Non-methane total hydrocarbon automatic sampler

Abstract

The invention relates to the technical field of air pollution monitoring and intelligent control, and provides a non-methane total hydrocarbon automatic sampler. The existing non-methane total hydrocarbon sampling equipment has the problems of low sampling efficiency, poor environmental adaptability and insufficient data analysis capability, and is difficult to meet the sampling requirement in a complex environment. Through modular hardware design, the system comprises a sampling device, an ultrasonic cleaning device, a manipulator device, a sensor assembly and an intelligent control unit, and a control layer adopts an inverse kinematics algorithm, fuzzy logic control and a path planning technology based on an A * algorithm to dynamically optimize movement of a mechanical arm, pressure adjustment of blockages and a sampling path. The system integrated sensor assembly performs environmental data acquisition, and performs data processing through the Kalman filter, so that the sampling stability and accuracy are remarkably improved. The device can realize efficient and automatic sampling of non-methane total hydrocarbon, and is widely applicable to the field of atmospheric pollution monitoring.

Description

Technical Field

[0001] The invention relates to the technical field of air pollution monitoring, in particular to an automatic sampler for non-methane total hydrocarbons. Background Art

[0002] As the problem of air pollution becomes increasingly serious, non-methane hydrocarbons (NMHC), as an important volatile organic compound in the atmosphere, have attracted much attention for their impact on the environment and human health. NMHC is not only an important precursor to the formation of photochemical smog, but also directly participates in the formation of ozone and fine particulate matter (PM2.5). Therefore, accurate and efficient sampling and monitoring of NMHC has become a key link in air pollution control and research. However, there are still many technical bottlenecks in the traditional sampling devices on the market. Most traditional devices rely on manual operation, with low sampling efficiency and easy to be affected by human factors. At the same time, it is difficult to accurately locate the sampling point in a complex environment, resulting in insufficient reliability and consistency of the sampling data. In addition, these devices have a low degree of automation and are difficult to adapt to the needs of multiple scenarios. They can usually only complete a single function under ideal conditions and lack the ability to dynamically adjust the sampling path and operation process.

[0003] In the existing technology, most sampling equipment only has basic data recording functions, but lacks the ability to intelligently analyze and deeply process the sampling data, and is unable to dynamically optimize the sampling strategy according to real-time environmental changes. At the same time, traditional equipment has poor adaptability in complex scenarios (such as scenarios with many obstacles or drastic changes in environmental conditions), and it is difficult to meet the high requirements of modern atmospheric environmental monitoring for accuracy, efficiency and automation. Therefore, the existing non-methane total hydrocarbon sampling technology still has a lot of room for improvement in improving the intelligence level of equipment, enhancing environmental adaptability and realizing multi-functional integration.

[0004] The present invention aims to solve the above-mentioned problems of traditional equipment and provide a non-methane total hydrocarbon automatic sampler, which significantly improves the accuracy and automation level of the sampling process by integrating intelligent path planning, real-time visual feedback, adaptive force control and multimodal analysis technology, meets the sampling needs in complex environments, and provides reliable technical support for atmospheric pollution monitoring. Summary of the invention

[0005] The purpose of the present invention is to provide an automatic sampler for non-methane total hydrocarbons, which aims to achieve efficient sampling, precise positioning and automatic operation of non-methane total hydrocarbons through intelligent path planning, adaptive force control algorithm and multimodal data fusion technology, and solve the problems of low sampling efficiency, poor environmental adaptability, insufficient data analysis ability and the like in the prior art. To achieve the above purpose, the automatic sampler for non-methane total hydrocarbons provided by the present invention comprises:

[0006] Two-layer architecture, the first layer is the hardware layer, specifically including the following components: sampling device, cleaning device, manipulator device, sensor assembly, housing, intelligent control unit; the sampling device includes a sampling probe, a sampling pump and a filter unit; the cleaning device is an ultrasonic cleaning device; the manipulator device includes a mechanical arm and a blocking device, which is used to seal the sampling path after the sampling is completed; the sensor assembly includes a camera, a gas sensor, an environmental sensor and a flow sensor, which are used to monitor the concentration of non-methane total hydrocarbons. The intelligent control unit is located inside the housing and includes: a chip, which is used to realize the automatic operation of the equipment, the dynamic optimization of the sampling path, and data processing and transmission.

