Intelligent gas pipeline waste gas safe treatment method and system based on Internet of Things

Abstract

The invention provides an intelligent gas pipeline waste gas safety treatment method and system based on the Internet of Things. The system comprises an intelligent gas government safety supervision management platform, an intelligent gas government safety supervision sensing network platform, a gas company management platform, a gas company sensing network platform and a gas equipment object platform. The gas company management platform is configured to determine the waste gas emission standard of the to-be-treated pipeline based on the waste gas treatment grade of the to-be-treated pipeline; responding to waste gas emission of the to-be-treated pipeline, and obtaining instant treatment parameters of waste gas treatment equipment in the to-be-treated pipeline; determining an expected treatment parameter based on at least one of the exhaust emission criteria, the immediate treatment parameter, and the exhaust characteristic; and generating an adjustment instruction according to the expected treatment parameter, and adjusting the treatment parameter of the waste gas treatment equipment based on the adjustment instruction. By means of the method and system, the waste gas treatment effect can be guaranteed, and the treated waste gas can reach the emission standard more efficiently and accurately.

Description

Technical Field

[0001] This specification relates to the field of gas safety, and in particular to a smart gas pipeline exhaust safety treatment method and system based on the Internet of Things. Background Art

[0002] During the renovation and repair of gas pipelines, it is necessary to treat the gas inside the local gas pipelines, such as venting and depressurizing, igniting and evacuating, so as to reduce the gas concentration in the gas pipeline to a safe range. However, the existing emission equipment only meets qualitative requirements, such as reducing the gas pressure to a certain degree or reducing the gas concentration in the pipeline to a certain level. The current method lacks the evaluation of the treatment efficiency and stability of the treatment process.

[0003] CN216259902U provides a natural gas waste gas treatment device applied to a long-distance natural gas pipeline. The natural gas waste gas treatment device is used to treat the natural gas discharged from various pressure relief points of the long-distance pipeline, absorb methane and other gases through adsorption, and treat the natural gas discharged by pressure relief before discharging it into the atmosphere.

[0004] The above method uses natural gas waste gas treatment equipment to treat the gas discharged from the pipeline, but does not conduct a systematic assessment of the waste gas emission time and emission risks, which poses a safety hazard.

[0005] Therefore, it is hoped to provide a smart gas pipeline exhaust safety treatment method and system based on the Internet of Things, which can systematically manage and evaluate pipeline exhaust gas emissions, thereby ensuring the safety of exhaust gas emissions. Summary of the invention

[0006] In order to better manage and evaluate pipeline exhaust gas emissions in a systematic manner and ensure the safety of exhaust gas emissions, we hope to develop a smart gas pipeline exhaust gas safety treatment method and system based on the Internet of Things.

[0007] The invention content includes a smart gas pipeline waste gas safety treatment system based on the Internet of Things, the system includes a smart gas government safety supervision management platform, a smart gas government safety supervision sensor network platform, a gas company management platform, a gas company sensor network platform and a smart gas equipment object platform; the gas company management platform includes a processor, and the gas company management platform is configured to: determine the waste gas emission standard of the pipeline to be treated based on the waste gas treatment level of the pipeline to be treated; in response to the pipeline to be treated starting to emit waste gas, obtain the real-time processing parameters of the waste gas treatment equipment in the pipeline to be treated from the gas equipment object platform through the gas company sensor network platform; based on the waste gas emission standard, the real-time processing parameters and at least one of the waste gas characteristics, determine the expected processing parameters corresponding to a preset time point in the future; generate an adjustment instruction according to the expected processing parameter, and send the adjustment instruction to the gas equipment object platform through the gas company sensor network platform to control the gas equipment object platform to adjust the processing parameters of the waste gas treatment equipment based on the adjustment instruction.

[0008] The invention content also includes a method for safe treatment of waste gas from a smart gas pipeline based on the Internet of Things. The method is executed by a processor of a gas company management platform in a gas pipeline waste gas treatment system based on the Internet of Things, and includes: determining the waste gas emission standard of the pipeline to be treated based on the waste gas treatment level of the pipeline to be treated; in response to the pipeline to be treated starting to discharge waste gas, obtaining the real-time processing parameters of the waste gas treatment equipment in the pipeline to be treated from the smart gas equipment object platform through the gas company sensor network platform; determining the expected processing parameters corresponding to a preset time point in the future based on the waste gas emission standard, the real-time processing parameters and at least one of the waste gas characteristics; generating an adjustment instruction according to the expected processing parameter, and sending the adjustment instruction to the smart gas equipment object platform through the gas company sensor network platform to control the smart gas equipment object platform to adjust the processing parameters of the waste gas treatment equipment based on the adjustment instruction.

[0009] Through the aforementioned method and system, the exhaust gas treatment effect can be guaranteed, and the treated exhaust gas can meet the emission standards more efficiently and accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein: Figure 1 It is an exemplary platform structure diagram of a smart gas pipeline waste gas safety treatment system based on the Internet of Things according to some embodiments of this specification; Figure 2It is an exemplary flow chart of a safe treatment method for waste gas in a smart gas pipeline based on the Internet of Things according to some embodiments of this specification; Figure 3 is a schematic diagram of determining expected processing parameters based on expected processing efficiency according to some embodiments of this specification; Figure 4 is a schematic diagram of determining expected treatment parameters based on exhaust gas treatment time according to some embodiments of this specification; Figure 5 It is a schematic diagram of determining expected processing parameters based on emission risks according to some embodiments of this specification.

[0011] Explanation of the accompanying reference numerals: 100-Smart gas pipeline waste gas safety treatment system based on the Internet of Things; 110-Smart gas government safety supervision and management platform; 120-Smart gas government safety supervision sensor network platform; 130-Smart gas government safety supervision object platform; 140-Gas company sensor network platform; 150-Smart gas equipment object platform; 310-Waste gas emission standards; 320-Real-time processing parameters; 330-Waste gas characteristics; 340-Standard processing efficiency; 350-Environmental characteristics; 360-Target processing efficiency; 370-Expected processing parameters; 410-Pipeline parameters; 420-Historical pressure regulation parameter sequence; 430-Waste gas volume to be treated; 440-Waste gas treatment time; 450-Duration conditions; 510-Pipeline characteristics; 520-Historical environmental characteristics; 530-Historical waste gas characteristics; 540-Risk assessment model; 550-Emission risk; 560-Temperature sequence of the target period. DETAILED DESCRIPTION

[0012] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0013] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0014] Unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0015] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0016] Figure 1 This is an exemplary platform structure diagram of the smart gas pipeline waste gas safety treatment system based on the Internet of Things shown in some embodiments of this specification. The smart gas pipeline waste gas safety treatment system 100 based on the Internet of Things (also referred to as the Internet of Things system) involved in the embodiments of this specification will be described in detail below. It should be noted that the following embodiments are only used to explain this specification and do not constitute a limitation on this specification.

[0017] In some embodiments, the Internet of Things system includes a smart gas government safety supervision management platform 110, a smart gas government safety supervision sensor network platform 120, a smart gas government safety supervision object platform 130, a gas company sensor network platform 140 and a smart gas equipment object platform 150.

[0018] The smart gas government safety supervision and management platform 110 is a comprehensive management platform for government departments to supervise gas pipelines and gas companies. In some embodiments, the smart gas government safety supervision and management platform can be configured to supervise the gas pipeline waste gas treatment process based on the Internet of Things, and process and / or store relevant data of the gas pipeline waste gas treatment process. The relevant data of the gas pipeline waste gas treatment process may include but are not limited to the environmental characteristics of the pipeline to be treated, the historical waste gas treatment time of the pipeline to be treated, and the corresponding historical scores.

[0019] The smart gas government safety supervision sensor network platform 120 is a platform for comprehensive management of government sensor information. In some embodiments, the smart gas government safety supervision sensor network platform 120 can realize the functions of sensing information sensing communication and controlling information sensing communication between the smart gas government safety supervision management platform 110 and the smart gas government safety supervision object platform 130.

[0020] The smart gas government safety supervision object platform 130 is a platform for generating government supervision information and controlling information execution. For example, the smart gas government safety supervision object platform 130 can obtain safety supervision demand information to enable government safety supervisors to perform safety supervision on tasks related to gas pipeline waste gas treatment.

[0021] In some embodiments, the smart gas government safety supervision object platform 130 may include a gas company management platform.

