A method for detecting natural gas flux in a gasification station

Abstract

This invention discloses a method for detecting the natural gas flux in a gasification station. The method involves obtaining the gas flux at the outlet of the gasifier as a first flux value, and obtaining the gas flux value for each of the pipeline devices as a second flux value. The change in the first flux over time is defined as a first change, and the change in each of the second flux values ​​over time is defined as a second change. The method outputs the difference between the second flux and the first flux, as well as the ratio between the first change and the second change. The method collects the difference and ratio results respectively. If the collected difference and ratio results do not meet the standard, it is determined that there is at least one fault between the gasifier and the pipeline device corresponding to the second change. This invention, based on the relationship between the pipeline gas flux and the gasification volume of the gasifier in the gasification station, obtains the gas flux in different areas and detects its changes, ratios, and differences, thereby achieving the detection of the entire gas pipeline system in the gasification station.

Description

Technical Field

[0001] This invention belongs to the field of gas management, and specifically relates to a method for detecting the natural gas flux of a gasification station. Background Technology

[0002] Gas flux refers to the amount of gas passing through a cross-section per unit time, usually expressed in cubic meters per second (m³ / s). 3 / s) or standard cubic meters per hour (Nm 3 The gas supply capacity is represented by / h). This concept is very important in gas transmission and distribution systems because it is directly related to the capacity and efficiency of gas supply.

[0003] Calculating gas flux typically involves factors such as gas velocity, pipe cross-sectional area, and gas density. During gas transmission, the stability of gas flux is crucial for ensuring the continuity and stability of gas supply. Fluctuations or instability in gas flux can lead to insufficient or excessive gas supply, affecting normal user operations.

[0004] To maintain a stable gas flow, gas transmission systems are typically equipped with appropriate regulating devices and monitoring systems for gas management. These devices can monitor gas flow and pressure in real time and make adjustments as needed to ensure a stable gas flow.

[0005] However, in existing technologies, the equipment is usually an independent, single-point detector, which leads to insufficient comprehensive monitoring of the gas management process. For example, in a gasification station, the amount of gas produced by the gasifier directly affects the gas flow in the subsequent pipeline. Detecting the gas flow of only a single device or a section of pipeline may not be sufficient to fully assess the operational status of the entire system, thus creating monitoring loopholes.

[0006] Furthermore, single-point detection methods may fail to detect localized faults or anomalies in the pipeline system in a timely manner, affecting the overall stability of the gas flux. Therefore, a more comprehensive and accurate gas flux monitoring method is needed to improve the stability and reliability of the system. Summary of the Invention

[0007] To address the aforementioned problems, this invention discloses a method for detecting the natural gas flux of a gasification station. The gasification station includes a gasifier and multiple pipeline devices. The method obtains the gas flux at the outlet of the gasifier as a first flux value, obtains the gas flux of each of the pipeline devices as a second flux value, obtains the change of the first flux over time as a first change value, and obtains the change of each of the second flux values ​​over time as a second change value.

[0008] Output the difference between the second flux and the first flux, and the ratio of the first change to the second change;

[0009] The difference and ratio results are collected separately. If the difference and ratio results do not meet the standard, it is determined that there is at least one fault between the gasifier and the pipeline equipment corresponding to the second change.

[0010] In some exemplary embodiments, the difference results and ratio results are obtained, and a curve showing the change of the difference results and ratio results over time is established;

[0011] The fluctuation difference algorithm is used to detect the fluctuation change of the curve. The gas flow value of adjacent time points of the changing curve is differentially calculated. The differential calculation determines whether the fluctuation of the changing curve meets the standard. If it does not meet the standard, the result of the fault is output.

[0012] In some exemplary embodiments, the first throughput, the first change, and several second throughputs and second changes are sent to a terminal, and the terminal performs a result judgment.

[0013] When the terminal outputs the fault result, it screens the location of the fault and identifies the pipeline equipment to be tested corresponding to the difference result or ratio result.

[0014] The terminal determines whether the first flow rate exceeds the limit; if it does, it outputs an error message indicating that the vaporizer is malfunctioning. It also determines whether the second flow rate exceeds the limit; if it does, it outputs an error message indicating that the pipeline equipment under test is malfunctioning.

