Intelligent gas pipe network auxiliary facility dehumidification supervision method, internet of things system and medium

Abstract

The application provides a kind of wisdom gas pipe network auxiliary facility dehumidification supervision method, internet of things system and medium, it is related to gas safety supervision field, the method is executed by the government safety supervision management platform of wisdom gas pipe network auxiliary facility dehumidification supervision internet of things system, the method includes: based on government safety supervision sensing network platform, by government safety supervision object platform, from gas company sensing network platform, the humidity monitoring data that is collected by gas equipment object platform is obtained;Gas equipment object platform includes humidity monitoring component and dehumidification component;Humidity monitoring component is configured to collect humidity monitoring data;Based on humidity monitoring data, the downstream characteristics of gas pipeline, determine dehumidification parameter;Dehumidification parameter is sent to dehumidification component, and dehumidification component is controlled based on dehumidification parameter to carry out self-cleaning.

Description

TECHNICAL FIELD

[0001] The present specification relates to the field of gas safety supervision, and in particular to a smart gas pipe network auxiliary facility dehumidification supervision method, an Internet of Things system, and a medium. BACKGROUND

[0002] Gas pipe humidity has an adverse effect on the safe and reliable operation of auxiliary facilities. For example, high humidity environment can accelerate the rusting of metal components such as gas pipe valves and pressure regulators, leading to a decrease in sealing performance and even gas leakage; long-term moisture in the pressure regulating box may cause water blockage, dust blockage, or ice blockage, affecting gas supply stability; humidity may also cause inaccurate monitoring data, false alarms, and a decrease in communication quality. With the widespread application of gas pipe network systems, the influence of pipe humidity on auxiliary facilities is increasingly concerned. Pipes are usually provided with pipe wells or maintenance rooms to accommodate valves, monitoring components, communication components, and other gas pipe auxiliary facilities. However, the environmental humidity of different pipe areas varies, resulting in different degrees of influence of humidity on auxiliary facilities.

[0003] Therefore, it is necessary to provide a smart gas pipe network auxiliary facility dehumidification supervision Internet of Things system and method, which can determine the dehumidification intensity corresponding to different auxiliary facilities at different times and can perform dehumidification operations on gas pipes. SUMMARY

[0004] The summary includes a smart gas pipe network auxiliary facility dehumidification supervision Internet of Things system, which comprises a government safety supervision management platform, a government safety supervision sensor network platform, a government safety supervision object platform, a gas company sensor network platform, a gas equipment object platform, and a gas maintenance object platform. The gas equipment object platform comprises a humidity monitoring component and a dehumidification component; the humidity monitoring component is configured to collect humidity monitoring data, including at least one of pipe environment humidity and pipe well humidity; the dehumidification component is configured to dehumidify the pipe well; and the gas maintenance object platform comprises a staff interaction device.

[0005] The invention includes a smart gas pipeline network auxiliary facility dehumidification monitoring method, which is executed based on a government safety supervision and management platform, comprising: based on the government safety supervision and management sensing network platform, through the government safety supervision and management object platform, obtaining, from the gas company sensing network platform, the humidity monitoring data collected by the gas equipment object platform; the gas equipment object platform comprises a humidity monitoring component and a dehumidification component; the humidity monitoring component is configured to collect the humidity monitoring data, which comprises at least one of pipeline environment humidity and pipe well humidity; the dehumidification component is configured to dehumidify the pipe well; the gas maintenance object platform comprises an interactive device; based on the humidity monitoring data and downstream characteristics of the gas pipeline, determining dehumidification parameters, which comprise a self-cleaning period of the dehumidification component, and the downstream characteristics comprise a gas usage frequency of downstream gas; sending the dehumidification parameters to the dehumidification component and controlling the dehumidification component to perform self-cleaning based on the dehumidification parameters.

[0006] Beneficial effects: by determining the self-cleaning period of the dehumidification component, the dehumidification component can maintain good condition, which is conducive to subsequent more effective dehumidification and ensures normal use of auxiliary facilities. BRIEF DESCRIPTION OF DRAWINGS

[0007] The present specification will be further illustrated in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, the same numbers represent the same structures, wherein:

[0008] Figure 1 is an exemplary schematic diagram of a smart gas pipeline network auxiliary facility dehumidification monitoring Internet of Things system according to some embodiments of the present specification;

[0009] Figure 2 is an exemplary flowchart of a smart gas pipeline network auxiliary facility dehumidification monitoring method according to some embodiments of the present specification;

[0010] Figure 3 is an exemplary flowchart of determining dehumidification parameters according to some embodiments of the present specification;

[0011] Figure 4 is an exemplary schematic diagram of determining dehumidification parameters according to other embodiments of the present specification. DETAILED DESCRIPTION

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some examples or embodiments of the present specification, and for those skilled in the art, the present specification can also be applied to other similar scenarios without creative labor on the basis of these drawings. Unless it is clear from the language environment or otherwise stated, the same reference numbers in the drawings represent the same structures or operations.

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

[0014] As shown in the specification and claims, unless the context clearly indicates otherwise, the words "one", "a", "an", and / or "the" do not refer to the singular, but can also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements explicitly identified, and these steps and elements do not constitute an exclusive list, and the method or device can also include other steps or elements.

