Unmanned underway monitoring method

Abstract

The invention relates to an environment monitoring technology, and particularly provides an unmanned underway monitoring method, which comprises the following steps that: A1, an unmanned vehicle underways to an ith place; a2, acquiring monitoring parameters of a plurality of orientations adjacent to the unmanned vehicle; a3, the parameters are ranked; a4, judging whether an obstacle exists in the jth direction or not, wherein j is equal to 1; if not, entering the next step; if the result is yes, enabling j to be equal to j + 1, and performing judgment again; and A5, when the unmanned vehicle sails to the (i + 1) th place in the j-th direction, returning to the step A2. The system has the advantages of autonomous cruise, no need of manual guarding and the like.

Description

Technical Field

[0001] This invention relates to environmental monitoring technology, and particularly to a method for unmanned mobile monitoring. Background Technology

[0002] Currently, mobile monitoring vehicles are commonly used to obtain environmental data, measuring concentrations at a fixed height, and they typically have only one sampling channel. These mobile monitoring vehicles have several drawbacks, such as: 1. Mobile monitoring vehicles require human staff to be on duty. Staff need to plan routes in advance and monitor data changes during the mobile monitoring process. Adjusting the mobile monitoring route manually can lead to a huge workload.

[0003] 2. Unmanned mobile vehicles rely on pre-set routes to carry out their work and cannot achieve adaptive cruise or autonomously find high-value locations.

[0004] 3. VOCs diffusion is affected by environmental conditions, and concentrations vary at different altitudes. VOCs deposition cannot be monitored, and their impact on human respiration cannot be assessed.

[0005] VOCs concentrations vary at the same altitude but in different locations. Existing technologies lack this information and cannot guide the route of the mobile vehicle. Summary of the Invention

[0006] To address the shortcomings of the existing technical solutions, this invention provides an unmanned mobile monitoring method.

[0007] The objective of this invention is achieved through the following technical solution: An unmanned mobile monitoring method includes the following steps: A1. The driverless vehicle travels to the i-th location; A2. Obtain monitoring parameters from multiple locations adjacent to the driverless vehicle; A3. Sort the parameters; A4. Determine if there is an obstacle in the j-th position, where j=1; If the result is negative, proceed to the next step; If the result is yes, set j = j + 1 and re-evaluate; A5. The unmanned vehicle travels to the (i+1)th location in the j-th direction and returns to step A2.

[0008] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. More detailed spatial distribution information of pollutants can guide unmanned mobile monitoring vehicles to achieve autonomous navigation and find high points autonomously, without the need for human supervision, thus reducing the amount of manual work; 2. The unmanned vehicle moves from point to area, guided by concentration monitoring (autonomous path planning), and can cover most areas within the electronic fence, providing real-time alarms for abnormal locations; 3. The unmanned mobile monitoring vehicle can perform multi-point sampling in space, and the switching unit can achieve selective sampling from multiple directions. A single instrument can quickly detect pollutant concentration information at multiple spatial points. 4. Cruise control can avoid dead-end roads, roads with obstacles, and sections of road where passage is prohibited; 5. Multi-channel sampling analysis of VOCs concentrations at different heights, combined with mass spectrometry data to determine whether VOCs pose a risk of sedimentation and assess the health risks to humans. Attached Figure Description

[0009] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are merely illustrative of the technical solutions of this invention and are not intended to limit the scope of protection of this invention. In the drawings: Figure 1 This is a flowchart illustrating the unmanned mobile monitoring method according to the present invention. Detailed Implementation

[0010] Figure 1 The following description illustrates optional embodiments of the invention to teach those skilled in the art how to implement and reproduce the invention. Some conventional aspects have been simplified or omitted to teach the technical solutions of the invention. Those skilled in the art should understand that variations or substitutions derived from these embodiments will be within the scope of the invention. Those skilled in the art should understand that the following features can be combined in various ways to form multiple variations of the invention. Therefore, the invention is not limited to the optional embodiments described below, but is defined only by the claims and their equivalents.

[0011] Example 1

[0012] This embodiment provides an unmanned mobile monitoring method, such as... Figure 1 As shown, it includes the following steps: A1. The unmanned vehicle travels to the i-th location, such as starting the unmanned travel from the first location.

[0013] A2. Obtain monitoring parameters from multiple directions adjacent to the unmanned vehicle, including the front, rear, left, and right sides.

[0014] A3. Sort the parameters. If some orientation parameters are equal, sort them according to the priority of front, back, left and right.

[0015] A4. Determine if there is an obstacle at the j-th position in the sorting, where j=1. The obstacle includes physical obstacles, dead ends, and prohibited areas.

[0016] If the result is negative, proceed to the next step.

