Random gating large-scale multichannel carbon flux monitoring system and method

Abstract

The invention relates to the technical field of forest carbon sink monitoring, and particularly discloses a random gating large-scale multichannel carbon flux monitoring system and method. Aiming at the problems of delayed accumulation of channel sampling and serious multi-gas-path residual pollution caused by sequence switching in the prior art, an innovative solution is provided. Comprising the following steps: (1) ensuring fair sampling of each channel based on a dynamic gating mechanism of a randomly generated sequence; (2) the three-axis high-speed stepping platform drives a shared terminal gas path butt joint to achieve gas path butt joint with the array control valve; and (3) a single-channel sampling time algorithm is dynamically compressed, so that a full-channel traversal period is maintained at a constant threshold value, and the time difference between channels is irrelevant to the number. A traditional fixed sequence switching model is broken through, the channel monitoring time difference is small, accurate and synchronous measurement data can be obtained, and the gas cross contamination rate is low; and channel dynamic expansion is supported, and the operation and maintenance cost is low. The technology is suitable for high-precision measurement of multi-tree forest carbon sink, and assists the implementation of the national'double carbon 'strategy.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecological environment monitoring, and in particular to a random gating large-scale multi-channel carbon flux monitoring system suitable for precise measurement of carbon sinks of multi-species forests. BACKGROUND

[0002] The current direction of forest carbon sink measurement is to develop a measurement method with high measurement accuracy and speed that can be applied to the vast multi-species forest areas in China. This relies on long-term high-resolution monitoring of each component of forest carbon flux, but related instruments rely on imports and cannot guarantee the time synchronization and resolution of measurement under large-scale sampling.

[0003] The mainstream carbon flux monitoring equipment such as LI-8100A system adopts a fixed sequence switching mode. When the number of channels increases, the sampling time difference of the first and last channels is large, resulting in poor time synchronization and easy error accumulation. In the high-density forest monitoring scene, this time difference can be more than 30 minutes, which seriously affects the comparability of the data. In addition, as the number of channels increases, the cumulative effect of residual gas in the gas path increases exponentially, greatly affecting the accuracy of the data.

[0004] Therefore, the prior art cannot achieve high synchronization monitoring under large-scale channels, which hinders the development of domestic high-precision carbon sink monitoring equipment, making it difficult to meet the long-term monitoring needs of multi-species mixed forests, and there is an urgent need for a breakthrough solution. SUMMARY

[0005] The purpose of the present application is to provide a random gating large-scale multi-channel carbon flux monitoring system and method to solve the contradiction between channel scale expansion and measurement time synchronization and data accuracy.

[0006] The technical solutions adopted by the present application are as follows: A random gating large-scale multi-channel carbon flux monitoring system, comprising: A plurality of sets of monitoring and sampling devices are arranged at predetermined sampling points for monitoring and sampling. Each set of monitoring and sampling devices comprises a monitoring device, a circulating pump and a control valve, and the monitoring device, the circulating pump and the control valve are connected in series through a pipeline to form a channel. A carbon flux measurement device is used to measure carbon flux. The carbon flux measurement device comprises a carbon flux measurement instrument and a shared terminal gas path connected thereto. The end of the shared terminal gas path is provided with a docking head, and all monitoring and sampling devices share the shared terminal gas path. A random gating device is used to drive the docking head to randomly connect to a target control valve. The random gating device comprises a three-axis high-speed stepping platform, and the control valve array is arranged on the working platform within the movement range of the sliding table of the three-axis high-speed stepping platform. A control device is connected to each device and performs: A: generate a random number sequence, determine the target control valve of the selected channel; B: drive the three-axis high-speed stepping platform to position to the target valve position; C: control the gas path docking of the docking head and the target control valve; D: dynamically compress the single-channel sampling time to realize full-channel high-synchronization traversal sampling.

[0007] Preferably, the control device generates a random sequence using the Xorshift128+ algorithm when randomly gating; and dynamically masks the already sampled channels until the traversal is completed.