[0015] Flowcharts are used in the present specification to illustrate the operations performed by the system according to the embodiments of the present specification. It should be understood that the preceding or subsequent operations are not necessarily performed in sequence. On the contrary, each step can be processed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or more steps of the operation can be removed from these processes.

[0016] Figure 1 is an exemplary schematic diagram of a smart gas pipeline network auxiliary facility dehumidification monitoring Internet of Things system according to some embodiments of the present specification.

[0017] As Figure 1 shown, in some embodiments, the smart gas pipeline network auxiliary facility dehumidification monitoring Internet of Things system includes a government safety supervision management platform 110, a government safety supervision sensing network platform 120, a government safety supervision object platform 130, a gas company sensing network platform 140, a gas maintenance object platform 150 and a gas equipment object platform 160.

[0018] The government safety supervision management platform 110 refers to the platform for government supervision and management, which can be configured as a processor or a server. In some embodiments, the processor can include one or more sub-processing devices (for example, single-core processing devices, multi-core multi-core processing devices, etc.). For example only, the processor can include a central processing unit (CPU), an application specific integrated circuit (ASIC), etc. or any combination thereof.

[0019] In some embodiments, the government safety supervision and management platform 110 can communicate with the government safety supervision object platform 130 through the government safety supervision sensor network platform 120. For example, the government safety supervision object platform 130 can send humidity monitoring data to the government safety supervision and management platform 110 through the government safety supervision sensor network platform 120. The humidity monitoring data is collected by the gas equipment object platform 160.

[0020] In some embodiments, the government safety supervision and management platform 110 is configured to: obtain humidity monitoring data collected by the gas equipment object platform 160 from the gas company sensor network platform 140 through the government safety supervision object platform 130 based on the government safety supervision sensor network platform 120; determine dehumidification parameters based on the humidity monitoring data and downstream characteristics of the gas pipeline, the dehumidification parameters including the self-cleaning cycle of the dehumidification component, and the downstream characteristics including the gas usage frequency of the downstream gas; send the dehumidification parameters to the dehumidification component, and control the dehumidification component to perform self-cleaning based on the dehumidification parameters.

[0021] In some embodiments, the government safety supervision and management platform 110 is further configured to: acquire terrain data, including altitude; determine the humidity influence coefficient of the well based on the terrain data and humidity monitoring data; and determine dehumidification parameters based on the humidity influence coefficient of the well and the downstream characteristics of the gas pipeline.

[0022] In some embodiments, the government safety supervision and management platform 110 is further configured to: determine the humidity influence coefficient of the well based on the gas transmission parameters of the gas pipeline, terrain data, and humidity monitoring data, using a coefficient determination model; the coefficient determination model is a machine learning model.

[0023] In some embodiments, the government safety supervision and management platform 110 is further configured to: determine humidity monitoring data for future periods based on humidity monitoring data; and determine dehumidification parameters based on humidity monitoring data for future periods and downstream characteristics of the gas pipeline.

[0024] In some embodiments, the government safety supervision and management platform 110 is further configured to: determine the humidity monitoring data for future periods based on humidity monitoring data, characteristics of ancillary facilities, terrain data, consumable types of dehumidifying consumables, gas transmission parameters of gas pipelines, and the last replacement time of dehumidifying consumables, using a humidity prediction model, wherein the humidity prediction model is a machine learning model.

[0025] In some embodiments, the government safety supervision and management platform 110 is further configured to: determine the humidity impact coefficient of the well based on humidity monitoring data for future periods; determine the well importance value based on the downstream characteristics of the gas pipeline; and determine whether there are dehumidifying consumables that need to be replaced in the well based on the humidity impact coefficient, well importance value, and impact threshold.

[0026] In some embodiments, the government safety supervision and management platform 110 is further configured to: determine whether there are dehumidifying consumables that need to be replaced in the well based on the humidity influence coefficient, influence threshold, well importance value, and influence reliability value, wherein the influence reliability value is related to the humidity influence coefficient and the consumable type of the dehumidifying consumables.

[0027] In some embodiments, the government safety supervision and management platform 110 is configured to: obtain humidity monitoring data collected by the gas equipment object platform 160 from the gas company sensor network platform 140 through the government safety supervision object platform 130 based on the government safety supervision sensor network platform 120; determine dehumidification parameters based on the humidity monitoring data and downstream characteristics of the gas pipeline, the dehumidification parameters including the self-cleaning cycle of the dehumidification component, and the downstream characteristics including the gas usage frequency of the downstream gas; send the dehumidification parameters to the dehumidification component, and control the dehumidification component to perform self-cleaning based on the dehumidification parameters.

[0028] The government security supervision sensor network platform 120 refers to a platform for the government to supervise and manage sensor network information, which can be configured as communication equipment or a server.

[0029] In some embodiments, the government security supervision sensor network platform 120 can be used for communication and interaction between the government security supervision management platform 110 and the government security supervision object platform 130.

[0030] The government safety supervision platform 130 refers to a platform that can comprehensively manage gas companies and can be configured as a processor or server.