[0007] The second layer of the device is a control layer, including:

[0008] The robot arm motion module uses an inverse kinematics algorithm to control the motion of the robot arm; the inverse kinematics algorithm is based on the recursive Newton-Euler Algorithm (RNEA) to plan and control the motion of the robot arm joints. The system calculates the motion angle of the robot arm joint according to the spatial position of the sampling device, and the stepper motor is accurately adjusted according to the angle;

[0009] The plug contact force module uses a fuzzy logic control algorithm to achieve real-time adjustment of the contact force of the robot arm during the plugging operation. The algorithm uses the force feedback error ΔF and the plug shape parameter θ as input, and converts the force feedback error and shape parameter into corresponding fuzzy sets through fuzzification processing; the system executes the fuzzy reasoning process, uses set operations to evaluate the activation degree of each rule, and calculates the output value based on the activation rule; generates force adjustment instructions based on the current contact state during the plugging process, dynamically optimizes the pressure applied by the robot arm, ensures that the plug can be reliably inserted into the syringe and form a seal, and avoids excessive force that causes damage to the plug or inability to reset;

[0010] The path planning module adopts a sampling path planning algorithm based on the A* algorithm (A-star algorithm) and combines it with the dynamic window method (DWA) to optimize the sampler motion path, ensuring that the robotic arm avoids obstacles in complex environments and plans and executes the optimal sampling path; at the same time, the system uses sensor modules to collect environmental data in real time for accurate positioning of sampling points and path correction; the visual feedback mechanism uses the Kalman filter to filter noise and process images of the collected data, further improving the accuracy of path planning and the stability of sampling.

[0011] The sampling probe in the sampling device is made of corrosion-resistant metal material; the ultrasonic cleaning device includes a built-in ultrasonic oscillator, a liquid storage tank and a control valve; the mechanical arm in the manipulator device is driven by a three-degree-of-freedom servo motor. The chip of the intelligent control unit includes an embedded microprocessor and a real-time operating system.

[0012] The robot arm motion module uses an inverse kinematics algorithm to control the movement of the robot arm. The inverse kinematics algorithm is based on a recursive Newton-Euler Algorithm (RNEA) to plan the motion of the joints of the robot arm, and the control module includes a motion planning unit and a joint driving unit, wherein: the motion planning unit is used to calculate the motion angle of the robot arm joint according to the target position of the sampling device; the joint driving unit adjusts the joint position in real time through a stepper motor and performs motion synchronization control.

[0013] The control layer includes a robot arm motion module, which uses an inverse kinematics algorithm to control the movement of the robot arm. The inverse kinematics algorithm is based on a recursive Newton-Euler Algorithm (RNEA) to perform motion planning for the joints of the robot arm, and the control module includes a motion planning unit and a joint driving unit, wherein: the motion planning unit is used to calculate the motion angle of the robot arm joint according to the target position of the sampling device; the joint driving unit adjusts the joint position in real time through a stepper motor and performs motion synchronization control.

[0014] The blockage contact force module further includes a force control unit, which adjusts the contact force of the robot arm in the blockage operation in real time through a fuzzy logic control algorithm. The force control unit includes:

[0015] A force feedback sensor is used to collect real-time contact force signals when the robot arm is applying force;

[0016] The fuzzy reasoning processor is used to perform fuzzy reasoning according to the force feedback error ΔF and the blockage shape parameter θ, and generate a robot arm force adjustment instruction.

[0017] The fuzzy inference processor includes: a fuzzification module, which is used to map the force feedback error and the blockage shape parameter to fuzzy sets respectively; a rule activation module, which is used to perform rule activation operations according to the fuzzy sets; and a defuzzification module, which is used to generate an adjusted manipulator force output signal according to the rule activation result. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments or exemplary embodiments of the present invention, the drawings required for use in the embodiments or exemplary descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained according to the drawings without paying creative work.

[0019] Figure 1 This is the overall structure diagram of a non-methane total hydrocarbon automatic sampler

[0020] Figure 2 Specific structure diagram of the cleaning device

[0021] Figure 3 Specific structure diagram of the manipulator device

[0022] Legend:

[0023] 1. Sampling device; 2. Cleaning device; 3. Manipulator device; 31. Robotic arm; 32. Blocking device; 4. Sensor assembly; 5. Housing.

[0024] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0025] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0026] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0027] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0028] See also Figure 1 As shown, the present invention discloses an automatic sampler for non-methane total hydrocarbons, comprising a sampling device 1, a cleaning device 2, a manipulator device 3, a sensor assembly 4 and a housing 5.

