small. Only when the tilt angle of the middle contour marker becomes large will it have a certain impact on adjacent contour markers. The calculated cascading impact is the cascading signal. The cascading signal is output together with the alarm signal to make the impact of the tilting more visible to the user, so that they can independently determine whether multiple adjacent contour markers also need to be repaired, and carry sufficient tools or repair materials.

[0039] Reference Figure 3 It also includes the following steps: S2. Acquire distance detection data; S21. Determine the distance data by comparing the distance detection data with the preset distance threshold; S22. Determine the breakage signal by comparing the distance data with the preset interval distance threshold and output it.

[0040] In detail: The distance detection data is the data detected by the distance module 4. In this embodiment, it is the signal strength between adjacent distance modules 4. The distance is determined by the magnitude of the signal strength. The distance detection data is the signal strength directly detected by the distance module 4. By comparing it with the distance threshold, the distance represented by the signal strength can be obtained, i.e., the distance data. The interval distance threshold is the distance that should be between adjacent contour markers, i.e., the standard distance range data. When the distance data exceeds the range of the interval distance threshold, it means that the distance between adjacent contour markers has exceeded the normal range. At this time, the guardrail has broken, and a breakage signal is output to the user.

[0041] Reference Figure 4 It also includes the following steps: S3. Acquire humidity detection signals and timing data; S31. Determine humidity detection data by comparing the humidity detection signal with the preset humidity detection threshold; S32. Determine humidity change data by combining humidity detection data and timing data; S33. Determine environmental interference data by comparing humidity change data with preset environmental judgment thresholds; S34. Determine the distance data using environmental interference data and distance detection data.

[0042] In detail: Environmental data includes humidity detection signals, which are data representing ambient humidity collected by acquisition module 1. However, the humidity detection signals are data directly collected by acquisition module 1. The humidity detection threshold is a conversion parameter, meaning that the directly detected humidity detection signals are converted and calculated using the humidity detection threshold to obtain the humidity data. Combining the humidity detection data with time yields the rate of change of humidity, which is the humidity change data. For example, if the humidity is 30% in the first second and 31% in the second second, the rate of change of humidity is 1% / s. The environmental judgment threshold is a parameter for judging the impact of the environment on the signal strength of distance module 4. For example, in a humid environment, humid air will have a certain impact on the signal strength. The impact of the environment on the signal strength is calculated, which is the environmental interference data. By correcting the detected distance detection data for the environmental interference data, a distance data closer to the actual distance can be obtained. For example, if the distance detection data is 1m, but the environmental interference data indicates 10% interference, then the actual distance may be 1.1m. Therefore, a distance data closer to the actual distance of 1.1m is obtained for calculation.

[0043] Reference Figure 5 It also includes the following steps: S4. Determine the detection change data through distance detection data and timing data; S41. Determine the occlusion data by detecting the change data and the preset occlusion threshold; S42. By backtracking the distance detection data involved in the calculation using occlusion data and timing data, the distance detection data before the occlusion data is replaced with the current distance detection data.

[0044] In detail: By combining the distance detection data with time, the distance change data can be obtained. This represents the distance change between adjacent contour markers. Usually, the change occurs when the guardrail shakes or tilts, or when the transmitting and receiving units of the distance module 4 are affected. This step is used to correct misjudgments when the distance module 4 is affected. When the detected change data exceeds the occlusion threshold, it means that there is a large obstruction between the distance modules 4 of adjacent contour markers, which affects the signal strength of the distance module 4 in transmitting and receiving distance detection data. For example, a large box falls from a car and blocks the distance between adjacent contour markers. At this time, the output indicates that there is an obstruction. The distance detection data is then traced back to the time point when the obstruction data indicates that there is no obstruction. That is, the distance detection data before the timing data corresponding to the obstruction data is traced back to replace the current distance detection data in the calculation. For example, the distance detection data two seconds ago is used as the current distance detection data to participate in the calculation until the obstruction data indicates that there is no obstruction. For example, the detected change data changes again until the previous sudden change in the detected change data is canceled out. Reference Figure 6 It also includes the following steps: S5. Determine the drying environment data by comparing the environmental interference data with the preset drying environment threshold. S51. Determine the dust collection data by combining the drying environment data, the detected change data, and the preset dust collection threshold. S52. Correct the distance detection data using the dust collection data to obtain corrected detection data to replace the distance detection data.