[0031] In some embodiments, the government safety supervision object platform 130 is communicatively connected to the government safety supervision management platform 110 via the government safety supervision sensor network platform 120, and communicatively connected to the gas maintenance object platform 150 and the gas equipment object platform 160 via the gas company sensor network platform 140. For example, the government safety supervision object platform 130 can send humidity monitoring data to the gas maintenance object platform 150 and dehumidification commands to the gas equipment object platform 160 through the gas company sensor network platform 140.

[0032] The gas company sensor network platform 140 refers to a platform that manages the sensor information of the gas company and can be configured as a communication device or a server. In some embodiments, the gas company sensor network platform 140 can be used for communication interaction between the government safety supervision object platform 130 and the gas maintenance object platform 150 and the gas equipment object platform 160.

[0033] The gas maintenance platform 150 refers to a platform for interaction with gas maintenance personnel, which can be configured as an app client or a server. Gas maintenance personnel refer to those involved in gas maintenance, such as pipeline repairmen and pipeline monitors.

[0034] The gas equipment object platform 160 refers to a functional platform for the gas company to generate sensing information and execute control information, and can be configured as a control component. In some embodiments, the gas equipment object platform 160 may include a humidity monitoring component and a dehumidification component. The humidity monitoring component includes, for example, a humidity sensor for acquiring humidity monitoring data. The dehumidification component may include dehumidification equipment such as a dehumidifier.

[0035] In some embodiments of this specification, the IoT system for monitoring the dehumidification of ancillary facilities of smart gas pipeline networks can form a closed loop of information operation between various functional platforms and operate in a coordinated and regular manner under the unified management of the government's safety supervision and management platform, thereby realizing the informatization and intelligentization of dehumidification of ancillary facilities of smart gas pipeline networks.

[0036] It should be noted that the above description of the intelligent gas pipeline ancillary facility dehumidification monitoring IoT system and its modules is for convenience only and should not limit this specification to the scope of the illustrated embodiments. It is understood that those skilled in the art, after understanding the principles of the system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from these principles. In some embodiments, Figure 1 The government safety supervision and management platform, government safety supervision sensor network platform, government safety supervision object platform, gas company sensor network platform, gas maintenance object platform, and gas equipment object platform disclosed herein can be different modules within a single system, or a single module can implement the functions of two or more of the aforementioned modules. For example, the modules can share a single storage module, or each module can have its own separate storage module. Such variations are all within the scope of protection of this specification.

[0037] Figure 2 This is an exemplary flowchart of a smart gas pipeline ancillary facility dehumidification monitoring method according to some embodiments of this specification. Figure 2 As shown, process 200 includes the following steps. In some embodiments, process 200 may be executed by a government security regulatory management platform.

[0038] Step 210: Obtain humidity monitoring data.

[0039] Humidity monitoring data refers to data obtained by monitoring the humidity of gas pipeline networks. Humidity monitoring data includes at least one of the following: pipeline environmental data and well humidity.

[0040] In some embodiments, gas pipelines are provided with manholes at regular intervals. The manholes are used to house various ancillary facilities, such as valves, monitoring components, communication components, alarm components, pressure and flow regulating equipment, sampling and maintenance components, etc.

[0041] Pipeline ambient humidity refers to the humidity inside the gas pipeline.

[0042] Well humidity refers to the humidity inside the well.

[0043] In some embodiments, the government safety supervision and management platform, based on the government safety supervision sensor network platform, obtains humidity monitoring data from the gas company's sensor network platform through the government safety supervision object platform. The humidity monitoring data is collected by the humidity monitoring component in the gas equipment object platform. For more information on the humidity monitoring component, please refer to [link to relevant documentation]. Figure 1 And related explanations.

[0044] Step 220: Determine dehumidification parameters based on humidity monitoring data and downstream characteristics of the gas pipeline.

[0045] Downstream characteristics of a gas pipeline refer to features related to gas usage by gas users downstream of the pipeline. For example, downstream characteristics of a gas pipeline include at least the frequency of gas usage downstream.

[0046] Downstream gas usage frequency refers to the frequency at which gas users downstream of the gas pipeline use gas.

[0047] In some embodiments, the government safety supervision and management platform obtains downstream characteristics of gas pipelines from the government safety supervision object platform through the government safety supervision sensor network platform.

[0048] Dehumidification parameters refer to the operating parameters of a dehumidification unit when it is dehumidifying. For example, dehumidification parameters include the self-cleaning cycle of at least one dehumidification unit. More information about self-cleaning cycles is provided below.

[0049] In some embodiments, the government safety supervision and management platform constructs a reference vector based on historical humidity monitoring data and downstream characteristics of historical gas pipelines in historical dehumidification control processes with good dehumidification effects. The actual dehumidification parameters of the dehumidification equipment in the historical dehumidification process are determined as the reference labels corresponding to the reference vectors, and a reference vector library is constructed based on multiple reference vectors and reference labels.

[0050] The government's safety supervision and management platform constructs a target vector based on current humidity monitoring data and downstream characteristics of the gas pipeline. It then matches this target vector against a reference vector library to obtain the reference vector with the highest similarity. The reference label corresponding to this reference vector is then determined as the current dehumidification parameter. The similarity can be determined based on vector distance, which includes, but is not limited to, cosine distance.