[0029] The housing 5 is the main structure of the system, which is used to carry and connect all functional modules, and provide overall support and protection for the equipment. The housing 5 is made of high-strength, corrosion-resistant metal material and can operate for a long time in a complex environment. The housing 5 is provided with a plurality of mounting slots and interfaces for fixing modules such as the sampling device 1, the cleaning device 2 and the sensor assembly 4. The bottom of the housing 5 is equipped with shock-absorbing feet, and the top is provided with a detachable panel for daily maintenance and equipment adjustment.

[0030] The sampling device 1 is installed in the central area of ​​the housing 5 and is the core module of the sampling system, which is used to extract non-methane total hydrocarbon gas samples from the target environment. The sampling device 1 is connected to the sensor assembly 4 through a precision pipeline and works in conjunction with the cleaning device 2 to ensure the purity of the sampled gas.

[0031] The cleaning device 2 is as follows Figure 2 As shown, it is installed in the rear area of ​​the housing 5. The cleaning device 2 includes an ultrasonic oscillator and a cleaning liquid supply unit, which is used to clean the sampling path through high-frequency vibration and cleaning liquid to remove gases and pollutants that may remain during the sampling process. The cleaning device 2 cooperates with the sampling device 1 through automatic control to ensure cleaning efficiency and cleaning effect.

[0032] The manipulator device 3 is as follows Figure 3 As shown, it is located on one side of the housing 5 and includes a mechanical arm 31 and a blocking device 32. The mechanical arm 31 is composed of a multi-degree-of-freedom joint and a servo motor, and can complete complex movements under the precise control of the control module. The blocking device 32 is installed at the end of the mechanical arm 31 and is made of a flexible material. It is used to reliably plug the blocking object into the sampling syringe after the sampling is completed to ensure the path is sealed.

[0033] The sensor assembly 4 integrates a gas sensor, a temperature and humidity sensor, and a flow sensor for real-time monitoring of sampling environmental parameters and non-methane total hydrocarbon concentration. The sensor assembly 4 is installed inside the housing 5 and transmits the collected information to the control module through a data interface to achieve intelligent analysis and dynamic adjustment.

[0034] The hardware layer of the present invention realizes the functional coordination of sampling, cleaning, sealing and monitoring through modular design and precise layout, and provides efficient and stable hardware support for non-methane total hydrocarbon sampling in complex environments.

[0035] The control layer is the core component of the present invention. It realizes the precise motion control of the robot arm, the contact force adjustment of the blockage operation and the path planning optimization through the logical coordination of the data flow. First, the robot arm motion module realizes the precise control of the robot arm based on the inverse kinematics algorithm. The algorithm adopts the recursive Newton-Euler Algorithm (RNEA) to perform motion planning and synchronous control on the multi-degree-of-freedom joints of the robot arm. The robot arm motion module includes a motion planning unit and a joint driving unit, wherein the motion planning unit calculates the motion angle of each joint of the robot arm according to the spatial position of the sampling device; the joint driving unit adjusts the actual position of the joint in real time through the stepping motor to ensure that the robot arm can accurately complete the positioning and operation of the blockage.

[0036] The obstruction contact force module uses a fuzzy logic control algorithm to optimize and adjust the contact force of the robot arm in the operation of inserting the obstruction in real time. The force control unit of this module receives the real-time force signal from the force feedback sensor, combines the shape parameters of the obstruction, and maps the force feedback error and shape parameters into a fuzzy set through fuzzification processing. The fuzzy inference processor further performs fuzzy inference, uses the rule activation module to perform set operations on the rules, and generates the final adjustment instructions based on all activated rules. The final defuzzification module converts the calculation results into the force output signal of the robot arm, thereby dynamically optimizing the pressure applied by the robot arm to ensure that the obstruction can be reliably inserted into the syringe and form a seal, while avoiding damage to the obstruction or reset failure due to excessive force.

[0037] The path planning module adopts a global path planning method based on the A* algorithm, and combines the dynamic window approach (DWA) to achieve local path optimization. The system collects data in the sampling environment in real time through sensor components, including the location of the sampling point, the dynamic characteristics of the environment, and obstacle information. The data collected by the sensor module is processed by the Kalman filter to remove noise and optimize image quality, and then passed to the path planning module for analysis. The path planning module ensures that the robot arm can avoid obstacles in complex environments and complete sampling and blocking operations with the optimal path through dynamic coordinated adjustment of global and local paths.

[0038] The control layer of the present invention also includes an intelligent control unit, which is composed of an embedded microprocessor and a real-time operating system, and is used to comprehensively schedule the tasks of the robot arm motion module, the blockage force module, and the path planning module. The intelligent control unit receives data input from the sensor component and analyzes it in real time, and dynamically adjusts the execution status of each module according to the feedback of the data stream, thereby achieving efficient and accurate automated operation.