[0045] In detail: The dry environment threshold is the impact on signal strength when in a dry environment. Generally, the impact on signal strength is small in a dry environment. When the environmental interference data is compared with the dry environment threshold, it is determined that the current environment is a dry environment, and the dry environment data is output. Under the dry environment data, the detected change data reflects the dust falling on the distance module 4, which affects the transmission and reception of the distance module 4. This step is usually used in dry and windy environments, such as deserts. The dust falling threshold is pre-input by the user. The dust falling threshold is the rate of dust falling in this area. That is, when the detected change data is within the range of the dust falling threshold, it is considered dust falling. The part exceeding the dust falling threshold is considered a change in the guardrail. At this time, the interference of the dust falling rate on the signal is the dust falling data. The distance detection data is corrected by the dust falling data.

[0046] Reference Figure 7 It also includes the following steps: S6. Determine the humid environment data by comparing the environmental interference data with the preset humid environment threshold; S61. Determine fogging data by combining humid environment data, detection change data, and preset fogging threshold; S62. Correct the distance detection data using fogging data to obtain corrected detection data to replace the distance detection data.

[0047] In detail: The humid environment threshold measures the impact of a humid environment on signal strength. Typically, the impact on signal strength is significant in humid environments. The humid environment data is calculated by comparing environmental interference data with the humid environment threshold. If the current environment is determined to be humid, then humid environment data is output. Under humid environment data, the detected changes reflect the impact of water mist adhering to distance module 4, affecting its signal transmission and reception, as well as the impact of water mist between adjacent distance modules 4 on signal strength. This step is typically applicable in humid environments, such as foggy days. The humidity threshold is pre-input by the user. The fogging threshold affects signal strength, and its range is wider than that of the dryness threshold. While both 70% and 40% humidity environments are considered humid, 70% humidity has a greater impact on signal strength. Therefore, the fogging threshold will adapt to environmental interference data and adjust itself accordingly. The adaptive fogging threshold has a certain range; when the detected change data is within the fogging threshold range, it is considered normal. Any change exceeding the fogging threshold is considered a change in the guardrail. The interference of fog on the signal is then called fogging data, which is used to correct the distance detection data.

[0048] Reference Figure 8 It also includes the following steps: S7. Determine rainfall data by combining humid environment data, detected change data, and preset rainfall thresholds; S71. Determine the critical data for drying by using environmental interference data, humid environment threshold, dry environment threshold and timing data; S72. Determine the post-wash data by using the drying critical data, environmental interference data, drying environment threshold and preset dust threshold; S73. Determine the maximum distance data by using rainfall data, timing data, and a preset rainfall time threshold; S74. Determine the estimated rainfall data using the highest distance data and post-wash data; S75. Correct environmental disturbance data using estimated rainfall data to participate in distance data calculation.

[0049] In detail: When the environment is excessively humid, exceeding the humidity threshold but falling within the rain threshold, it indicates rain rather than fog. Alternatively, if the humidity data fluctuates and the maximum humidity reaches the rain threshold, it also indicates rain, such as a sudden shower, rather than a rise in humidity followed by rain. In rainy conditions, the surface dust on distance module 4 will be washed away first. However, dust that has adhered for a long time is difficult to remove. Therefore, the humidity is first used to determine the point in time when the environment is still dry, i.e., the dryness threshold data. Then, a period of time is calculated backwards. Dust that adheres over time is called surface dust, which is easily washed away by rain. The data after removing surface dust is called post-wash data. Post-wash data is the data of distance module 4 affected by the interference of difficult-to-wash dust and rainy environment, and the interference of surface dust has been removed. Unlike foggy environment, rainy environment is not as uniform as fog. Rain will cause signal strength to fluctuate, which is not as stable as foggy environment. The data with the highest signal strength in the fluctuation is used as the highest distance data, that is, the time when the impact of rain is the least. Combined with post-wash data, the estimated rainfall data is obtained, and this data is used in the calculation.