[0022] In some embodiments, the gas company management platform can exchange data with the smart gas government safety supervision management platform 110 through the smart gas government safety supervision sensor network platform 120. For example, the gas company management platform can obtain data such as environmental characteristics of the pipeline to be treated, historical waste gas treatment time of the pipeline to be treated, and corresponding historical scores from the smart gas government safety supervision management platform 110 via the smart gas government safety supervision sensor network platform 120.

[0023] In some embodiments, the gas company management platform may include a communication module and a processor.

[0024] In some embodiments, the communication module can be used for communication and information transfer between various platforms and devices in the Internet of Things system.

[0025] In some embodiments, the processor may process information and / or data related to the Internet of Things system to perform the functions described in this specification.

[0026] The processor can be used to collect, analyze and process data, generate corresponding control instructions according to the data, and send the control instructions to the actuator to make the actuator perform corresponding actions or functions. For example, the control instructions are sent to the communication module to make the communication module perform at least one of the functions of starting, connecting, obtaining data, transmitting data, etc.

[0027] In some embodiments, the processor can determine the exhaust gas emission standard of the pipeline to be treated based on the exhaust gas treatment level of the pipeline to be treated; in response to the pipeline to be treated starting to emit exhaust gas, obtain the real-time processing parameters of the exhaust gas treatment equipment in the pipeline to be treated from the smart gas equipment object platform through the gas company sensor network platform; based on the exhaust gas emission standard, the instant processing parameters and at least one of the exhaust gas characteristics, determine the expected processing parameters corresponding to a preset time point in the future; generate adjustment instructions according to the expected processing parameters, and send the adjustment instructions to the smart gas equipment object platform through the gas company sensor network platform to control the smart gas equipment object platform to adjust the processing parameters of the exhaust gas treatment equipment based on the adjustment instructions. For more detailed instructions, please refer to this manual Figure 3-Figure 5 Related description.

[0028] By adopting processors and communication modules, the functions of automatic data transmission, data processing and automatic control can be realized, which improves the degree of automation of the gas pipeline exhaust treatment system based on the Internet of Things and can improve the efficiency and accuracy of gas scheduling.

[0029] In some embodiments, the gas company management platform can send an implementation plan including the processing parameters of the exhaust gas treatment equipment to the smart gas government safety supervision and management platform 110, and execute the implementation plan only when a confirmation instruction is received from the gas government safety supervision and management platform.

[0030] The gas company sensor network platform 140 is a platform for managing sensor communications. In some embodiments, the gas company sensor network platform 140 can exchange information with the gas company sensor network platform and the government safety supervision sensor network platform respectively.

[0031] In some embodiments, the gas company sensor network platform 140 can implement the functions of perception information sensor communication and control information sensor communication.

[0032] The smart gas equipment object platform 150 is a functional platform for sensing information generation and controlling information execution.

[0033] In some embodiments, the smart gas equipment object platform 150 may include at least exhaust gas treatment equipment, monitoring equipment, etc.

[0034] In some embodiments, the smart gas equipment object platform 150 can interact bidirectionally with the gas company sensor network platform. For example, the smart gas equipment object platform 150 can receive adjustment instructions issued by the gas company management platform via the gas company sensor network platform 140, and issue the adjustment instructions to the exhaust gas treatment equipment to control the treatment parameters of the exhaust gas treatment equipment.

[0035] The IoT-based smart gas pipeline waste gas safety treatment system 100 in some embodiments of this specification can form information communication between various platforms, and coordinate and operate regularly under the unified management of the smart gas government safety supervision object platform, thereby realizing the intelligence and standardization of the gas pipeline waste gas treatment process, effectively supervising the gas pipeline waste gas treatment process, and avoiding safety hazards.

[0036] It should be noted that the above description of the system and platform is only for convenience of description and does not limit the present specification to the scope of the embodiments. It is understandable that, after understanding the principle of the system, those skilled in the art may arbitrarily combine the modules or form a subsystem to connect with other modules without deviating from the principle.

[0037] Figure 2This is an exemplary flow chart of a method for treating waste gas from a gas pipeline based on the Internet of Things according to some embodiments of this specification. Figure 2 As shown, the process 200 includes the following steps. In some embodiments, the process 200 can be executed by a gas company management platform.

[0038] Step 210, determining the exhaust gas emission standard of the pipeline to be treated based on the exhaust gas treatment level of the pipeline to be treated.

[0039] The pipeline to be treated refers to the pipeline that needs to be treated with gas. Among them, gas treatment can include exhaust gas in the discharge pipe, treatment of exhaust gas in the pipeline, etc. Exhaust gas refers to the gas that needs to be discharged or treated in the gas pipeline.

[0040] The waste gas treatment level can indicate the urgency of waste gas treatment. The higher the waste gas treatment level, the more urgent the waste gas treatment is for the pipeline to be treated, and the sooner the waste gas treatment needs to be completed.

[0041] In some embodiments, the waste gas treatment level can be determined by the reason why the waste gas treatment is required for the pipeline to be treated. In some embodiments, the reason for the waste gas treatment may include at least one of easy explosion, gas leakage, pipeline modification, pressure regulation, and emergency maintenance. The gas company management platform can assign corresponding weights to different reasons, and determine the treatment evaluation value corresponding to the pipeline to be treated by weighted summation according to at least one reason corresponding to the pipeline to be treated and its corresponding weight; determine the waste gas treatment level corresponding to the pipeline to be treated based on the aforementioned treatment evaluation value and the pre-set treatment level classification standard.

[0042] In some embodiments, the reason why the waste gas treatment is required for the pipeline to be treated can be determined based on user feedback. For example, the gas company management platform can obtain the input data of the gas management user in the smart gas government safety supervision management platform through the smart gas government safety supervision sensor network platform, and then determine the reason why the waste gas treatment is required for the pipeline to be treated.

[0043] In some embodiments, the weights corresponding to different reasons can be set based on prior experience and / or actual needs. For example, the weight range for emergency situations such as gas leakage and emergency repair is the first preset range, and the weight range for non-emergency situations such as pipeline modification and pressure regulation is the second preset range. Among them, the first preset range and the second preset range are both greater than 0, and the minimum value of the first preset range is not less than the maximum value of the second preset range.

[0044] The preset processing level classification standard may be set based on at least one of prior experience, historical data, and actual needs.

[0045] In some embodiments, the treatment level classification standard can be determined based on the historical data of waste gas treatment. For example, the gas company management platform can determine the historical evaluation value corresponding to the pipeline to be treated in the historical data based on the aforementioned weights and the reasons for the waste gas treatment corresponding to different waste gas treatment operations in the historical data; determine the evaluation value range based on the maximum and minimum values ​​of the historical evaluation values, and evenly divide the evaluation value range into several levels. The gas company management platform can determine the treatment level classification standard based on the aforementioned several levels and the evaluation value ranges corresponding to different levels.

[0046] Waste gas emission standards refer to the restrictions on the concentration and / or total amount of waste gas discharged into the atmosphere. For example, waste gas emission standards may include the maximum concentration of each component in the waste gas discharged from the pipeline to be treated.

[0047] In some embodiments, the gas company management platform may determine the exhaust gas emission standard of the pipeline to be treated based on the exhaust gas treatment level of the pipeline to be treated through an emission standard reference table.

[0048] The emission standard reference table may include a reference exhaust gas treatment level and its corresponding reference emission standard. In some embodiments, the gas company management platform may be determined based on historical data that meets the requirements, and the historical data may be obtained based on the smart gas government safety supervision management platform. As an example only, the gas company management platform may obtain target historical data that meets the requirements from the smart gas government safety supervision management platform through the smart gas government safety supervision sensor network platform, determine the reference exhaust gas treatment level based on the historical exhaust gas treatment level corresponding to the target historical data, and determine the reference emission standard based on the average of the historical emission standards corresponding to at least one target historical data with the same historical exhaust gas treatment level. Among them, meeting the requirements means that there was no danger in the historical gas emission process corresponding to the historical data.

[0049] In some embodiments, the gas company management platform can determine the exhaust gas emission standard of the pipeline to be treated through preset rules based on the exhaust gas treatment level of the pipeline to be treated. The preset rules may include exhaust gas emission standards corresponding to different exhaust gas treatment levels, which can be determined based on the input of the gas supervision user.