[0051] In some embodiments, dehumidification parameters also include the self-cleaning strength of the dehumidification components. The government safety supervision and management platform acquires terrain data; based on the terrain data and humidity monitoring data, it determines the humidity influence coefficient of the manhole; based on the humidity influence coefficient of the manhole and the downstream characteristics of the gas pipeline, it determines the dehumidification parameters. See more details... Figure 3 And related explanations.

[0052] In some embodiments, the dehumidification component further includes dehumidification consumables, and the dehumidification parameters also include the dehumidification consumables that need to be replaced. The government safety supervision and management platform determines humidity monitoring data for future periods based on humidity monitoring data; and determines dehumidification parameters based on future humidity monitoring data and downstream characteristics of the gas pipeline. See more details... Figure 4 And related explanations.

[0053] Step 230: Send the dehumidification parameters to the dehumidification component and control the dehumidification component to perform self-cleaning based on the dehumidification parameters.

[0054] In some embodiments, the dehumidification component can perform self-cleaning based on dehumidification parameters.

[0055] For example, the dehumidification component's workflow includes: drawing in humid air via a fan; adsorbing water droplets via dehumidification consumables; and discharging treated, dry air. The dehumidification component can eliminate the adsorbed water droplets through self-cleaning.

[0056] The self-cleaning cycle of a dehumidifier refers to the cycle in which the dehumidifier eliminates adsorbed water droplets through self-cleaning. In some embodiments, the dehumidification parameter also includes the self-cleaning strength of the dehumidifier. The self-cleaning strength of the dehumidifier refers to the power of the dehumidifier to eliminate adsorbed water droplets through self-cleaning.

[0057] In some embodiments, the dehumidifier achieves self-cleaning by heating itself to evaporate the adsorbed water droplets. In this case, the self-cleaning cycle of the dehumidifier is the cycle of heating itself, and the self-cleaning intensity of the dehumidifier is the power of heating itself.

[0058] The above description of the dehumidification component's operating process is for illustrative purposes only. The dehumidification component can dehumidify and self-clean using any feasible method, and this manual does not impose any restrictions on this.

[0059] Some embodiments in this specification, by determining the self-cleaning cycle of the dehumidification component, ensure that the dehumidification component remains in good condition, which is conducive to more effective dehumidification in the future and ensures the normal use of auxiliary facilities.

[0060] It should be noted that the above description of process 200 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to process 200 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0061] Figure 3 This is an exemplary flowchart illustrating the determination of dehumidification parameters according to some embodiments of this specification. Figure 3 As shown, process 300 includes the following steps. In some embodiments, process 300 may be executed by a government security regulatory management platform.

[0062] Step 310: Obtain terrain data.

[0063] Topographic data refers to data related to the terrain at the location of gas pipelines and / or wells. For example, topographic data includes the elevation of the location of gas pipelines and / or wells.

[0064] In some embodiments, the government security supervision and management platform obtains terrain data from the government security supervision object platform through the government security supervision sensor network platform.

[0065] Step 320: Determine the humidity influence coefficient of the well based on topographic data and humidity monitoring data.

[0066] For more information on humidity monitoring data, please see [link / reference]. Figure 2 Related explanations.

[0067] The humidity impact coefficient measures the degree to which current humidity affects auxiliary facilities. The higher the humidity impact coefficient, the more prone the auxiliary facilities are to problems, such as oxidation and corrosion.

[0068] In some embodiments, the government safety supervision and management platform determines the humidity impact coefficient by querying a first preset table based on terrain data and humidity monitoring data.

[0069] The first preset table includes the correspondence between the combination of topographic data and humidity monitoring data and the humidity influence coefficient.

[0070] In some embodiments, for each combination of terrain data and humidity monitoring data, the government safety supervision and management platform calculates the total number of data entries corresponding to that combination in historical data, as well as the number of data entries that malfunction within a subsequent preset time period. The ratio of the number of malfunctioning data entries to the total number of data entries is determined as the humidity impact coefficient corresponding to that combination, thereby obtaining a first preset table. The duration of the preset time period can be set based on experience. Malfunctions include malfunctions of ancillary facilities and pipeline malfunctions caused by adjustments to ancillary facilities.

[0071] In some embodiments, the government safety supervision and management platform determines the humidity influence coefficient of the well based on the gas transmission parameters, terrain data, and humidity monitoring data of the gas pipeline through a coefficient determination model.

[0072] The coefficient determination model is a model used to determine the humidity influence coefficient of a well. In some embodiments, the coefficient determination model is a machine learning model, such as a deep neural network (DNN) model.

[0073] The inputs to the coefficient determination model include gas transmission parameters of the gas pipeline, terrain data, and humidity monitoring data. The output of the coefficient determination model includes the humidity influence coefficient of the well.

[0074] Gas transmission parameters refer to parameters related to the transmission of gas within gas pipelines. For example, gas transmission parameters include gas transmission flow rate and gas transmission temperature.

[0075] In some embodiments, the government safety supervision and management platform, based on the government safety supervision sensor network platform, obtains gas delivery flow rate and gas delivery temperature from the gas company's sensor network platform through the government safety supervision object platform. Specifically, the gas delivery flow rate is collected by a gas flow meter in the gas equipment object platform, and the gas delivery temperature is collected by a temperature sensor in the gas equipment object platform.