[0015] If none of them are abnormal, check in turn whether there is a fault in the pipeline equipment between the vaporizer and the pipeline equipment to be tested. If there is a fault, output the corresponding pipeline equipment is abnormal.

[0016] If the adjacent equipment of the pipeline under test is identified as faulty, determine whether the adjacent equipment is unique;

[0017] If there is only one adjacent device, then output the pipeline fault between the tested pipeline device and the adjacent device;

[0018] If the adjacent devices are not unique, obtain the third flux value of each of the adjacent devices, obtain the judgment difference result between the third flux value and the second flux value, and output the pipeline fault between the adjacent device with the largest difference and the pipeline device under test.

[0019] In some exemplary embodiments, the pipeline equipment has a rated throughput, and when the detection result does not output a fault result, the fluctuation range of the ratio result is obtained;

[0020] The endpoints of the fluctuation range are the upper threshold and the lower threshold, respectively. The ratio of the first flux to the upper threshold and the lower threshold at the current time is calculated to obtain the predicted value of the second flux at the next time.

[0021] When the second flux prediction value exceeds the rated flux, the detection result is output as a fault result.

[0022] In some exemplary embodiments, the rate of change of the gas flux of the first flux over a period of time is obtained based on the first change amount;

[0023] Based on the first flux and rate of change at the current moment, predict the predicted value of the first flux at the next moment;

[0024] The second flux prediction value is obtained by predicting the first flux prediction value. If the second flux prediction value exceeds the rated flux of the equipment, the detection result is output as a fault result.

[0025] In some exemplary embodiments, when the detection result does not output a fault result, the absolute value of the difference between the second flux prediction value at the previous moment and the second flux value at the current moment is obtained. If the absolute value exceeds a preset value, a correction parameter is introduced.

[0026] Multiply the shown rate of change by the correction factor to obtain the adjusted rate of change;

[0027] Multiply the upper and lower thresholds by the correction coefficients respectively, and use the adjusted upper and lower thresholds to calculate the first flux at the current time to obtain the corrected ratio result.

[0028] In some exemplary embodiments, the correction system is obtained through the least squares method, specifically including:

[0029] The second flux prediction value and the actual second flux value are respectively curve-fitted using the least squares method;

[0030] Substitute the data into the fitted formula to obtain the correction values ​​for both;

[0031] The predicted flux value and the actual flux value are then subjected to curve fitting again, which are the X and Y values, respectively, to obtain the correction parameters.

[0032] In some exemplary embodiments, the piping equipment includes at least a heater;

[0033] The inlet of the gasifier is connected to a liquefied natural gas storage tank, and the outlet of the gasifier is connected to at least one heater; gas flow detection equipment is provided at the inlet of the pipeline equipment and the outlet of the gasifier.

[0034] The beneficial effect of this invention is that it obtains the gas flow rate at the output end of the gasifier and the pipeline equipment respectively, and based on the relationship between the gas flow rate in the pipeline and the gasification rate of the gasifier in the gasification station, it obtains the gas flow rate in different areas and detects its changes, ratios before and after, and differences, thereby realizing the detection of the overall gas pipeline system in the gasification station.

[0035] For example, by obtaining the ratio and difference results, the location of the fault can be effectively determined. In addition to the area being detected, it is also possible to determine whether there is a fault in the pipeline between two or more detection points through calculation and judgment.

[0036] Furthermore, by acquiring data on changes in gas flow, it is possible to predict the gas flow at the next moment, thereby predicting the occurrence of faults.

[0037] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A method for detecting the natural gas flux of a gasification station according to an embodiment of the present invention is shown.

[0040] Figure 2 A method for detecting the natural gas flux of a gasification station according to an embodiment of the present invention is shown.

[0041] Figure 3 A method for detecting the natural gas flux of a gasification station according to an embodiment of the present invention is shown.

[0042] Figure 4 A method for detecting the natural gas flux of a gasification station according to an embodiment of the present invention is shown.

[0043] Figure 5 A method for detecting the natural gas flux of a gasification station according to an embodiment of the present invention is shown.