[0050] Step 220, in response to the pipeline to be treated starting to discharge waste gas, the real-time processing parameters of the waste gas treatment equipment in the pipeline to be treated are obtained from the smart gas equipment object platform through the smart gas company sensor network platform.

[0051] Exhaust gas treatment equipment refers to equipment installed in a gas pipeline to treat pipeline exhaust gas. In some examples, the exhaust gas treatment equipment may include an induced draft fan, a filter device, and a regulating valve.

[0052] The induced draft fan can be used to extract the exhaust gas after combustion. In some embodiments, the gas company management platform can send instructions to the smart gas equipment object platform through the gas company sensor network platform to adjust the speed of the induced draft fan, thereby controlling the exhaust gas emission rate.

[0053] The filtering equipment may include dust removal equipment, desulfurization equipment, denitrification equipment and other equipment for purifying waste gas.

[0054] The regulating valve is a valve installed in the gas pipeline. In some embodiments, the gas company management platform can send instructions to the smart gas equipment object platform through the gas company sensor network platform to control the opening of the regulating valve, thereby controlling the discharge rate of the gas in the pipeline.

[0055] The instant processing parameter is a parameter that characterizes the working efficiency of the exhaust gas treatment equipment at the current time.

[0056] In some embodiments, the gas company management platform can obtain real-time processing parameters from the smart gas equipment object platform through the gas company sensor network platform. As an example only, the smart gas equipment object platform can communicate with the exhaust gas treatment equipment to obtain the real-time processing parameters of the exhaust gas treatment equipment.

[0057] Step 230, based on at least one of the exhaust emission standard, the immediate processing parameter and the exhaust characteristics, determine the expected processing parameter corresponding to the preset time point in the future.

[0058] The exhaust gas characteristics may include the components of the exhaust gas and the concentrations of the components. In some embodiments, the exhaust gas characteristics may be represented in the form of a vector, the vector including at least one element, each element representing a component in the exhaust gas and its corresponding concentration.

[0059] In some embodiments, the gas company management platform can obtain the exhaust gas characteristics from the smart gas equipment object platform through the gas company sensor network platform. As an example only, the smart gas equipment object platform can determine the exhaust gas characteristics through sensors set in the gas pipeline to be processed.

[0060] The future preset time point refers to the pre-set time for adjusting the working efficiency of the exhaust gas treatment equipment.

[0061] In some embodiments, the future preset time may be set based on prior experience and / or actual needs.

[0062] The expected treatment parameters represent the operating efficiency of the exhaust gas treatment equipment after adjustment.

[0063] In some embodiments, the gas company management platform may determine the expected processing parameters corresponding to a preset time point in the future based on at least one of the exhaust gas emission standards, technical processing parameters, and exhaust gas characteristics. As an example only, the gas company management platform may determine the expected processing parameters by querying a reference processing parameter table based on at least one of the exhaust gas emission standards, immediate processing parameters, and exhaust gas characteristics. The reference processing parameter table includes reference characteristics and their corresponding reference processing parameters. In some embodiments, the gas company management platform may obtain the recommended processing parameters input by the user based on prior experience, and determine the recommended processing parameters as the expected processing parameters.

[0064] In some embodiments, the gas company management platform can determine the standard treatment efficiency based on the exhaust gas emission standard, the immediate treatment parameters and the exhaust gas characteristics, determine the target treatment efficiency based on the standard treatment efficiency and the environmental characteristics of the pipeline to be treated, and determine the expected treatment parameters corresponding to the preset time point in the future based on the target treatment efficiency. For detailed description, see Figure 3 and its related description.

[0065] In some embodiments, the gas company management platform can also evaluate the emission risk of exhaust gas emission from the pipeline to be treated through a risk assessment model based on at least one of the pipeline characteristics, immediate processing parameters, historical environmental characteristics within a preset historical time period, and historical exhaust gas characteristics of the pipeline to be treated, and determine the expected processing parameters corresponding to the preset time point in the future in response to the emission risk not meeting the safety conditions. For detailed description, see Figure 5 and its related description.

[0066] Step 240, generating an adjustment instruction according to the expected processing parameters, and sending the adjustment instruction to the smart gas equipment object platform through the gas company sensor network platform to control the smart gas equipment object platform to adjust the processing parameters of the exhaust gas treatment equipment based on the adjustment instruction.

[0067] Adjustment instructions refer to instructions to adjust the input quantity and working efficiency of exhaust gas treatment equipment.

[0068] In some embodiments, the gas company management platform can generate adjustment instructions based on the expected processing parameters. For example, if the expected processing parameters are {( ),…,( )}, then the adjustment instruction can be determined as "processing parameters {( ),…,( )} Adjust each waste gas treatment equipment in the pipeline to be treated". Among them, ( ) is the treatment parameter of the nth exhaust gas treatment equipment in the pipeline to be treated, Indicates the on state of the nth exhaust gas treatment device. The on state can be represented by 1 or 0, 1 for on and 0 for off. Characterizes the working efficiency of the nth exhaust gas treatment equipment.

[0069] In some embodiments, the gas company management platform can send the aforementioned adjustment instructions to the smart gas equipment object platform through the gas company sensor network platform; the smart gas equipment object platform can control at least one waste gas treatment device in the treatment pipeline based on the adjustment instructions, and adjust the processing parameters of the aforementioned at least one waste gas treatment device according to the expected processing parameters contained in the adjustment instructions.

[0070] In some embodiments of the present specification, the expected treatment parameters are determined by at least one of the exhaust gas emission standard, immediate treatment parameters and exhaust gas characteristics of the pipeline to be treated, which can fully consider the current exhaust gas treatment situation and exhaust gas characteristics, and is conducive to determining more appropriate treatment parameters based on the actual treatment situation, thereby ensuring the exhaust gas treatment effect and achieving the exhaust gas emission standards more efficiently and accurately.

[0071] It should be noted that the above description of the process 200 is only for example and illustration, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to the process 200 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0072] Figure 3 FIG. 1 is a schematic diagram of determining expected processing parameters based on expected processing efficiency according to some embodiments of this specification. Figure 3 As shown, determining the expected processing parameters based on the expected processing efficiency may include the following: In some embodiments, determining the expected processing parameters based on the expected processing efficiency may be performed by a processor of the gas company management platform.

[0073] In some embodiments, the gas company management platform can determine the standard treatment efficiency 340 based on the exhaust gas emission standard 310, the immediate treatment parameters 320 and the exhaust gas characteristics 330; determine the target treatment efficiency 360 based on the environmental characteristics 350 and the standard treatment efficiency 340; and determine the expected treatment parameters 370 corresponding to a preset time point in the future based on the target treatment efficiency 360.

[0074] For more information on exhaust emission standards, immediate treatment parameters, and exhaust gas characteristics, please refer to Figure 2 and its related description.

[0075] The standard treatment efficiency is used to characterize the actual amount of waste gas discharged from the pipeline to be treated per unit time. For example, when the standard treatment efficiency is 500m 3 / h, it means that the waste gas treatment equipment in the pipeline to be treated can actually treat 500 cubic meters of waste gas per hour.

[0076] In some embodiments, the gas company management platform can determine the standard treatment efficiency in a variety of ways based on the exhaust gas emission standards, immediate treatment parameters and exhaust gas characteristics.

[0077] In some embodiments, the exhaust gas emission standard may include the maximum value of the concentration of each component in the exhaust gas. The immediate processing parameter may include the number of exhaust gas treatment devices that are currently processing exhaust gas in the pipeline to be processed and the current working efficiency of the corresponding exhaust gas treatment devices. The exhaust gas characteristics may include the concentration of each exhaust gas component. For more information about exhaust gas emission standards, immediate processing parameters, and exhaust gas characteristics, please refer to Figure 2 and its related description.

[0078] In some embodiments, the gas company management platform can determine the standard treatment efficiency of the pipeline to be treated by the following formula (1) based on the fact that the standard treatment efficiency of the pipeline to be treated is positively correlated with the standard working efficiency of each exhaust gas treatment equipment, and negatively correlated with the maximum threshold of the concentration of each exhaust gas component and the concentration of each exhaust gas component.

[0079] (1) in, is the standard processing efficiency of the pipeline to be processed, is the exhaust gas emission per unit time of the i-th exhaust gas treatment equipment in the pipeline to be treated, is the standard working efficiency corresponding to the i-th exhaust gas treatment equipment, is the intake concentration of the exhaust gas component in the pipeline to be treated, It is the maximum threshold value of the concentration of each exhaust gas component in the exhaust gas emission standard of the pipeline to be treated.