[0017] If the result is yes, let j = j + 1 and re-evaluate.

[0018] A5. The unmanned vehicle travels to the (i+1)th location in the j-th direction. The distance between adjacent locations is fixed. Then, return to step A2.

[0019] In order to analyze and provide early warning of the deposition characteristics of VOCs and / or their health effects on humans, the multiple orientations further include the upper side and the lower side; By comparing the changing trends of parameters on the upper and lower sides, we can analyze and provide early warning of the deposition characteristics of VOCs and / or their impact on human health.

[0020] To further reduce the complexity and cost of the mobile monitoring vehicle, the parameters are obtained as follows: The switching unit allows sampling gases from multiple directions to selectively enter the analysis device, thereby obtaining parameters from multiple directions.

[0021] Example 2

[0022] Application example of the unmanned mobile monitoring method in Embodiment 1.

[0023] In this application example, sampling ports are installed around the unmanned vehicle (UAV) (front, rear, left, and right sides), on its bottom, and on the lifting platform. Six sampling ports are connected to a sample inlet wheel, which in turn connects to an analyzer. The sample inlet wheel switches sampling channels to introduce the sample into the analyzer for detection. The lifting platform is software-controlled and can be raised to the target height for sampling. A meteorological parameter instrument obtains wind direction and speed information. A lidar sensor can model and measure distances to surrounding buildings for obstacle avoidance by the UAV. A GIS system obtains latitude and longitude information.

[0024] like Figure 1 As shown, the monitoring method in this embodiment includes the following steps: A1. When the unmanned mobile monitoring vehicle starts its work, it first demarcates the electronic fence, and then the unmanned vehicle only patrols within the electronic fence.

[0025] The driverless car navigated to the first location.

[0026] A2. Obtain monitoring parameters from multiple directions adjacent to the unmanned vehicle, including the front, rear, left, and right sides.

[0027] Sampling channels are activated in four directions (front, rear, left, and right) around the vehicle. A preset wheel switches the sampling channel every 2 seconds, and samples from each channel are sequentially introduced into the rapid mass spectrometer for detection. The rapid mass spectrometer has a detection rate of 1 second per spectrum. Therefore, acquiring data from all four directions at a single location takes 8 seconds.

[0028] Four directions were obtained (East 396μg / m 3 416 μg / m 3 721 μg / m 3 389 μg / m 3 (Concentration values, GIS data, wind speed and direction information)

[0029] A3. Sort the parameters. If some orientation parameters are equal, sort them according to the priority of front, back, left and right.

[0030] Compare the concentration values ​​monitored from the four locations, and assign them to N1 = 721 μg / m² in descending order. 3 N2 = 416 μg / m 3 N3 = 396 μg / m 3 N4 = 389 μg / m 3 .

[0031] A4. Determine if there is an obstacle at the j-th position in the sorting, where j=1. The obstacle includes physical obstacles, dead ends, and prohibited areas.

[0032] If the result is negative, proceed to the next step. There are no obstacles in this embodiment.

[0033] If the result is yes, let j = j + 1 and re-evaluate.

[0034] A5. The unmanned vehicle travels to the second location in the first position. The distance between adjacent locations (L=10m) is fixed. Then, it returns to step A2.

[0035] Repeat the above steps. The unmanned mobile monitoring vehicle is always in a patrol monitoring state. This method allows the unmanned vehicle to move from point to area, guided by the monitoring concentration (autonomous path planning), and can cover most areas within the electronic fence, providing real-time alarms for abnormal points.

[0036] If the unmanned mobile monitoring vehicle repeatedly travels back and forth between the i-th location and the (i+1)-th location more than 3 times, there may be a strong pollution emission point near that location. It will then exit the patrol mode and remind staff to conduct further investigation.

[0037] Example 3

[0038] The application example of the unmanned mobile monitoring method in Embodiment 1 differs from Embodiment 2 in that: 1. Concentration values ​​were obtained from four directions at the first location: East 280 μg / m³ 3 416 μg / m 3 156 μg / m 3 416 μg / m 3 , as well as GIS and wind speed and direction information.

[0039] Compare the concentration values ​​monitored from the four directions and assign them in descending order. Since the values ​​for the west and north are the same, they are assigned according to the priority sequence of east, west, south, and north. N1 = West 416 μg / m 3 N2 = 416 μg / m 3 N3 = 280 μg / m 3 N4 = 156 μg / m 3 .

[0040] Take bearing N1 as the next cruise point, and mark the next cruise point as S2.

[0041] 2. If an obstacle exists between S2 and S1 based on lidar ranging information, and the distance does not meet the set 10m requirement, then N2 is selected as the next cruise point and remarked as S2. If N2 still does not meet the requirement, this process continues.