[0044] Figure 6 A method for detecting the natural gas flux of a gasification station according to an embodiment of the present invention is shown.

[0045] Figure 7This paper illustrates an application scenario for natural gas flux detection in a gasification station according to an embodiment of the present invention.

[0046] In the attached image:

[0047] 1-Storage tank, 2-Vaporizer, 3-Heater. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] This invention detects gas flow at different locations, with reference to... Figure 1 The gas flow rate at the gasifier outlet is obtained as a first flow rate value, and the gas flow rate value for each pipeline device is obtained as a second flow rate value. The change in the first flow rate over time is also obtained as a first change rate, and the changes in each second flow rate value over time are obtained as second changes rate values. The detection method described in this embodiment can be implemented by sensors or other hardware devices to detect and transmit data to a management terminal. Specific methods for flow rate acquisition are already available in the prior art, and any one of these methods can be used in this embodiment, which will not be elaborated upon here.

[0050] In this embodiment, the difference between the second flux and the first flux, and the ratio of the first change to the second change, are output as detection results. These two results together reflect the relative relationship between the flow state of the gas in the pipeline equipment and the gas flux at the gasifier outlet.

[0051] In this embodiment, the first flux value is set as Q1 and the second flux value is set as Q2. In fact, considering the pressure loss, temperature change and internal friction of the pipeline that may occur during the gas transmission process, the calculation of the difference result needs to introduce the loss influence parameters α and β.

[0052] Calculate the theoretical difference in gas flow between the gasifier outlet and each pipeline equipment:

[0053] ΔQ 实际 =αβ(Q1-ΣQ 2i );

[0054] Where, ΔQ 实际 Q represents the corrected actual difference. 1i It is the gas flow rate at the gasifier outlet, ΣQ2i It is the sum of gas flux at all pipeline equipment locations. α is the parameter representing the impact of gas density changes caused by pressure variations and temperature fluctuations on flux measurement, and β is the impact of internal pipeline friction and other energy losses during transport on gas flux.

[0055] In a specific implementation scenario, tests showed that in the gasification station under these conditions, the value of α ranged from 0.95 to 1.05, and the value of β ranged from 0.90 to 1.00.

[0056] The ratio result needs to further consider the change of gas flux over time. In the process of calculating the ratio, the time factor τ is introduced to consider the dynamics of the change of gas flux, and the stability coefficient γ is introduced to consider the dynamic stability of gas flow.

[0057] The ratio result is calculated as follows:

[0058]

[0059] Where R represents the adjusted rate of change ratio, ΔtQ 1i ΔtQ represents the change in gas flow at the gasifier outlet. 2i τ1 and τ represent the changes in gas flux of each pipeline and equipment. 2i These represent the corresponding time intervals.

[0060] In one specific case, tests showed that γ ranged from 0.80 to 1.20. This coefficient is used to adjust for the impact of the dynamic stability comparison value calculation on the change of gas flux over time.

[0061] The difference and ratio results are collected separately. If the difference and ratio results do not meet the standard, as mentioned above, if the collected difference and ratio results do not meet the preset standard, it indicates that there is a fault between the two detected locations, and it is determined that there is at least one fault between the vaporizer and the pipeline equipment corresponding to the second change.

[0062] In this embodiment, the standard can be a preset range, namely the range of the difference between the second flux and the first flux and the range of the ratio between the first change and the second change; when the ratio or difference does not conform to the standard, the detection result is output as a fault result.

[0063] It's easy to understand that by acquiring and monitoring the gas flow rate and changes of each pipeline component at the vaporizer outlet and downstream, and comparing the gas flow rates of the preceding and following sections of the pipeline, a comprehensive pipeline inspection can be achieved, rather than monitoring individual points. There is a close pipeline relationship between the vaporization rate of the vaporizer and the gas flow rate of the downstream components. By acquiring and monitoring the gas flow rate and changes of each pipeline component at the vaporizer outlet and downstream, and monitoring these changes in real time, a more comprehensive understanding of the pipeline's operation can be obtained.