[0080] The standard operating efficiency refers to the characterization of the ability of the exhaust gas treatment device in the pipeline to be treated to treat the exhaust gas. For example, the standard operating efficiency of the exhaust gas treatment device can be expressed by the volume of exhaust gas treated per unit time. In some embodiments, the standard operating efficiency of the exhaust gas treatment device can be determined based on the specifications of the exhaust gas treatment device. In some embodiments, the standard operating efficiency of at least one exhaust gas treatment device can be different.

[0081] Environmental features are features that characterize the surrounding environment of the pipeline to be processed. For example, environmental features may include, but are not limited to, at least one of the flow of people around the pipeline to be processed, the traffic congestion index, and air fluidity. In some embodiments, environmental features may be represented in the form of a vector, and the elements in the vector may include at least one of the flow of people around the pipeline to be processed, the traffic congestion index, and air fluidity.

[0082] In some embodiments, the gas company management platform can obtain environmental characteristics of the pipeline to be processed from the smart gas government safety supervision management platform. For example, the smart gas government safety supervision management platform can collect the flow of people, traffic congestion index and air flow around the pipeline to be processed through sensors, cameras and other equipment, and transmit them to the gas company management platform.

[0083] The flow of people refers to the number of pedestrians passing around the pipeline to be treated per unit time. For example, 200 people pass around the pipeline to be treated per hour. In some embodiments, the area around the pipeline to be treated can be limited by professional technicians or by system default. As an example only, it can be an area of ​​100 square meters near the pipeline to be treated, etc., which can be set based on prior experience and / or actual needs.

[0084] The traffic congestion index refers to a value used to characterize the degree of traffic congestion on the roads around the pipeline to be processed. For example, the traffic congestion index can be a value from 0 to 100, and a larger value represents a higher degree of congestion.

[0085] Air fluidity refers to data related to the air flow velocity around the pipeline to be treated. For example, the air fluidity around the pipeline to be treated may be a wind speed of 2 m / s and a wind direction of northeast wind.

[0086] The target treatment efficiency refers to the value adjusted from the standard treatment efficiency, which is used to characterize the amount of waste gas emissions that the pipeline to be treated is expected to achieve per unit time.

[0087] In some embodiments, the treatment efficiency of the exhaust gas treatment equipment will vary with environmental factors and the state of the exhaust gas treatment equipment itself. By determining the target treatment efficiency, it is possible to better adapt to the actual environment and thus improve the exhaust gas treatment system's ability and efficiency in treating exhaust gas.

[0088] In some embodiments, the gas company management platform can determine the target processing efficiency based on the environmental characteristics and the standard processing efficiency. As an example only, the gas company management platform can determine the adjustment ratio based on the vector distance between the environmental characteristics and the standard environmental characteristics, and the weighted sum of each sub-parameter in the environmental characteristics (the flow of people around the pipeline to be processed, the traffic congestion index, and the air mobility, etc.); and adjust the standard processing efficiency based on the adjustment ratio to determine the target processing efficiency. Among them, the vector distance can be determined based on the cosine distance between the environmental characteristics and the standard environmental characteristics.

[0089] In some embodiments, the target processing efficiency is positively correlated with the standard processing efficiency. As an example only, the gas company management platform may determine the target processing efficiency based on the following formula (2).

[0090] (2) in, is the target processing efficiency of the pipeline to be processed, is the standard processing efficiency of the pipeline to be processed, is the cosine distance between the environmental feature and the standard environmental feature, is the flow of people around the pipeline to be treated in the environmental characteristics, is the traffic congestion index around the pipeline to be processed in the environmental characteristics, is the air flow around the pipeline to be treated in the environmental characteristics, , , They are the weight coefficients of passenger flow, traffic congestion index and air fluidity respectively.

[0091] In some embodiments, the weight coefficients of the flow of people around the pipeline to be treated, the traffic congestion index, and the air fluidity can be determined based on prior experience. In some embodiments, the greater the influence of a certain sub-parameter of environmental characteristics on the exhaust gas treatment, the greater the corresponding weight coefficient. As an example only, the influence of air fluidity on the diffusion of exhaust gas emissions may be greater than the flow of people and the traffic congestion index, so the weight coefficient of air fluidity can be greater than the weight coefficients of the flow of people around the pipeline to be treated and the traffic congestion index.

[0092] The standard environment characteristics refer to parameters related to the surrounding environment of the pipeline to be processed under standard conditions. For example, the standard environment characteristics may include but are not limited to the flow of people, traffic congestion index, and air fluidity under standard conditions. In some embodiments, the standard environment characteristics may be represented in the form of a vector, which may include elements such as the flow of people, traffic congestion index, and air fluidity around the pipeline to be processed under standard conditions.

[0093] Standard conditions refer to an ideal setting of characteristic parameters of the surrounding environment of the pipeline to be treated under specific circumstances. For example, standard conditions can be ideal weather, no abnormal events, and normal operation of equipment.

[0094] In some embodiments, the gas company management platform can determine the standard environment characteristics through the following steps: S1. Obtain a set of historical environmental features of the pipeline to be processed. Each environmental feature in the set of historical environmental features may include multiple sub-parameters, such as the flow of people, traffic congestion index, and air fluidity of the pipeline to be processed.

[0095] S2. Cluster the historical environmental feature set according to each sub-parameter (people flow, traffic congestion index, and air fluidity), and obtain multiple clusters A1, A2, A3, ... clustered by people flow; multiple clusters B1, B2, B3, ... clustered by traffic congestion index; multiple clusters C1, C2, C3, ... clustered by air fluidity. In some embodiments, the types of clustering algorithms may include multiple types, for example, the clustering algorithm may include K-Means clustering, density-based clustering method (DBSCAN), etc.

[0096] S3. For each sub-parameter in the historical environmental feature set, the mean of the sub-parameter in the corresponding cluster is calculated respectively; and then multiple means of the passenger flow, multiple means of the traffic congestion index, and multiple means of the air fluidity in the historical environmental feature set are obtained respectively.

[0097] S4. Calculate the weighted sum of the mean of each sub-parameter in the historical environmental feature set obtained in S3 to obtain the weighted sum of the passenger flow, the weighted sum of the traffic index, and the weighted sum of the air fluidity in the historical environmental feature set.

[0098] For example, taking the flow of people in the historical environmental feature set as an example, the gas company management platform can determine the weighted sum corresponding to the sub-parameter through the following formula (3) based on the positive correlation between the weighted sum of each sub-parameter and the mean of each cluster of each sub-parameter.

[0099] (3) in, is the weighted sum of human traffic, is the average value of human traffic in each cluster, is the weight coefficient of the mean passenger flow corresponding to cluster i.

[0100] In some embodiments, the weight coefficient k of cluster i si It is the number of environmental features in cluster i divided by the size of the historical environmental feature set.

[0101] In some embodiments, the weighted sum of the traffic congestion index and the air mobility, and the weight calculation method may be determined in a similar manner.

[0102] In some embodiments, the weight of each mean of each sub-parameter is the number of environmental features of the cluster corresponding to the sub-parameter divided by the total number of environmental features in the historical environmental feature set.

[0103] S5. The gas company management platform may determine the standard environmental characteristics based on the weighted sum of the sub-parameters determined in the aforementioned S4.

[0104] For example, the weighted sum of the pedestrian flow obtained in the above S4 is used as the pedestrian flow in the standard environmental characteristics, the weighted sum of the traffic index is used as the traffic congestion index in the standard environmental characteristics, and the weighted air fluidity is used as the air fluidity in the standard environmental characteristics; and then the standard environmental characteristics of the pipeline to be processed are obtained.

[0105] Exemplarily, take the calculation of pedestrian flow of standard environmental features as an example. Assume that there are multiple environmental features in the historical environmental feature set, and cluster the pedestrian flow in the historical environmental feature set to obtain clusters A1, A2, and A3. Then calculate the mean pedestrian flow a1 of the environmental features in cluster A1, the mean pedestrian flow a2 of the environmental features in cluster A2, and the mean pedestrian flow a3 of the environmental features in cluster A3. And use the above formula (3) to calculate the weighted sum of the pedestrian flow in the historical environmental feature set as the pedestrian flow of the standard environmental feature. In some embodiments, the traffic congestion index and air fluidity of the standard environmental feature are obtained in the same way as the pedestrian flow calculation method, and please refer to the relevant description above.