[0008] Preferably, it also includes a cleaning path, which includes a circulating pump, a control valve and a pipeline, and the control valve is also arrayed on the working platform within the movement range of the sliding table.

[0009] Preferably, in step D, the control device makes the full-channel traversal period ≤5 minutes, and the time difference between channels is independent of the number of channels.

[0010] Preferably, the traversal period is controlled by the formula t_sample = T_total / N, wherein T_total≤600 seconds, and N is the total number of channels.

[0011] Preferably, the random sequence is generated by a hardware random number generator, and a dynamic masking algorithm is used to ensure the completeness of channel traversal.

[0012] The application also provides a random gating large-scale carbon flux monitoring method, comprising the following steps: S1: random channel gating: dynamically generating a target channel number by a random number generator, and dynamically masking the already sampled channels; S2: three-dimensional precise positioning: driving the sliding table of the three-axis high-speed stepping platform to move, so that the docking head sharing the terminal gas path is positioned above the target channel control valve, and the positioning accuracy is ≤±0.1mm; S3: gas path docking and sampling: controlling the airtight connection of the docking head and the target control valve, starting the carbon flux measuring instrument to collect gas data, and after completion, cleaning the gas path of the carbon flux measuring device by the cleaning path, and dynamically compressing the single-channel sampling time according to the total number of channels; S4: high-synchronization traversal control: repeating steps S1-S3 until all channels are traversed, so that the maximum time difference of full channels is independent of the number of channels; S5: output timestamp alignment dataset: generate a carbon flux monitoring result with a channel-to-channel time deviation ≤constant threshold.

[0013] Preferably, step S1 comprises: initializing the Xorshift128+ algorithm seed based on the environmental noise entropy source; generating an unpredictable random sequence, and removing the selected channel number in real time.

[0014] Preferably, the constant threshold in step S5 is 120 seconds, and the single-channel sampling duration is dynamically compressed by the formula t_sample = 120 / N, where N is the total number of channels.

[0015] The technical effects achieved by the present application are as follows: the present application generates random numbers in real time through the control system to select the channel that needs to be sampled, positions the slide table of the three-axis high-speed stepping platform to the target valve position, and controls the air path docking of the docking head and the target control valve. All channels share a shared terminal air path, avoiding the problem of increasing residual gas in the air path with the increase in the number of channels. Moreover, since the channels are randomly selected, the differences in sampling time points of each channel caused by sequential switching are also avoided. Through air path switching in a short time slice, carbon flux data of each channel can be obtained in quasi-synchronization within each measurement period. The time phase difference between channels can be controlled and shortened to within 5 minutes, and the time phase difference between channels is not affected by the number of channels. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is a schematic diagram of the overall structure of the present application.

[0017] In the drawings, the components represented by each reference numeral are listed as follows: 100, monitoring and sampling device; 200, cleaning path; 300, random selection device; 400, carbon flux measurement device; 500, control device; 110, monitoring device; 120, circulating pump; 130, control valve; 140, pipeline; 210, circulating pump; 220, control valve; 230, pipeline; 310, three-axis high-speed stepping platform; 311, slide table; 410, carbon flux measurement instrument; 420, shared terminal air path; 421, docking head; 510, hardware random number generator. DETAILED DESCRIPTION

[0018] In order to make the purpose and advantages of the present application clearer and more apparent, the present application will be specifically described below in conjunction with examples. It should be understood that the following text is only used to describe one or several specific embodiments of the present application, and does not strictly limit the specific protection scope requested by the present application.

[0019] As Figure 1As shown, the random gating large-scale multi-channel carbon flux monitoring system of the present application comprises a plurality of sets of monitoring sampling devices 100, a cleaning path 200, a random gating device 300, a carbon flux measuring device 400 and a control device 500.

[0020] The plurality of sets of monitoring sampling devices are arranged at predetermined sampling points for monitoring and sampling; each set of monitoring sampling devices comprises a monitoring device 110, a circulating pump 120 and a control valve 130, and the monitoring device 110, the circulating pump 120 and the control valve 130 are connected in series through a pipeline 140 to form an independent path.