[0076] In some embodiments, the government safety supervision and management platform trains a coefficient determination model based on multiple first training samples with first labels. For example, the platform can input multiple first training samples into the initial coefficient determination model, construct a first loss function based on the model's output and the first labels, iteratively update the model's parameters using this loss function, and terminate the iteration when the iteration completion condition is met, thus obtaining the trained coefficient determination model. The iterative update method includes, but is not limited to, gradient descent, and the iteration completion condition can be the convergence of the first loss function or the reaching of a threshold number of iterations.

[0077] The first training sample includes the sample gas delivery parameters of the gas pipeline where the sample well is located or corresponds to, the sample topographic data of the sample well, and the sample humidity monitoring data of the sample well. The first training sample can be obtained based on historical data. The government safety supervision and management platform determines the humidity influence coefficient of the sample well corresponding to the first training sample based on the method for determining the humidity influence coefficient as described above, and uses it as the first label corresponding to the first training sample.

[0078] In some embodiments, the inputs to the coefficient determination model may also include ancillary facility characteristics and humidity monitoring data for future periods.

[0079] Ancillary facility characteristics refer to features related to ancillary facilities. For example, ancillary facility characteristics include the type of ancillary facility. For more information on ancillary facilities, see [link to relevant documentation]. Figure 2 And related explanations.

[0080] For more information on humidity monitoring data for future periods, please see [link / reference]. Figure 4 And related explanations.

[0081] In some embodiments, when the input to the coefficient determination model includes ancillary facility features and humidity monitoring data for future periods, the first training sample is the sample gas delivery parameters of the gas pipeline where the sample well is located or corresponding, the sample terrain data of the sample well, the sample humidity monitoring data of the sample well, the sample ancillary facility features of the sample well, and the sample humidity monitoring data of the sample well in the second historical period, wherein the first historical period is before the second historical period.

[0082] Different manholes contain different auxiliary facilities, and different types of auxiliary facilities have different humidity requirements. In some embodiments of this specification, the influence of the type of auxiliary facilities in the manhole is taken into account when determining the humidity influence coefficient, resulting in a more accurate humidity influence coefficient.

[0083] Some embodiments in this specification determine the humidity influence coefficient based on both the current humidity and the humidity in future periods, which can take into account the impact of future humidity changes on auxiliary facilities, resulting in a more accurate humidity influence coefficient.

[0084] In some embodiments, the government security supervision and management platform verifies the initial model trained on the training set based on the validation set, and tests the initial model that has passed the validation set based on the test set. The initial model that has passed the test set is used as the coefficient to determine the model.

[0085] In some embodiments, the training set is a dataset used to tune the learning parameters of the model during training. Learning parameters include weights, biases, and other parameters. The validation set is a dataset used to tune the hyperparameters of the model during training. Hyperparameters include the number of network layers, the number of network nodes, the number of iterations, and the learning rate, etc. The test set is a dataset used to evaluate the performance of the final model.

[0086] In some embodiments, the government security supervision and management platform divides multiple first training samples with a first label into one of the datasets in the training set, validation set, and test set. The data volumes of the training set, validation set, and test set constitute a first preset ratio.

[0087] The ratio of the amount of data in the training set, validation set, and test set can affect the training effect of the model. In some embodiments, the first preset ratio is 8:1:1.

[0088] There is no data overlap between the training set, validation set, and test set; that is, there is no duplicate sample data contained in the training set, validation set, and test set.

[0089] In some embodiments, different first training samples have different learning rates during the training of the initial model.

[0090] The learning rate reflects the degree of influence of different training samples on model training. In some embodiments, the government safety supervision and management platform adjusts the learning rate of the first training sample based on the maintenance data of the sample's ancillary facilities. The more maintenance data of the sample's ancillary facilities, the higher the learning rate of the first training sample.

[0091] In some embodiments of this specification, cross-validation is used to train coefficients to determine the model, which can improve the stability and accuracy of the model.

[0092] Step 330: Determine the dehumidification parameters based on the humidity influence coefficient of the well and the downstream characteristics of the gas pipeline.

[0093] In some embodiments, the government safety supervision and management platform determines the self-cleaning strength of the dehumidification component based on the humidity influence coefficient of the well, and determines the self-cleaning cycle of the dehumidification component based on the downstream characteristics of the gas pipeline. For example, the higher the humidity influence coefficient of the well, the greater the self-cleaning strength of the dehumidification component; the higher the frequency of gas consumption downstream, the shorter the self-cleaning cycle of the dehumidification component. The government safety supervision and management platform combines the self-cleaning cycle and self-cleaning strength of the dehumidification component to obtain dehumidification parameters.

[0094] When dehumidifier components are not self-cleaned for extended periods, their dehumidification capacity decreases, leading to increased humidity. To ensure the normal operation of auxiliary facilities, dehumidifier components need to self-clean. Some embodiments in this specification adjust the self-cleaning cycle and intensity of the dehumidifier components based on the degree of humidity's impact on auxiliary facilities, enabling different levels of dryness to be maintained for different manholes while saving energy.