[0106] The historical environmental feature set refers to a set of environmental features at multiple moments in the historical data. For example, the historical environmental feature set can be composed of {X 1 , X 2 , …, X i , …X n}. Among them, X i Represents the environmental characteristics corresponding to the i-th moment.

[0107] In some embodiments, the gas company management platform can evenly increase the working efficiency of each exhaust gas treatment device (for example, increase the speed of the induced draft fan, increase the opening of the regulating valve, and increase the power of the filtering device) until the maximum power (or maximum speed, maximum opening). If the current exhaust gas treatment efficiency is still less than the target treatment efficiency, the number of exhaust gas treatment devices in operation is increased (increase the induced draft fan or increase the filtering device), thereby obtaining the expected treatment parameters.

[0108] In some embodiments, in response to the pipeline to be treated starting to emit exhaust gas, the gas company management platform can obtain a monitoring parameter sequence of the pipeline to be treated within a preset historical time period from the smart gas equipment object platform through the gas company sensor network platform based on the data acquisition cycle.

[0109] The data acquisition cycle refers to the frequency of obtaining data from the smart gas equipment object platform at a preset time interval. For example, the data acquisition cycle can be 1 day, 1 hour, etc.

[0110] In some embodiments, the data acquisition period can be determined in a variety of ways. For example, the data acquisition period can be set based on prior experience and / or actual needs.

[0111] In some embodiments, the data acquisition period is related to a target processing efficiency.

[0112] In some embodiments, the data acquisition period may be negatively correlated with the target processing efficiency of the current pipeline to be processed.

[0113] In some embodiments of this specification, a higher exhaust gas emission efficiency means a greater number of exhaust gas treatment devices, a higher working efficiency, and a more dramatic change in exhaust gas concentration. When an exhaust gas treatment device fails, the impact is greater. Therefore, by appropriately shortening the interval of the data acquisition cycle, it helps to take corresponding measures in a timely manner when the risk increases.

[0114] The preset historical time period refers to a preset historical time range calculated from the current moment forward. For example, the preset historical time period can be a historical time of 1 week or 1 month from the current moment.

[0115] In some embodiments, the preset historical time period may be set based on prior experience and / or actual needs.

[0116] The monitoring parameters refer to parameters used to reflect the operating status and safety of the pipeline to be processed. For example, the monitoring parameters may include but are not limited to at least one of the temperature, pressure, and gas flow rate in the pipeline to be processed.

[0117] The monitoring parameter sequence refers to a sequence consisting of monitoring parameters at multiple moments. For example, the monitoring parameter sequence can be composed of {(t 1 , Y 1 ), t 2 , Y 2 ),…,(t i , Y i ),…,(t n , Y n )}. Among them, Y i Indicates t i The monitoring parameters corresponding to the time.

[0118] In some embodiments, the gas company management platform can obtain monitoring parameters of temperature sensors, pressure sensors, flow sensors and other devices from the smart gas equipment object platform through the gas company sensor network platform.

[0119] In some embodiments, in response to the monitoring parameter sequence not satisfying a preset condition, the gas company management platform may predict a remaining processing time.

[0120] The preset condition refers to a condition used to determine whether a parameter in the monitoring parameter sequence is lower than a safe condition. For example, the preset condition may be that the temperature, pressure, and gas flow rate in the pipeline to be processed in the monitoring parameter sequence are all lower than a threshold. In some embodiments, the threshold may be set by a professional technician or by system default.

[0121] The remaining treatment time refers to the time that the pipeline to be treated needs to process the waste gas, for example, 10 minutes.

[0122] In some embodiments, the gas company management platform can determine the remaining processing time based on the exhaust gas emission time and historical data. For example, the gas company management platform can obtain the average time of the exhaust gas treatment of the pipeline to be treated in the historical data, determine the estimated time of the exhaust gas treatment of the pipeline to be treated, and determine the remaining processing time based on the estimated time of the exhaust gas treatment and the exhaust gas emission time.

[0123] In some embodiments, in response to the pipeline to be treated starting to discharge waste gas, the gas company management platform can obtain the monitoring parameter sequence of the pipeline to be treated within a preset historical time period from the smart gas equipment object platform through the gas company sensor network platform; in response to the monitoring parameter sequence not meeting the preset conditions, predict the remaining processing time. For more detailed descriptions, please refer to Figure 4 and its related description.

[0124] In some embodiments, the gas company management platform may update the target treatment efficiency according to the exhaust gas emission time, the remaining treatment time, and environmental characteristics to determine the expected treatment efficiency.

[0125] The exhaust gas emission time refers to the time that the exhaust gas has been emitted.

[0126] The expected processing efficiency refers to the data after the target processing efficiency is updated.

[0127] In some embodiments, in response to the remaining processing time being greater than the difference between the time threshold and the exhaust gas emission time, the gas company management platform can construct a to-be-matched vector based on the environmental characteristics of the pipeline to be processed, match the to-be-matched vector in the processing efficiency reference database to determine the exhaust gas processing efficiency of the pipeline to be processed, and determine the exhaust gas processing efficiency as the expected processing efficiency of the pipeline to be processed.

[0128] The treatment efficiency reference database is a database used to determine the exhaust gas treatment efficiency, and includes at least one reference scene feature vector and its corresponding reference exhaust gas treatment efficiency.

[0129] In some embodiments, the reference vector in the treatment efficiency reference database can be determined based on historical data. For example, the gas company management platform can construct a historical vector based on the historical environmental parameters of the pipeline to be treated in the historical data, cluster the historical vectors to form a preset number of cluster centers, and construct a reference vector based on the historical environmental characteristics corresponding to the cluster centers. And determine the reference exhaust gas treatment efficiency corresponding to the reference vector based on the historical exhaust gas treatment efficiency.

[0130] In some embodiments, the gas company management platform can obtain the actual exhaust gas emission time corresponding to multiple historical vectors in each cluster from the smart gas government safety supervision management platform. The exhaust gas treatment efficiency corresponding to the exhaust project with no exhaust accident and the shortest exhaust gas emission time in the exhaust treatment process corresponding to multiple historical vectors in the cluster is used as the historical exhaust gas treatment efficiency.

[0131] In some embodiments, the gas company management platform can calculate the similarity between the vector to be matched and at least one reference vector, and use the reference acquisition parameter corresponding to the reference vector with the highest similarity to the vector to be matched as the exhaust gas treatment efficiency. The similarity can be negatively correlated to the vector distance between the vector to be matched and the reference vector, and the vector distance can be determined based on the cosine distance, etc.

[0132] The time threshold is a value used to determine whether the remaining processing time is too long. For more information about the time threshold, see Figure 4 and its related description.

[0133] Exhaust gas treatment efficiency refers to the maximum emission of exhaust gas treated by the pipeline to be treated per unit time.

[0134] In some embodiments, in response to the remaining processing time being less than or equal to the difference between the time threshold and the exhaust gas emission time, the gas company management platform may use the current target processing efficiency as the expected processing efficiency.

[0135] In some embodiments of this specification, when the remaining processing time is less than or equal to the time threshold, it means that the exhaust gas emission may not be carried out according to the predicted processing efficiency. At this time, it is necessary to adjust the exhaust gas emission efficiency in time to complete the exhaust gas treatment within the specified time.

[0136] In some embodiments, the gas company management platform may determine the expected processing parameters corresponding to a preset time point in the future based on the expected processing efficiency.

[0137] In some embodiments, the gas company management platform adjusts the expected processing parameters in response to the emission risk of exhaust gas emissions from the pipeline to be processed meeting safety conditions.

[0138] Emission risk is a numerical value used to characterize the risk in the waste gas treatment process. For example, the larger the numerical value, the higher the emission risk of the pipeline to be treated. Detailed instructions for determining emission risk can be found in this manual Figure 5 Related description in .

[0139] The safety condition refers to a condition used to determine whether it is safe to discharge exhaust gas. For example, the safety condition may include that the emission risk is not greater than a risk threshold.

[0140] The risk threshold is the threshold used to determine whether the emission risk is too high. For more information on how to determine the risk threshold, see Figure 5 and its related description.