[0021] The cleaning path 200 comprises a circulating pump 210, a control valve 220 and a pipeline 230, and the inlet and outlet of the cleaning path 200 are connected to fresh air or atmosphere.

[0022] The random gating device 300 is used to drive the docking head 421 to randomly connect to the target control valve (130, 220); the random gating device comprises a three-axis high-speed stepping platform 310, which is an XYZ three-axis motion robot control platform or an XYZ three-axis motion platform, and the control valves (130, 220) are arranged in an array on the working platform within the motion range of the sliding table 311.

[0023] The carbon flux measuring device 400 is used to measure the carbon flux; the carbon flux measuring device 400 comprises a carbon flux measuring instrument 410 and a shared terminal gas path 420 connected thereto, and the shared terminal gas path 420 is provided with a docking head 421 at the end, and all monitoring sampling devices 100 share the shared terminal gas path 420.

[0024] The control device 500 is connected to the above-mentioned devices and performs the following tasks: A: generating a random number sequence to determine the target control valve to be gated; when the control device performs random gating, the Xorshift128+ algorithm is used to generate a random sequence, the random sequence is generated by a hardware random number generator, and a dynamic masking algorithm is used to dynamically mask the sampled channels until the traversal is completed, ensuring the integrity of the channel traversal; B: driving the three-axis high-speed stepping platform to position to the target valve position; C: controlling the gas path docking of the docking head and the target control valve; D: dynamically compressing the single-channel sampling time, so that the full-channel traversal period is less than or equal to two minutes, and the traversal period is controlled by the formula t_sample = T_total / N, wherein T_total≤120 seconds, N is the total number of channels, and it can be seen that the time difference between channels is independent of the number of channels, and full-channel high-synchronous traversal sampling is achieved.

[0025] The random gating large-scale carbon flux monitoring method of the aforementioned random gating large-scale multi-channel carbon flux monitoring system comprises the following steps: S1: Random channel gating: dynamically generating a target channel number by a hardware random number generator 510, and dynamically shielding the sampled channel; S2: Three-dimensional precision positioning: driving the slide table of the three-axis high-speed stepping platform to move, so that the docking head sharing the terminal gas path is positioned above the control valve of the target channel, with a positioning accuracy of ≤±0.1 mm; S3: Gas path docking and sampling: controlling the docking head to be airtight connected with the target control valve, starting the carbon flux measuring instrument to collect gas data, and after completion, cleaning the gas path of the carbon flux measuring device, and dynamically compressing the single-channel sampling duration according to the total number of channels; S4: High-synchronization traversal control: repeating steps S1-S3 until all channels are traversed, so that the maximum time difference of all channels is independent of the number of channels; S5: Output timestamp alignment dataset: generating a carbon flux monitoring result with a time deviation between channels ≤ a constant threshold.

[0026] Preferably, step S1 comprises: initializing the Xorshift128+ algorithm seed based on the environmental noise entropy source; generating an unpredictable random sequence, and removing the selected channel number in real time.

[0027] Preferably, the constant threshold in step S5 is 120 seconds, and the single-channel sampling duration is dynamically compressed by the formula t_sample = 120 / N, where N is the total number of channels.

[0028] The present application generates random numbers in real time by using a control system to gate the channels that need to be sampled, positions the slide table of the three-axis high-speed stepping platform to the target valve position, and controls the gas path docking of the docking head and the target control valve. All channels share a shared terminal gas path, which avoids the problem of increasing residual gas in the gas path with the increase of the number of channels, and since it is randomly gated, it also avoids the difference in sampling time points of each channel caused by sequential switching. By switching the gas path in a short time slice, the carbon flux data of each channel can be obtained in quasi-synchronization within each measurement period, the time phase difference between channels can be controlled and shortened to 2 minutes, and the channel time phase difference is not affected by the number of channels.