[0039] Through the coordinated operation of the above modules, the control layer of the present invention can effectively solve the problems of low sampling efficiency, unstable blocking operation and insufficient path planning in the prior art, and provide reliable technical support for the sampling and sealing of non-methane total hydrocarbons in complex environments.

Claims

1. A non-methane total hydrocarbon automatic sampler, characterized in that: The sampler logic mechanism design includes a two-layer architecture, wherein the first layer of the logic structure is a hardware layer, which specifically includes the following components: a sampling device (1), a cleaning device (2), a manipulator device (3), a sensor component (4), a housing (5), and an intelligent control unit; the sampling device (1) includes a sampling probe, a sampling pump, and a filter unit; the cleaning device (2) is an ultrasonic cleaning device; the manipulator device (3) includes a mechanical arm (31) and a blocking device (32) for sealing the sampling path after sampling is completed; the sensor component (4) includes a camera, a gas sensor, an environmental sensor, and a flow sensor for monitoring the concentration of non-methane total hydrocarbons; The intelligent control unit is located inside the housing (5) and includes: a chip for realizing automatic operation of the device, dynamic optimization of the sampling path, data processing and transmission; The second layer of the sampler logic structure is the control layer, including: Robotic arm motion module: The control module uses an inverse kinematics algorithm to control the motion of the robotic arm; the inverse kinematics algorithm is based on a recursive Newton-Euler Algorithm (RNEA) to plan and control the motion of the robotic arm joints. The system calculates the motion angle of the robotic arm joints based on the spatial position of the sampling device, and the stepper motor is precisely adjusted based on the angle; Blockage contact force module: The module uses a fuzzy logic control algorithm to achieve real-time adjustment of the contact force of the robot arm during the operation of plugging a blockage. The algorithm uses the force feedback error ΔF and the blockage shape parameter θ as inputs, and uses fuzzification processing to convert the force feedback error and shape parameter into corresponding fuzzy sets; the system executes the fuzzy reasoning process, uses set operations to evaluate the activation degree of each rule, and calculates the output value based on the activation rule; generates force adjustment instructions based on the current contact state during the plugging process, and dynamically optimizes the pressure applied by the robot arm; Path planning module: The module adopts a sampling path planning algorithm based on the A* algorithm (A-star algorithm) and combines it with the dynamic window method (DWA) to optimize the sampler motion path; at the same time, the system uses a sensor module to collect environmental data in real time; the visual feedback mechanism uses a Kalman filter to perform noise filtering and image processing on the collected data.

2. The automatic sampler of non-methane total hydrocarbons according to claim 1, characterized in that: The sampling probe in the sampling device (1) is made of corrosion-resistant metal material.

3. The automatic sampler of non-methane total hydrocarbons according to claim 1, characterized in that: The ultrasonic cleaning device (2) comprises a built-in ultrasonic oscillator, a liquid storage tank and a control valve.

4. The automatic sampler of non-methane total hydrocarbons according to claim 1, characterized in that: The mechanical arm (31) in the mechanical hand device (3) is driven by a three-degree-of-freedom servo motor.

5. The automatic sampler of non-methane total hydrocarbons according to claim 1, characterized in that: The chip of the intelligent control unit includes an embedded microprocessor and a real-time operating system.

6. The automatic sampler of non-methane total hydrocarbons according to claim 1, characterized in that: The control layer includes a robotic arm motion module, which uses an inverse kinematics algorithm to control the movement of the robotic arm. The inverse kinematics algorithm is based on a recursive Newton-Euler Algorithm (RNEA) to perform motion planning on the joints of the robotic arm, and the control module includes a motion planning unit and a joint driving unit, wherein: the motion planning unit is used to calculate the motion angle of the robotic arm joint according to the target position of the sampling device; the joint driving unit adjusts the joint position in real time through a stepping motor and performs motion synchronization control.

7. The automatic sampler for non-methane total hydrocarbons according to claim 1, characterized in that: The blockage contact force module further includes a force control unit, which adjusts the contact force of the robot arm in the blockage insertion operation in real time through a fuzzy logic control algorithm. The force control unit includes: a force feedback sensor; a fuzzy inference processor.

8. The automatic sampler for non-methane total hydrocarbons according to claim 7, characterized in that: The fuzzy inference processor uses a fuzzification module, a rule activation module, and a defuzzification module for operation.

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