[0141] In some embodiments, the gas company management platform can adjust the expected processing parameters when the emission risk is lower than the risk threshold. For example, the working efficiency of each exhaust gas treatment device is uniformly increased (for example, increasing the speed of the induced draft fan, increasing the opening of the regulating valve, and increasing the power of the filtering device) until the maximum power (or maximum speed, maximum opening). If the current exhaust gas treatment efficiency is still less than the target treatment efficiency, the number of exhaust gas treatment devices in operation is increased (adding induced draft fans or adding filtering devices).

[0142] In some embodiments of this specification, when the emission risk is relatively high, it helps to ensure the safety of waste gas treatment by giving priority to controlling the risk of waste gas emissions and then considering the efficiency of waste gas emissions.

[0143] In some embodiments of this specification, through the cooperation of the gas company management platform and the sensor network platform, the system can obtain the historical monitoring parameter sequence from the smart gas equipment object platform based on the data acquisition cycle when the pipeline to be treated begins to discharge waste gas, and predict the remaining processing time when the monitoring parameters do not meet the preset conditions. The system can also update the target processing efficiency according to the waste gas emission time, the remaining processing time and the environmental characteristics to determine the expected processing efficiency, and further determine the expected processing parameters corresponding to the future preset time point according to the expected processing efficiency, which can further improve the accuracy and real-time performance of waste gas treatment and optimize the overall efficiency of waste gas treatment.

[0144] In some embodiments of this specification, through the collaborative work of the gas company management platform and the gas government safety supervision sensor network platform, the system can determine the standard treatment efficiency based on the exhaust gas emission standards, immediate treatment parameters and exhaust gas characteristics, and obtain the environmental characteristics of the pipeline to be treated from the smart gas government safety supervision management platform. By comprehensively considering the environmental characteristics and standard treatment efficiency, the target treatment efficiency is determined, and further based on the target treatment efficiency, the expected treatment parameters corresponding to the preset time point in the future are determined, which can effectively improve the accuracy and reliability of the exhaust gas treatment process and ensure that the system can maintain an efficient and safe exhaust gas treatment level under various environmental conditions.

[0145] Figure 4 FIG. 1 is a schematic diagram of determining expected treatment parameters based on waste gas treatment time according to some embodiments of this specification. Figure 4 As shown, determining the expected processing parameters based on the exhaust gas processing time may include the following: In some embodiments, determining the expected processing parameters based on the exhaust gas processing time may be performed by a processor of the gas company management platform.

[0146] In some embodiments, the gas company management platform can also determine the amount of waste gas to be treated 430 based on the pipeline parameters 410 and the historical pressure regulation parameter sequence 420; determine the waste gas treatment time 440 based on the waste gas amount to be treated 430 and the target treatment efficiency 360; in response to the waste gas treatment time 440 not satisfying the duration condition 450, determine the expected treatment parameters 370 corresponding to a future preset time point.

[0147] The pipeline parameters are parameters that describe pipeline characteristics and related conditions. For example, the pipeline parameters may include at least one of the diameter of the pipeline, the temperature in the pipeline, and the flow rate of the pipeline gas. The temperature in the pipeline and the flow rate of the pipeline gas can be obtained based on sensors, and the diameter of the pipeline can be obtained based on the specification parameters of the pipeline to be processed.

[0148] The historical pressure regulation parameter sequence represents the pressure of the pipeline to be processed at multiple historical moments before and after the pressure regulation.

[0149] In some embodiments, the gas company management platform can obtain the pipeline parameters of the pipeline to be processed and the historical pressure regulation parameter sequence of a preset historical time period from the smart gas object platform through the gas company sensor network platform.

[0150] The preset historical time period refers to the time period from a certain historical moment to the current moment, and can be set based on prior experience and / or actual needs.

[0151] The amount of waste gas to be treated refers to the volume of waste gas in the pipeline that needs to be treated.

[0152] In some embodiments, the gas company management platform can determine the amount of waste gas to be processed by querying a reference database based on the pipeline parameters of the pipeline to be processed and the historical pressure regulation parameter sequence.

[0153] In some embodiments, the reference database may include a reference feature vector and its corresponding reference exhaust gas volume, wherein the reference feature vector may be constructed based on historical pipeline parameters and historical pressure regulation parameter sequences of multiple historical pipelines to be processed in historical data; and the reference exhaust gas volume may be determined based on the actual exhaust gas treatment volume of the historical pipelines to be processed.

[0154] In some embodiments, the processor can construct a vector to be matched based on the pipeline parameters and the pressure regulating parameter sequence of the pipeline to be processed, and match the vector to be matched in the reference database based on the vector to be matched, and determine the reference feature vector with the highest similarity to the vector to be matched as the target vector; and determine the reference exhaust gas volume corresponding to the target vector as the exhaust gas volume to be processed. The similarity can be calculated based on cosine distance, Euclidean distance, etc.

[0155] In some embodiments, the gas company management platform can also determine at least one reference feature vector whose similarity with the vector to be matched is higher than a similarity threshold, and use the average value of the reference exhaust gas volume corresponding to the aforementioned at least one reference feature vector as the exhaust gas volume to be processed corresponding to the vector to be matched.

[0156] The waste gas treatment time refers to the time required to treat the waste gas in the pipeline. In some embodiments, the waste gas treatment time can be determined based on the amount of waste gas to be treated and the target waste gas treatment efficiency.

[0157] In some embodiments, the gas company management platform can determine the waste gas treatment time based on the amount of waste gas to be treated and the target waste gas treatment efficiency. As an example only, the waste gas treatment time is positively correlated with the amount of waste gas to be treated and negatively correlated with the target waste gas treatment efficiency. The gas company management platform can determine the waste gas treatment time by the following formula (4): (4) Wherein, T represents the waste gas treatment time; V represents the amount of waste gas to be treated; and P represents the target waste gas treatment efficiency.

[0158] In some embodiments, in response to the exhaust gas treatment time not satisfying the duration condition, the gas company management platform may determine the expected treatment parameters corresponding to a preset time point in the future.

[0159] In some embodiments, the duration condition may include a time threshold. For example, the duration condition may be that the exhaust gas treatment time is not greater than the time threshold. The time threshold refers to the maximum value of the set exhaust gas treatment time.

[0160] In some embodiments, the time threshold may be determined based on prior experience and / or actual needs.

[0161] In some embodiments, the gas company management platform may determine the time threshold based on historical exhaust gas treatment time and historical scores.

[0162] Historical exhaust gas treatment time refers to the time spent on the historical exhaust gas treatment process.

[0163] The historical score represents an evaluation of the historical exhaust gas treatment process. The higher the historical score is, the better the effect of exhaust gas treatment based on the historical exhaust gas treatment time is.

[0164] In some embodiments, the gas company management platform can obtain the historical waste gas treatment time and corresponding historical scores of the pipeline to be treated from the smart gas government safety supervision management platform through the smart gas government safety supervision sensor network platform.

[0165] In some embodiments, the gas company management platform can screen the aforementioned historical waste gas treatment time based on the historical score to determine the reference waste gas treatment time. For example, the historical waste gas treatment time whose historical score does not meet the score requirement is eliminated, such as the historical score is less than the minimum threshold, the historical score is ranked in the bottom 30% from large to small, etc.

[0166] In some embodiments, the gas company management platform may determine an average value of the reference exhaust gas treatment time as the time threshold.

[0167] In some embodiments, the time threshold is determined based on the historical exhaust gas treatment time and historical scores, and indicators that are more in line with actual needs can be set to ensure that the exhaust gas treatment meets the expected goal of meeting the exhaust requirements, effectively manage the exhaust gas treatment, and conduct effective cost control to avoid unnecessary investment or unqualified treatment problems.

[0168] In some embodiments, the processor can uniformly increase the working efficiency of each exhaust gas treatment device (for example, increasing the speed of the induced draft fan, increasing the power of the filtering device) until the rated power is reached; if the current exhaust gas treatment time is still greater than the time threshold, the number of exhaust gas treatment devices is increased (for example, adding induced draft fans or adding filtering equipment, etc.).

[0169] In some embodiments, determining the expected processing parameters corresponding to a preset time point in the future helps with advance planning and resource allocation, more timely processing of waste gas in the pipeline, improving the efficiency and accuracy of the processing, and ensuring the orderliness and controllability of the waste gas treatment process.