[0042] If none of the four conditions are met, the unmanned mobile monitoring vehicle is in the wrong initial position and is stuck in a dead end, triggering an alarm to alert staff for assistance.

[0043] Example 4

[0044] The application example of the unmanned mobile monitoring method in Embodiment 1 differs from Embodiment 2 in that: The unmanned mobile monitoring vehicle was started. The sampling port and meteorological parameter instrument were raised to the target height (H1=4m) via the lifting platform, and the sampling port was arranged under the vehicle (H2=0.25m).

[0045] Channels H1 and H2 are enabled, and the sampling port is connected to a multi-channel rotary disc. The disc is set to switch between the two sampling channels every 5 seconds, and samples are sequentially introduced into the rapid mass spectrometer for detection. The rapid mass spectrometer has a detection rate of 1 second per spectrum. Excluding the 1-second sample stabilization time, the rapid mass spectrometer can acquire 4 seconds of data per cycle. The concentrations of substances with high mass-to-charge ratios of 100-300 are statistically analyzed for sedimentation analysis.

[0046] Each channel records the concentration change trend over a period of time. By comparing the trends of H1 and H2, the deposition characteristics of VOCs and their impact on human health can be analyzed and warnings can be issued.

[0047] . Example

[0048] The application example of the unmanned mobile monitoring method in Embodiment 1 differs from Embodiment 2 in that: The unmanned mobile monitoring vehicle conducts large-area patrols and establishes a coordinate system, where -1km≤x≤1km, -1km≤y≤1km, and the concentration unit is mg / m³. 3 .

[0049] Six different coordinate locations and their corresponding concentrations were selected (to ensure the representativeness of the sample, several sets of coordinate locations with large concentration differences are generally selected).

[0050] The coordinates (0.1, 0.74) correspond to A1=5.908, and the coordinates (0.202, -0.149) correspond to A2=7.304.

[0051] The coordinates (0.52, 0.7) correspond to A3=0.307, and the coordinates (-0.118, -0.17) correspond to A4=9.6.

[0052] The coordinates (0.158, 0.274) correspond to A5=9.16, and the coordinates (-0.585, -0.349) correspond to A6=3.9.

[0053] Using the correspondence between the above coordinates and monitoring parameters, we obtain: A = f(x, y) = -18.2x 2 -10.7y 2 +0.5xy-3.6x+2.8y+10.02.

[0054] ∂A / ∂x=0.5y-36.4x-3.6=0, ∂A / ∂y=-21.4y+0.5x+2.8=0.

[0055] The critical points are obtained as x0 = -0.097 and y0 = 0.129.

[0056] Using A=f(x,y), we obtain A0=10.55 corresponding to the coordinates (x0,y0).

Claims

1. An unmanned mobile monitoring method, characterized in that, The unmanned mobile monitoring method includes the following steps: A1. The driverless vehicle travels to the i-th location; A2. Obtain monitoring parameters from multiple locations adjacent to the driverless vehicle; A3. Sort the parameters; A4. Determine if there is an obstacle in the j-th position, where j=1; If the result is negative, proceed to the next step; If the result is yes, set j = j + 1 and re-evaluate; A5. The unmanned vehicle travels to the (i+1)th location in the j-th direction and returns to step A2.

2. The monitoring method according to claim 1, characterized in that, The multiple directions include the front, rear, left, and right sides.

3. The monitoring method according to claim 2, characterized in that, If the parameters of some directions are equal, sort them according to the priority of front, back, left and right.

4. The monitoring method according to claim 2, characterized in that, The multiple orientations also include the upper side and the lower side; By comparing the changing trends of parameters on the upper and lower sides, we can analyze and provide early warning of the deposition characteristics of VOCs and / or their impact on human health.

5. The monitoring method according to claim 1, characterized in that, The distance between adjacent locations is fixed.

6. The monitoring method according to claim 5, characterized in that, The parameters are obtained in the following way: The switching unit allows sampling gases from multiple directions to selectively enter the analysis device, thereby obtaining parameters from multiple directions.

7. The monitoring method according to claim 1, characterized in that, The obstacles include barriers, dead ends, and no-entry zones.

8. The monitoring method according to claim 1, characterized in that, The monitoring method also includes tracing the pollution source, specifically: Obtain monitoring parameters A from multiple locations. i , i = 1, 2, ..., N; According to the parameter A i and the coordinates of its corresponding location (x i ,y i Establish a mapping relationship A=f(x,y) between monitoring parameter A and coordinates (x,y); Based on ∂A / ∂x=0 and ∂A / ∂y=0, the coordinates of the critical point (x0, y0) are obtained; Based on A=f(x,y), the monitoring parameter A0 corresponding to the coordinate (x0,y0) is obtained.

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