[0064] The various results described in this embodiment, such as difference results and ratio results, can be output through any display or broadcasting device. The specific implementation of this invention is not limited.

[0065] To better illustrate the embodiments of the present invention, further understanding is required in conjunction with subsequent embodiments.

[0066] First Embodiment

[0067] Based on the foregoing embodiments, this exemplary embodiment discloses a specific judgment method. In this embodiment, the standard judgment is implemented using a differential algorithm, as described above. Figure 2 To understand.

[0068] In this embodiment, abnormal fluctuations in the curve of the difference result indicate a problem with the corresponding pipeline equipment. Specifically, abnormal fluctuations in the difference may suggest a sudden change in gas flow within the pipeline equipment, which could be caused by gas leaks, pipeline blockages, equipment malfunctions, or other reasons. Therefore, abnormal fluctuations in the difference result may indicate a gas leak, pipeline blockage, or other fault between the two test points.

[0069] Similarly, if the ratio of the first change to the second change changes too much, it means that the change in the vaporization rate of the vaporizer differs too much from the gas flow rate in subsequent equipment. For example, the flow rate change rate in the heating tube may differ greatly, or the flow rate in the subsequent pipeline may be changing drastically, while the vaporization rate remains basically unchanged. Conversely, a smaller ratio may also lead to an excessively large change.

[0070] As mentioned above, the fluctuation results can be obtained using a fluctuation differential algorithm. In the gasification station gas flux detection method, the gas flux values ​​at adjacent time points can be differentially calculated. In this embodiment, this can be the fluctuation results of a first flux, a second flux, or a first change and a second change. It is evident that in this embodiment, the differential algorithm is not only applied to a single flux measurement point, but also considers the gas flux at the gasifier outlet and the measurement points of each pipeline equipment, as well as their changes over time.

[0071] In one specific embodiment, the time points are set to consecutive time points t1, t2, ... tn Taking the first flux as an example, the corresponding gas flux is Q. 11 Q 12 …Q 1n .

[0072] Assume ΔQ 1i It is a first-order difference, that is:

[0073] ΔQ 1i =Q 1(i+1) -Q 1i ;

[0074] Among them, Q i Q represents the gas flux at any given point in time. 1i This represents the gas flow rate at the next moment.

[0075] Further calculation of the second-order difference:

[0076] Δ 2 Q 1i =Q 1(i+1) -Q i And so on.

[0077] After calculating the difference values, applying a sliding window averaging method can smooth out short-term fluctuations and reduce false alarms caused by random factors. The window size is set to n, and for any time point Q... i Its average sliding window value is:

[0078]

[0079] To accurately identify abnormal fluctuations, it is necessary to set reasonable thresholds based on historical data. In some cases, the statistical characteristics of changes in gas flux (such as average value, standard deviation, etc.) can be calculated based on past measurement data, and a threshold T can be set accordingly. When the difference value at a certain time point or the average of its sliding window exceeds this threshold, it is considered that an abnormal fluctuation has occurred. Continuing with the first flux as an example:

[0080]

[0081] The threshold T can be adjusted according to specific application scenarios and security requirements to balance sensitivity and false alarm rate. Based on the foregoing, the aforementioned differential algorithm can be implemented using a differential algorithm. First, the first-order difference is calculated, and then, depending on different implementation situations, higher-order differences are set, such as the second-order difference Δ. 2 Q 1i .

[0082] Applying a sliding window average to the difference values ​​yields the smoothed rate of change. Based on the set threshold T, determine whether there are abnormal fluctuations.

[0083] Second Embodiment

[0084] Based on the foregoing embodiments, in one instance, refer to Figure 3 In this exemplary embodiment, the first throughput, the first change, and several second throughputs and second changes are sent to the terminal, and the terminal performs a result judgment.

[0085] The terminal can be a dedicated monitoring system or a computer, or any system capable of analyzing and judging the received data, determining whether the system has a fault based on preset algorithms and rules, and instructing operators to take corresponding maintenance or handling measures.

[0086] When a fault is identified, the location of the fault is screened. The first throughput, the first change, and several second throughputs and second changes are sent to the terminal, which then performs a result judgment. In this embodiment, the terminal processes and analyzes the data to determine whether a system fault exists and to pinpoint the specific location of the fault.