[0170] Figure 5 Schematic diagram of determining expected processing parameters based on emission risk according to some embodiments of this specification. Figure 5 As shown, determining the expected processing parameters based on the emission risk may include the following: In some embodiments, determining the expected processing parameters based on the emission risk may be performed by a processor of the gas company management platform.

[0171] In some embodiments, Figure 5 As shown, the gas company management platform can evaluate the emission risk 550 of waste gas emissions from the pipeline to be treated through a risk assessment model 540 based on the assessment cycle; the input of the risk assessment model 540 includes at least one of pipeline characteristics 510, immediate processing parameters 320, historical environmental characteristics 520 within a preset historical time period, and historical waste gas characteristics 530 within a preset historical time period.

[0172] For more information on emission risks, immediate processing parameters, and preset historical time periods, see Figure 3 and its related description.

[0173] The pipeline feature refers to a feature related to the properties of the pipeline to be processed. For example, the pipeline feature may include but is not limited to the type of the pipeline to be processed, the adjacency matrix of the pipeline to be processed, etc.

[0174] The type of pipeline to be processed refers to the classification result of the pipeline according to the location and other characteristics of the pipeline to be processed. For example, the type of pipeline to be processed can be a trunk pipeline, a branch pipeline, a branch pipeline, etc.

[0175] The adjacency matrix of the pipeline to be processed refers to a matrix used to describe the connection relationship between each pipeline to be processed in the gas pipeline waste gas treatment system of the Internet of Things.

[0176] In some embodiments, the rows and columns of the adjacency matrix of the pipeline to be processed can respectively represent the pipeline to be processed in the exhaust gas treatment system. Each element of the adjacency matrix indicates whether there is a connection between two pipelines to be processed. For example, when the element in the adjacency matrix is ​​0, it means that there is no connection between the two pipelines to be processed; when the element in the adjacency matrix is ​​1, it means that there is a connection between the two pipelines to be processed.

[0177] In some embodiments, the gas company management platform can obtain the pipeline characteristics of the pipeline to be processed from the smart gas equipment object platform through the gas company sensor network platform.

[0178] The assessment cycle refers to the time interval for assessing the emission risk of exhaust gas emissions from the pipeline to be treated, for example, 1 week.

[0179] In some embodiments, the evaluation period may be set by a professional technician or by system default.

[0180] The historical environmental features refer to parameters composed of environmental features within a preset historical time period. In some embodiments, the historical environmental features can be represented in a sequence. For example, the historical environmental features can be represented by {(t 1 , P 1 ), t 2 , P 2 ),…,(t i , P i ),…,(t n , P n )}. Among them, P i Indicates t i For more information about the preset historical time period, please refer to this manual. Figure 3 Related description in .

[0181] In some embodiments, the gas company management platform can determine the historical environmental characteristics by obtaining historical data on the environmental characteristics of the pipeline to be processed and the time when the environmental characteristics were historically obtained from the smart gas government safety supervision management platform.

[0182] For more information on environmental characteristics, see Figure 3 and its related description.

[0183] Historical exhaust gas characteristics refer to the parameters of exhaust gas characteristics within a preset historical time period.

[0184] In some embodiments, the historical exhaust gas characteristics may be represented in a sequence, similar to the historical environmental characteristics, except that the historical exhaust gas characteristics include exhaust gas characteristics at each moment in a preset historical time period.

[0185] In some embodiments, the gas company management platform may determine the historical exhaust gas characteristics by obtaining the exhaust gas characteristics in the historical data and the time when the exhaust gas characteristics were obtained.

[0186] For more information on exhaust gas characteristics, see Figure 2 and its related description.

[0187] The risk assessment model refers to a model used to assess the emission risk of exhaust gas emission from the pipeline to be treated. In some embodiments, the risk assessment model can be a machine learning model, such as a deep neural network (DNN) model.

[0188] In some embodiments, the input of the risk assessment model may include pipeline characteristics of the pipeline to be treated, instantaneous treatment parameters of the waste gas treatment equipment in the pipeline to be treated, historical environmental characteristics of the pipeline to be treated within a preset historical time period, and historical waste gas characteristics within a preset historical time period. The output of the risk assessment model may be the emission risk of the waste gas emission from the pipeline to be treated.

[0189] In some embodiments, the risk assessment model can be obtained by training based on a large number of first training samples with first labels. The gas company management platform can input multiple first training samples with first labels into the initial risk assessment model, construct a loss function through the first label and the result of the initial risk assessment model, and iteratively update the initial risk assessment model based on the loss function. When the preset conditions are met, the model training is completed and a trained risk assessment model is obtained. Among them, the preset conditions can be that the loss function converges, the number of iterations reaches a threshold, etc.

[0190] In some embodiments, the first training sample can be a sample pipeline characteristic corresponding to a sample pipeline to be processed in historical data, a sample instant processing parameter of a sample exhaust gas treatment device in the sample pipeline to be processed, a sample historical environmental characteristic within a preset historical time period, and a sample historical exhaust gas characteristic within a preset historical time period.

[0191] In some embodiments, the first label may be the emission risk of exhaust gas emission from the sample to be processed pipeline. In some embodiments, the gas company management platform may cluster the first training samples, and count the number of emission accidents in the exhaust gas emission project of the training samples corresponding to each cluster in a subsequent period of time, and divide the number of times by the number of training samples corresponding to the class as the first label corresponding to the sample of the class. The aforementioned subsequent period of time is a time period after the preset historical time period of the sample, which can be determined based on prior experience and / or actual needs; the number of emission accidents refers to the number of adverse events and / or unexpected situations that occur during the exhaust gas emission process.

[0192] In some embodiments, the input to the risk assessment model 540 may also include a temperature sequence 560 for a target period.

[0193] The target period is the time period used to obtain the temperature series, for example, 1 hour.

[0194] The temperature sequence refers to a sequence consisting of the temperature around the pipeline to be processed within the target time period. In some embodiments, the temperature sequence is similar to the construction of the historical environmental features, except that the temperature sequence includes the temperature around the pipeline to be processed at each moment.

[0195] Correspondingly, when the input of the risk assessment model includes the temperature sequence of the target period, the first training sample may further include the temperature sequence of the sample target period based on the above content.

[0196] In some embodiments of this specification, temperature affects the diffusion and transmission rate of exhaust gas. Higher temperature usually accelerates the diffusion rate of gas, causing it to be diluted and dispersed into the surrounding environment faster, thereby affecting the concentration distribution of pollutants and the duration of the peak concentration. Therefore, considering the temperature around the pipeline to be treated when assessing emission risks can improve the accuracy of the risk assessment model.

[0197] In some embodiments, the risk assessment model can be obtained based on training an initial risk assessment model; the training samples used to train the risk assessment model include at least one acquisition classification, and the number of samples in each acquisition classification is greater than the quantity threshold corresponding to the acquisition classification; the quantity threshold is related to the connection information of the gas pipeline in the acquisition classification.

[0198] Collection classification means dividing the sampling area into multiple areas according to longitude and latitude, with each area as a collection classification.

[0199] The quantity threshold refers to a threshold used to characterize whether the amount of training sample data in the collected classification is abundant.

[0200] In some embodiments, each acquisition category corresponds to a quantity threshold.

[0201] For example, the gas company management platform can classify the areas in the sampling area with longitudes between 0 and 10 and latitudes between 0 and 10 as collection category 1, and the corresponding quantity threshold is A; and classify the areas in the sampling area with longitudes between 0 and 10 and latitudes between 10 and 20 as collection category 2, and the corresponding quantity threshold is B.

[0202] In some embodiments, the more complex the connection information of the gas pipeline in the collection classification is, the greater the quantity threshold is. For example, complex connection information refers to the complexity and diversity of the connection relationship between the pipelines to be processed in the exhaust gas treatment system. For example, complex connection information can be that the connection methods between the pipelines to be processed are diverse, or the number of connections is large, etc.

[0203] Connection information is information that characterizes the connection relationship between the pipeline to be processed and other pipelines. Connection information can be represented by the adjacency matrix of the pipeline to be processed in the collection classification. For more information about the adjacency matrix, see Figure 5 Related description above.

[0204] In some embodiments of this specification, the more complex the connection of the pipeline to be processed is, the greater the impact of the exhaust gas on the surrounding pipelines is, and the greater the complexity of the emission risk assessment is. Therefore, by collecting more training samples, the training effect of the risk assessment model can be guaranteed.