[0095] It should be noted that the above description of process 300 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to process 300 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0096] Figure 4 This is an exemplary schematic diagram illustrating the determination of dehumidification parameters according to some embodiments of this specification.

[0097] In some embodiments, the dehumidification assembly further includes dehumidification consumables, and the dehumidification parameters also include dehumidification consumables that need to be replaced.

[0098] Dehumidifiers are used to absorb water droplets from humid air. Types of dehumidifiers include, but are not limited to, desiccant such as silica gel and calcium chloride.

[0099] The ability of dehumidifying consumables to absorb water droplets decreases over time. In order to ensure the dehumidifying capacity of the dehumidifying components, the dehumidifying consumables need to be replaced in a timely manner.

[0100] In some embodiments, such as Figure 4 As shown, the government safety supervision and management platform determines the humidity monitoring data 411 for future periods based on humidity monitoring data 401, and determines the dehumidification parameters 421 based on the humidity monitoring data 411 for future periods and the downstream characteristics of the gas pipeline 412.

[0101] For more information on humidity monitoring data, downstream characteristics of gas pipelines, and dehumidification parameters, please refer to [link to relevant documentation]. Figure 2 Related explanations.

[0102] In some embodiments, the government safety supervision and management platform retrieves humidity monitoring data 411 for future periods from a second preset table based on humidity monitoring data 401.

[0103] The second preset table includes the correspondence between humidity monitoring data 401 and humidity monitoring data 411 for future periods. The second preset table can be constructed based on historical data. In some embodiments, the government security supervision and management platform obtains historical humidity monitoring data at a specific historical point in time and determines the humidity monitoring data for a preset period after that historical point in time as the humidity monitoring data for the future period corresponding to the historical humidity monitoring data. The length of the preset period can be set based on experience.

[0104] In some embodiments, such as Figure 4 As shown, the government safety supervision and management platform determines the humidity monitoring data 411 for future periods based on humidity monitoring data 401, characteristics of ancillary facilities 402, terrain data 403, consumable type of dehumidifying consumables 404, gas transmission parameters of gas pipelines 405, and the last replacement time of dehumidifying consumables 406, through a humidity prediction model 431.

[0105] For more information on the characteristics of ancillary facilities, topographic data, and gas transmission parameters for gas pipelines, please refer to [link / reference]. Figure 3 And related explanations.

[0106] Humidity prediction model 431 is a model used to determine humidity monitoring data 411 for future periods. In some embodiments, humidity prediction model 431 is a machine learning model, such as a deep neural network (DNN) model.

[0107] The inputs to the humidity prediction model 431 include humidity monitoring data 401, auxiliary facility characteristics 402, terrain data 403, dehumidifier consumable type 404, gas pipeline gas transmission parameters 405, and the last replacement time of the dehumidifier consumable 406. The output of the humidity prediction model 431 includes humidity monitoring data 411 for future periods.

[0108] In some embodiments, the government security supervision and management platform obtains the consumable type 404 and the last replacement time 406 of the dehumidifying consumable from the government security supervision object platform based on the government security supervision sensor network platform.

[0109] In some embodiments, the government security supervision and management platform trains a humidity prediction model based on multiple second training samples with second labels. For example, the government security supervision and management platform uses methods such as... Figure 3 The method described above for training coefficients to determine the model is used to train a humidity prediction model. For more information on training coefficients to determine the model, please refer to [link to relevant documentation]. Figure 3 And related explanations.

[0110] The second training sample includes humidity monitoring data of the sample well at the first historical moment, characteristics of sample ancillary facilities in the sample well, sample terrain data, consumable type of sample dehumidifying consumables in the sample well, gas transmission parameters of the gas pipeline where the sample well is located or corresponds, and the last replacement time of the sample dehumidifying consumables in the sample well. The second training sample can be obtained based on historical data. The government safety supervision and management platform can determine the historical humidity monitoring data of the sample well at the second historical moment as the second tag corresponding to the second training sample. The first historical moment is earlier than the second historical moment.

[0111] In some embodiments, the government safety supervision and management platform retrieves information from a third preset table based on humidity monitoring data 411 for future periods and downstream characteristics 412 of the gas pipeline to determine the dehumidifying consumables that need to be replaced.

[0112] The third preset table includes humidity monitoring data 411 for future periods, downstream characteristics of the gas pipeline 412, and the corresponding relationships between the dehumidifiers that need to be replaced. Staff can build the third preset table based on their work experience.

[0113] The government's safety supervision and management platform is based on the dehumidifiers that need to be replaced and through methods such as... Figure 2 , Figure 3 The self-cleaning cycle and self-cleaning intensity of the dehumidification component determined by the method are combined to obtain dehumidification parameter 421.

[0114] Some embodiments in this specification predict humidity monitoring data for future periods and determine the dehumidifying consumables that need to be replaced based on the humidity monitoring data for future periods and the downstream characteristics of the gas pipeline. This allows for timely replacement of dehumidifying consumables before the dehumidification capacity of the dehumidifying components declines, ensuring the normal operation of auxiliary facilities.

[0115] In some embodiments, the government safety supervision and management platform determines the humidity impact coefficient of the well based on humidity monitoring data for future periods; determines the well importance value based on the downstream characteristics of the gas pipeline; and determines whether there are dehumidifying consumables that need to be replaced in the well based on the humidity impact coefficient, well importance value, and impact threshold.