[0050] This application discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program that can be loaded by a processor and executed, along with a smart delineator and information acquisition control method.

[0051] Computer-readable storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, and other media capable of storing program code.

[0052] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for information acquisition and control of intelligent delineators, relating to intelligent delineators and information acquisition and control systems, characterized in that, The system includes the following modules: The data acquisition module (1) is used to collect data on the environment in which the contour marker is located, acquire environmental data and output it. Angle module (2) is used to detect the tilt angle of the contour marker, obtain the tilt angle signal and output it; The photovoltaic module (3) is used for photovoltaic power generation and energy storage, and provides power to the acquisition module (1) and the angle module (2); The distance module (4) is used to collect the distance between contour markers, obtain distance detection data and output it; The processing module (5) receives the environmental data, the distance detection data and the tilt angle signal, performs data calculation and processing, obtains an alarm signal and outputs it; The method includes the following steps: S1. Obtain the tilt angle signal; S11. Determine the tilt angle data by using the tilt angle signal and the preset tilt angle threshold; S12. Determine the alarm signal based on the tilt angle data and the preset alarm threshold, and output it. S13. Determine the associated signal through the alarm signal, the tilt angle data and the preset associated threshold, include the associated signal in the alarm signal and output it simultaneously; S2. Obtain the distance detection data; S21. Determine distance data by comparing the distance detection data with a preset distance threshold; S22. Determine and output the breakage signal by comparing the distance data with a preset interval distance threshold; S3. Acquire humidity detection signals and timing data; S31. Determine humidity detection data by comparing the humidity detection signal with a preset humidity detection threshold; S32. Determine humidity change data using the humidity detection data and the timing data; S33. Determine environmental interference data by comparing the humidity change data with a preset environmental judgment threshold. S34. Determine the distance data using the environmental interference data and the distance detection data; S4. Determine the detection change data using the distance detection data and the timing data; S41. Determine occlusion data by comparing the detected change data with a preset occlusion threshold. S42. By using the occlusion data and the timing data, backtrack the distance detection data involved in the calculation, and replace the current distance detection data with the distance detection data before the occlusion data; S5. Determine the drying environment data by comparing the environmental interference data with the preset drying environment threshold. S51. Determine the dust collection data by combining the drying environment data, the detected change data, and the preset dust collection threshold. S52. Correct the distance detection data using the dust accumulation data to obtain corrected detection data to replace the distance detection data; S6. Determine the humid environment data by comparing the environmental interference data with the preset humid environment threshold; S61. Determine fogging data by combining the humid environment data, the detected change data, and a preset fogging threshold. S62. Correct the distance detection data using the fogging data to obtain the corrected detection data to replace the distance detection data; S7. Determine rainfall data by combining the humid environment data, the detected change data, and a preset rainfall threshold; S71. Determine the critical data for drying by using the environmental interference data, the humid environment threshold, the dry environment threshold, and the timing data; S72. Determine the post-wash data using the drying critical data, the environmental interference data, the drying environment threshold, and the preset dust threshold. S73. Determine the maximum distance data using the rainfall data, the timing data, and a preset rainfall time threshold; S74. Determine the estimated rainfall data using the highest distance data and the post-washing data; S75. The environmental disturbance data is corrected using the estimated rainfall data so that it can be used in the calculation of the distance data.

2. A computer-readable storage medium, characterized in that, The computer program stores a method for acquiring and controlling the information of a smart delineator as described in claim 1, which can be loaded by a processor.

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