[0205] In some embodiments, Figure 5 As shown, the gas company management platform can also determine the expected processing parameters 370 at a future preset time point in response to the emission risk 550 not meeting the safety condition.

[0206] In some embodiments, the gas company management platform can evenly reduce the working efficiency of each exhaust gas treatment equipment (for example, reducing the speed of the induced draft fan, reducing the power of the filtering equipment) until the emission risk is less than the risk threshold.

[0207] In some embodiments, the risk threshold is related to environmental characteristics of the pipeline to be treated.

[0208] For more information on risk thresholds and environmental characteristics, see Figure 3 and its related description.

[0209] In some embodiments, the risk threshold may be negatively correlated with the weighted sum of human flow, traffic congestion index, and air fluidity in the environmental characteristics.

[0210] For more information about the weighted sum of human traffic, traffic congestion index, and air mobility in environmental characteristics, see Figure 3 and its related description.

[0211] In some embodiments of this specification, the greater the weighted sum of the human flow, traffic congestion index, and air fluidity in the environmental characteristics, the more people and vehicles there are near the pipeline to be processed. At this time, appropriately lowering the risk threshold can ensure the safety of the exhaust project.

[0212] In some embodiments of this specification, the pipeline characteristics of the pipeline to be treated are obtained from the smart gas equipment object platform through the gas company management platform and the sensor network platform, which can ensure that the system has detailed information about the pipeline and provide an accurate data basis for subsequent risk assessment. In addition, based on the assessment cycle, the risk assessment model constructed by the machine learning model comprehensively considers pipeline characteristics, immediate processing parameters, historical environmental characteristics, and historical exhaust gas characteristics to assess the emission risk of the pipeline to be treated, which is conducive to improving the accuracy and reliability of the model assessment. When the emission risk is greater than the risk threshold, by determining the expected processing parameters corresponding to the preset time point in the future, the exhaust gas treatment process can be optimized to improve the safety and overall processing efficiency of the exhaust gas treatment.

[0213] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0214] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0215] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0216] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0217] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining the digits. Although the numerical domains and parameters used to confirm the breadth of the range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0218] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification is hereby incorporated by reference in its entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification, documents that limit the broadest scope of the claims of this specification (currently or later attached to this specification) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions, and / or use of terms in this specification shall prevail.

[0219] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A smart gas pipeline waste gas safety treatment system based on the Internet of Things, characterized in that: The system includes a smart gas government safety supervision management platform, a smart gas government safety supervision sensor network platform, a gas company management platform, a gas company sensor network platform and a smart gas equipment object platform; The gas company management platform includes a processor, and the gas company management platform is configured to: Determining the exhaust gas emission standard of the pipeline to be treated based on the exhaust gas treatment level of the pipeline to be treated; In response to the pipeline to be treated starting to discharge waste gas, obtaining real-time processing parameters of the waste gas treatment equipment in the pipeline to be treated from the smart gas equipment object platform through the gas company sensor network platform; Determining an expected treatment parameter corresponding to a preset time point in the future based on at least one of the exhaust emission standard, the immediate treatment parameter, and the exhaust characteristics; An adjustment instruction is generated according to the expected processing parameters, and the adjustment instruction is sent to the smart gas equipment object platform through the gas company sensor network platform to control the smart gas equipment object platform to adjust the processing parameters of the exhaust gas treatment equipment based on the adjustment instruction.

2. The system according to claim 1, characterized in that The gas company management platform is also configured to: Determining a standard treatment efficiency according to the exhaust gas emission standard, the immediate treatment parameter and the exhaust gas characteristics; Obtaining environmental characteristics of the pipeline to be processed from the smart gas government safety supervision management platform through the smart gas government safety supervision sensor network platform; Determining a target processing efficiency according to the environmental characteristics and the standard processing efficiency; The expected processing parameters corresponding to the future preset time point are determined according to the target processing efficiency.

3. The system according to claim 2, characterized in that The gas company management platform is also configured to: Obtaining pipeline parameters of the pipeline to be processed and a historical pressure regulation parameter sequence of a preset historical time period from the smart gas object platform through the gas company sensor network platform; Determining the amount of waste gas to be treated according to the pipeline parameters and the historical pressure regulation parameter sequence; Determining the waste gas treatment time according to the waste gas volume to be treated and the target treatment efficiency; In response to the exhaust gas treatment time not satisfying a duration condition, the expected treatment parameter corresponding to the future preset time point is determined; the duration condition includes a duration threshold.

4. The system according to claim 1, characterized in that The gas company management platform is also configured to: Obtaining the pipeline characteristics of the pipeline to be processed from the smart gas equipment object platform through the gas company sensor network platform; Based on the evaluation cycle, the emission risk of the waste gas emission from the pipeline to be treated is evaluated by a risk assessment model; the input of the risk assessment model includes at least one of the pipeline characteristics, the immediate treatment parameters, the historical environmental characteristics within a preset historical time period, and the historical waste gas characteristics within the preset historical time period, and the risk assessment model is a machine learning model; In response to the emission risk not satisfying a safety condition, determining the expected processing parameter corresponding to the future preset time point; the safety condition includes a risk threshold.

5. The system according to claim 4, characterized in that The risk threshold is related to the environmental characteristics of the pipeline to be processed.

6. A smart gas pipeline waste gas safety treatment method based on the Internet of Things, characterized in that: The method is executed by a processor of a gas company management platform in a gas pipeline exhaust treatment system based on the Internet of Things, and includes: Determining the exhaust gas emission standard of the pipeline to be treated based on the exhaust gas treatment level of the pipeline to be treated; In response to the pipeline to be treated starting to discharge waste gas, obtaining real-time processing parameters of the waste gas treatment equipment in the pipeline to be treated from the smart gas equipment object platform through the gas company sensor network platform; Determining an expected treatment parameter corresponding to a preset time point in the future based on at least one of the exhaust emission standard, the immediate treatment parameter, and the exhaust characteristics; An adjustment instruction is generated according to the expected processing parameters, and the adjustment instruction is sent to the smart gas equipment object platform through the gas company sensor network platform to control the smart gas equipment object platform to adjust the processing parameters of the exhaust gas treatment equipment based on the adjustment instruction.

7. The method according to claim 6, characterized in that The determining of the expected processing parameters corresponding to a preset time point in the future based on at least one of the exhaust emission standard, the immediate processing parameters and the exhaust characteristics includes: Determining a standard treatment efficiency according to the exhaust gas emission standard, the immediate treatment parameter and the exhaust gas characteristics; Obtaining environmental characteristics of the pipeline to be processed from the smart gas government safety supervision management platform through the smart gas government safety supervision sensor network platform; Determining a target processing efficiency according to the environmental characteristics and the standard processing efficiency; The expected processing parameters corresponding to the future preset time point are determined according to the target processing efficiency.

8. The method according to claim 7, characterized in that The determining, according to the target processing efficiency, the expected processing parameter corresponding to the future preset time point includes: Obtaining pipeline parameters of the pipeline to be processed and a historical pressure regulation parameter sequence of a preset historical time period from the smart gas object platform through the gas company sensor network platform; Determining the amount of waste gas to be treated according to the pipeline parameters and the historical pressure regulation parameter sequence; Determining the waste gas treatment time according to the waste gas volume to be treated and the target treatment efficiency; In response to the exhaust gas treatment time not satisfying a duration condition, the expected treatment parameter corresponding to the future preset time point is determined; the duration condition includes a duration threshold.

9. The method according to claim 6, characterized in that The determining of the expected processing parameters corresponding to a preset time point in the future based on at least one of the exhaust emission standard, the immediate processing parameters and the exhaust characteristics includes: Obtaining the pipeline characteristics of the pipeline to be processed from the smart gas equipment object platform through the gas company sensor network platform; Based on the evaluation cycle, the emission risk of the waste gas emission from the pipeline to be treated is evaluated by a risk assessment model; the input of the risk assessment model includes at least one of the pipeline characteristics, the immediate treatment parameters, the historical environmental characteristics within a preset historical time period, and the historical waste gas characteristics within the preset historical time period, and the risk assessment model is a machine learning model; In response to the emission risk not satisfying a safety condition, determining the expected processing parameter corresponding to the future preset time point; the safety condition includes a risk threshold.

10. The method according to claim 9, characterized in that The risk threshold is related to the environmental characteristics of the pipeline to be processed.

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