[0087] When the terminal outputs a fault result, it screens the location of the fault and identifies the pipeline equipment to be tested corresponding to the difference or ratio result. In this embodiment, when a fault occurs in the gas transmission system, the terminal can accurately locate the specific pipeline equipment with the problem, so as to carry out subsequent repairs or handling.

[0088] The terminal determines whether the first throughput exceeds the limit; if so, it outputs an error message indicating a vaporizer malfunction. It also determines whether the second throughput exceeds the limit; if so, it outputs an error message indicating a malfunction in the pipeline equipment under test. When performing fault diagnosis, the terminal simultaneously checks whether the throughput exceeds the preset limit and determines whether the vaporizer or pipeline equipment is operating normally.

[0089] If no abnormalities are found, the system sequentially checks whether there is a fault in the pipeline between the vaporizer and the tested pipeline equipment. If a fault is found, the corresponding pipeline equipment is output as faulty. If no flow abnormalities are found, the terminal further checks whether there is a fault between the vaporizer and the pipeline equipment to ensure the stability of the system operation.

[0090] If the adjacent equipment of the pipeline under test is identified as faulty, it is determined whether the adjacent equipment is unique.

[0091] If the adjacent devices are unique, the system outputs the pipeline fault between the tested pipeline device and the adjacent device. If the adjacent devices are not unique, the system obtains the third flux value of each adjacent device, calculates the difference between the third flux value and the second flux value, and outputs the pipeline fault between the adjacent device with the largest difference and the tested pipeline device. Therefore, when the terminal detects a fault in an adjacent device, it can further determine the specific fault location for accurate fault repair.

[0092] Third Embodiment

[0093] Based on the foregoing embodiments, in one example, the pipeline equipment has a rated throughput. For example, the gas throughput of equipment such as the main vaporizer and heater is limited. Limiting the gas throughput of these devices ensures that they operate within the recommended operating range, preventing equipment damage and accidents. The first embodiment described above has already described fault determination by identifying the degree of curve fluctuation; in this embodiment, the rated throughput needs to be detected.

[0094] Therefore, refer to Figure 4 In this exemplary embodiment, the pipeline equipment has a rated throughput, and when the detection result does not output a fault result, the fluctuation range of the ratio result is obtained.

[0095] The endpoints of the fluctuation range are the upper threshold and the lower threshold, respectively. The ratio of the first flux to the upper threshold and the lower threshold at the current time is calculated to obtain the predicted value of the second flux at the next time.

[0096] In one specific embodiment, considering the time-series nature of the gas flux data, this embodiment employs a time-series analysis method for prediction. Specifically, it uses an Autoregressive Moving Average (ARIMA) model or a variant thereof for calculation.

[0097] The basic form of the model can be represented as:

[0098] Q^ t+1 =μ+φ1Q t +φ2Q t-1 +...+φ p Q t-p+1 +θ 1∈t +θ 2∈t-1 +...+θ q∈t-q+1

[0099] Among them, Q^ t+1 Q represents the predicted flux value at the next time step. t This represents the actual flux value at the current moment, μ is a constant term in the model, and φ is the flux value at the current moment. i It is the coefficient of the autoregressive term, θ j It is the coefficient of the moving average term, ∈t This is the error term.

[0100] In the formula, Q t Q t-1 ,...,Q t-p+1 The historical gas flux values ​​are φ1, φ2, ..., φ p This represents the impact of flux at past p time points on the current flux forecast. θ1, θ2, ..., θ q This represents the impact of prediction errors over the past q time steps on the current flux prediction value, ∈ t ,∈ t-1 ,...,∈ t-q+1 This reflects the difference between the actual value and the model prediction.

[0101] When the second flux prediction value exceeds the rated flux, the detection result is output as a fault result.

[0102] In fact, the above exemplary embodiments disclose a predictive detection method based on pipeline flux detection. Therefore, in conjunction with the content of the second exemplary embodiment, the applicant further discloses a third exemplary embodiment.