[0029] The above only describes the preferred embodiments of the present application, and it should be noted that for ordinary skilled persons in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which should also be considered as the protection scope of the present application. The structures, devices and operation methods not specifically described and explained in the present application, such as without special description and limitation, are implemented according to the conventional means in the art.

Claims

1. A random strobe large scale multi-channel carbon flux monitoring system characterized by, Comprise: A plurality of groups of monitoring sampling devices are respectively arranged at predetermined sampling points; each group of monitoring sampling devices comprises a monitoring device, a circulating pump and a control valve, and the monitoring device, the circulating pump and the control valve are connected in series through pipelines to form a passage; A carbon flux measuring device is used for measuring carbon flux; the carbon flux measuring device comprises a carbon flux measuring instrument and a shared terminal gas path connected thereto, and a connector is arranged at the end of the shared terminal gas path, and all the monitoring sampling devices share the shared terminal gas path; A random gating device is used for driving the connector to be connected to a target control valve; the random gating device comprises a three-axis high-speed stepping platform, and the control valve array is arranged on a work platform within the movement range of the sliding table of the three-axis high-speed stepping platform; A control device is connected to each device and performs: A: generating a random number sequence to determine the target control valve to be gated; B: driving the three-axis high-speed stepping platform to position to the target valve position; C: controlling the gas path connection of the connector and the target control valve; D: dynamically compressing the single-channel sampling time to realize full-channel high-synchronization traversal sampling.

2. The random-gated large-scale multi-channel carbon flux monitoring system of claim 1, wherein: When the control device performs random gating, the Xorshift128+ algorithm is used to generate a random sequence; the already-sampled channels are dynamically shielded until the traversal is completed.

3. The random-gated large-scale multi-channel carbon flux monitoring system of claim 1, wherein: It also comprises a cleaning passage, which comprises a circulating pump, a control valve and a pipeline, and the control valve is also arrayed on a work platform within the movement range of the sliding table.

4. The random-gated large-scale multi-channel carbon flux monitoring system of claim 1, wherein: In step D, the control device makes the full-channel traversal period ≤5 minutes, and the time difference between channels is independent of the number of channels.

5. The random-gated large-scale multi-channel carbon flux monitoring system of claim 4, wherein: The traversal period is controlled by the formula t_sample = T_total / N, wherein T_total≤600 seconds, and N is the total number of channels.

6. The random-gated large-scale multi-channel carbon flux monitoring system of claim 1, wherein: The random sequence is generated by a hardware random number generator, and a dynamic shielding algorithm is used to ensure the completeness of channel traversal.

7. A method of random gating large scale carbon flux monitoring, characterized by, The steps comprise: S1: random channel gating: generating a target channel number by randomization and dynamically shielding the already-sampled channels; S2: three-dimensional positioning: driving the sliding table of the three-axis high-speed stepping platform to move, so that the connector of the shared terminal gas path is positioned above the control valve of the target channel; S3: gas path connection and sampling: controlling the airtight connection of the connector and the target control valve, starting the carbon flux measuring instrument to collect gas data, and after the collection is completed, cleaning the gas path of the carbon flux measuring device through the cleaning passage, and dynamically compressing the single-channel sampling time according to the total number of channels; S4: high-synchronization traversal control: repeating steps S1-S3 until all channels are traversed, and the maximum time difference between full channels is independent of the number of channels; S5: output timestamp alignment dataset: generating carbon flux monitoring results with a time deviation between channels ≤a constant threshold.

8. The random strobe large-scale carbon flux monitoring method of claim 8, wherein, Step S1 comprises: initializing the Xorshift128+ algorithm seed based on environmental noise entropy source; generating an unpredictable random sequence, and removing the already-gated channel number in real time.

9. The random strobe large-scale carbon flux monitoring method of claim 8, wherein, In step S5, the constant threshold is 120 seconds, and the single-channel sampling time is dynamically compressed by the formula t_sample = 120 / N, wherein N is the total number of channels.

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