[0116] For more information on the influence of humidity, please refer to [link / reference]. Figure 3 And related explanations.

[0117] In some embodiments, the government safety supervision and management platform determines the humidity impact coefficient of the manhole based on humidity monitoring data for future periods. For example, the government safety supervision and management platform calculates the humidity impact coefficient of the manhole using the following formula (1):

[0118] (1)

[0119] in, Humidity influence coefficient For the future period of pipeline environmental humidity, Given the current humidity level of the pipeline environment, For well humidity in future time periods, The current humidity of the well. This represents the average humidity sensitivity of all ancillary facilities within the well. , is a coefficient. , It can be set based on experience.

[0120] Humidity sensitivity reflects the degree to which ancillary facilities are affected by humidity. The more easily the ancillary facilities are damaged by moisture, the higher their humidity sensitivity.

[0121] In some embodiments, humidity sensitivity can also be determined experimentally. Specifically, researchers can place the auxiliary facility in environments with different humidity levels, obtain the time it takes for the auxiliary facility to be completely corroded and damaged under different humidity levels, construct a humidity-corrosion time curve, and determine the average curvature of the curve as the humidity sensitivity corresponding to that auxiliary facility.

[0122] In some embodiments, the government security supervision and management platform can also be implemented through, for example... Figure 3 The method shown determines the humidity effect coefficient.

[0123] The well importance value indicates the degree of importance of a well. The higher the well importance value, the greater the importance of the well.

[0124] In some embodiments, the well importance value is related to the frequency of downstream gas consumption. The higher the frequency of downstream gas consumption, the greater the well importance value.

[0125] In some embodiments, the well importance value is also related to the facility criticality value of ancillary facilities. The higher the facility criticality value of ancillary facilities, the higher the well importance value.

[0126] Facility key values ​​are used to indicate the importance of ancillary facilities.

[0127] In some embodiments, the facility key value is related to the number of associated downstream branches of the ancillary facility and the historical maintenance timeliness. For example, the facility key value is a weighted sum of the number of associated downstream branches and the historical maintenance timeliness. The weights of the number of associated downstream branches and the historical maintenance timeliness can be set based on experience.

[0128] The number of associated downstream branches refers to the number of downstream gas pipelines affected by ancillary facilities. Government safety supervision and management platforms can determine the number of associated downstream branches of ancillary facilities based on the distribution of gas pipelines.

[0129] Historical maintenance timeliness refers to the timeliness of maintenance performed on ancillary facilities in historical data. In some embodiments, the government safety supervision and management platform can determine historical maintenance timeliness based on the average time between reporting a fault and performing maintenance on multiple ancillary facilities. The larger the average time between reporting a fault and performing maintenance, the smaller the historical maintenance timeliness.

[0130] In some embodiments, the government safety supervision and management platform determines the importance value of a well by weighted summation based on the average of the facility critical values ​​of all ancillary facilities in the well and the gas consumption frequency of downstream gas. The weights for the weighted summation can be set based on experience.

[0131] The impact threshold is a threshold used to determine whether dehumidifier consumables need to be replaced.

[0132] In some embodiments, the impact threshold is related to the type of dehumidifying consumable. Different types of dehumidifying consumables have different water absorption capacities; the stronger the water absorption capacity of the dehumidifying consumable, the greater the impact threshold.

[0133] In some embodiments, the government safety supervision and management platform retrieves the water absorption capacity of the dehumidifying consumable from a fourth preset table based on the consumable type of the dehumidifying consumable, and determines the impact threshold based on the water absorption capacity of the dehumidifying consumable.

[0134] The fourth preset table includes the correspondence between the types of dehumidifying consumables and their water absorption capacity. This fourth preset table can be constructed through experiments.

[0135] The stronger the water absorption capacity of the dehumidifying consumables, the slower the rate of humidity rise in the well, which can ensure the normal operation of the auxiliary facilities for a longer period of time. Therefore, the impact threshold can be appropriately increased.

[0136] In some embodiments, in response to the humidity impact coefficient of the well being greater than the ratio of the impact threshold to the well's importance value, the government safety supervision and management platform determines that the well contains dehumidifier consumables that need to be replaced. Otherwise, the government safety supervision and management platform determines that the well does not contain dehumidifier consumables that need to be replaced.

[0137] In some embodiments, the government safety supervision and management platform determines whether there are dehumidification consumables that need to be replaced in a well based on the humidity impact coefficient, impact threshold, well importance value, and impact reliability value.

[0138] The reliability value represents the reliability of the humidity influence coefficient. In some embodiments, the government safety supervision and management platform calculates the reliability value using the following formula (2):

[0139] (2)

[0140] in, To affect the reliability value, The humidity influence coefficient is determined by the method described in step 320. The humidity influence coefficient is determined by formula (1) as described above. This refers to the water absorption capacity of dehumidifying consumables.

[0141] In some embodiments, in response to the humidity influence coefficient, influence threshold, well importance value, and influence reliability value satisfying the following formula (3), the government safety supervision and management platform determines that there are dehumidifying consumables in the well that need to be replaced. Otherwise, the government safety supervision and management platform determines that there are no dehumidifying consumables in the well that need to be replaced.

[0142] (3)

[0143] in, Humidity influence coefficient To affect the reliability value, To affect the threshold, This is an important value for wellbore. Humidity Influence Coefficient Humidity Influence Coefficient Any one of them, or a weighted sum or average of the two, etc. Some embodiments in this specification can reliably determine whether there are dehumidifying consumables in the well that need to be replaced based on the temperature influence coefficient, which can reduce misjudgment and avoid material waste caused by replacing dehumidifying materials too early, or failure caused by replacing dehumidifying materials too late.

[0144] More critical wells have stricter humidity requirements. Some embodiments in this specification determine whether dehumidifying consumables need to be replaced based on the well's importance value, enabling individual assessments for wells of different importance to ensure that different wells maintain different levels of dryness.

[0145] Some embodiments of this specification also provide a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the intelligent gas pipeline auxiliary facility dehumidification monitoring method described in any of the above embodiments.

[0146] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, 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 and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0147] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0148] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0149] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0150] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates 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 be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0151] For each patent, patent application, patent application publication, and other material such as articles, books, specifications, publications, and documents referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0152] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and are considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A smart gas pipeline network ancillary facility dehumidification monitoring IoT system, characterized in that, This includes the government safety supervision and management platform, the government safety supervision sensor network platform, the government safety supervision object platform, the gas company sensor network platform, the gas equipment object platform, and the gas maintenance object platform; The gas equipment platform includes a humidity monitoring component and a dehumidification component; the humidity monitoring component is configured to collect humidity monitoring data, which includes at least one of pipeline ambient humidity and well humidity; the dehumidification component is configured to dehumidify the well; the gas maintenance platform includes an interactive device; the government safety supervision and management platform is configured as follows: Based on the government safety supervision sensor network platform, the humidity monitoring data collected by the gas equipment object platform is obtained from the gas company sensor network platform through the government safety supervision object platform. Acquire terrain data, including elevation; Based on the gas transmission parameters of the gas pipeline, the terrain data, and the humidity monitoring data, the humidity influence coefficient of the well is determined by a coefficient determination model; the coefficient determination model is a machine learning model. Based on the humidity influence coefficient of the well and the downstream characteristics of the gas pipeline, dehumidification parameters are determined. The dehumidification parameters include the self-cleaning cycle of the dehumidification component, and the downstream characteristics include the frequency of gas consumption downstream. The dehumidification parameters are sent to the dehumidification component, and the dehumidification component is controlled to perform self-cleaning based on the dehumidification parameters.

2. The system according to claim 1, characterized in that, The dehumidification component also includes dehumidification consumables; the dehumidification parameters also include dehumidification consumables that need to be replaced; the government safety supervision and management platform is further configured as follows: Based on the humidity monitoring data, determine the humidity monitoring data for future periods; The dehumidification parameters are determined based on the humidity monitoring data for the future period and the downstream characteristics of the gas pipeline.

3. The system according to claim 1, characterized in that, The government safety supervision sensor network platform is communicatively connected to the government safety supervision management platform and the government safety supervision object platform, respectively; the gas company sensor network platform is communicatively connected to the government safety supervision object platform, the gas maintenance object platform, and the gas equipment object platform, respectively.

4. A method for monitoring the dehumidification of intelligent gas pipeline ancillary facilities, executed on the government safety supervision and management platform of the intelligent gas pipeline ancillary facility dehumidification monitoring IoT system as described in claim 1, characterized in that, The method includes: Based on the government safety supervision sensor network platform, the humidity monitoring data collected by the gas equipment object platform is obtained from the gas company sensor network platform through the government safety supervision object platform; the gas equipment object platform includes a humidity monitoring component and a dehumidification component; the humidity monitoring component is configured to monitor the humidity monitoring data, which includes at least one of pipeline ambient humidity and well humidity; the dehumidification component is configured to dehumidify the well; the gas maintenance object platform includes interactive devices; Acquire terrain data, including elevation; Based on the gas transmission parameters of the gas pipeline, the terrain data, and the humidity monitoring data, the humidity influence coefficient of the well is determined by the coefficient determination model; the coefficient determination model is a machine learning model. Based on the humidity influence coefficient of the well and the downstream characteristics of the gas pipeline, dehumidification parameters are determined. The dehumidification parameters include the self-cleaning cycle of the dehumidification component, and the downstream characteristics include the gas consumption frequency of the downstream gas pipeline. The dehumidification parameters are sent to the dehumidification component, and the dehumidification component is controlled to perform self-cleaning based on the dehumidification parameters.

5. The method according to claim 4, characterized in that, The dehumidification component also includes dehumidification consumables; the dehumidification parameters also include dehumidification consumables that need to be replaced; determining the dehumidification parameters based on the humidity monitoring data and downstream characteristics of the gas pipeline includes: Based on the humidity monitoring data, determine the humidity monitoring data for future periods; The dehumidification parameters are determined based on the humidity monitoring data for the future period and the downstream characteristics of the gas pipeline.

6. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions. When the computer reads the computer instructions from the storage medium, the computer executes the method as described in claim 4.

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