[0103] Fourth embodiment

[0104] Based on the foregoing embodiments, in one instance, a terminal or other computing device obtains the rate of change of the gas flux of the first flux over a period of time based on the first change amount, and predicts the first flux value for the next time moment based on the first flux and the rate of change at the current moment. In this embodiment, the terminal acquires and processes data sent by various sensors or detection devices.

[0105] refer to Figure 5 To understand this, this embodiment utilizes a terminal or other computing device to predict changes in gas flow, thereby determining whether there are potential faults in the pipeline system. This prediction method is based on analyzing the relationship between the change in the first flow over a past period and time, thus calculating the predicted value of the first flow at the next moment. Based on this predicted value, the change in the second flow is further predicted to determine whether it exceeds the rated capacity of the pipeline equipment, thereby outputting a fault result. The prediction formula can be expressed as:

[0106] Q t+1 =β0+β1·MA(Q) t ,n)+∈;

[0107] Among them, Q t+1 Let β0 be the first flux prediction value at the next time step, β1 be the intercept term of the linear regression model, β1 be the coefficient of the independent variable in the linear regression model, representing the impact of historical flux changes on the predicted value, and ∈ be the error term. MA(Q) tLet (n) be the first flux Q at time t. t The moving average over the past n time points is calculated as follows:

[0108]

[0109] Based on the foregoing, the second flux prediction value is obtained by predicting the first flux prediction value. If the second flux prediction value exceeds the rated flux, the detection result is output as a fault result.

[0110] Fourth exemplary embodiment

[0111] To improve prediction accuracy, based on the third exemplary embodiment, this exemplary embodiment is disclosed. When the detection result does not output a fault result, the absolute value of the difference between the second flux prediction value at the previous moment and the second flux value at the current moment is obtained. If the absolute value exceeds a preset value, a correction parameter is introduced, referencing... Figure 6 To understand.

[0112] The principle of correction parameters is to dynamically adjust the output of the prediction model based on the deviation between historical and current data, thereby adapting to the actual changes in gas flux. When the difference between the predicted and actual values ​​exceeds a preset threshold, it indicates that the model may have failed to accurately capture certain dynamic characteristics of gas flux changes. Therefore, correction parameters need to be introduced to adjust subsequent predictions, thereby improving the accuracy and reliability of the predictions.

[0113] In one specific embodiment, the absolute value of the difference between the predicted second flux value at the previous time step and the actual second flux value at the current time step is calculated and denoted as |ΔQ2|. If this absolute value exceeds a preset value T, a correction parameter K is calculated. The correction parameter K can be dynamically determined based on the magnitude of the difference; for example, it can be set as a function of |ΔQ2| / T to ensure that the correction parameter is proportional to the actual deviation.

[0114] The rate of change and the threshold are adjusted using a correction parameter K. Specifically, the original rate of change R is multiplied by the correction factor K to obtain the adjusted rate of change R′.

[0115] Similarly, the original upper threshold U and lower threshold L are multiplied by the correction factor K to obtain the adjusted upper threshold U′ and lower threshold L′. The adjusted thresholds U′ and L′ are then used to calculate the corrected ratio with the current flux Q1.

[0116] After obtaining the correction parameters, they can be used for adjustment calculations. Multiply the indicated rate of change by the correction coefficient to obtain the adjusted rate of change. Multiply the upper and lower thresholds by the correction coefficients respectively, and use the adjusted upper and lower thresholds to calculate the first flux at the current time to obtain the corrected ratio result.

[0117] In some specific embodiments, it can be implemented through the terminal device.

[0118] The correction is obtained by the least squares method, specifically including:

[0119] Curve fitting is performed on the second flux prediction value and the actual second flux value respectively by the least squares method.

[0120] Curve fitting is performed on the predicted value and the actual value of the second flux. The purpose is to find a function f(x) such that the sum of the squares of the errors between the predicted value and the actual value is minimized.

[0121] Let the predicted value be X = {x1, x2,..., x n}, and the actual value be Y = {y1, y2,..., y n}. Then the least squares method aims to find the parameters a and b. The specific content of the least squares fitting will not be elaborated here.

[0122] Substitute the data into the fitted formula to obtain the correction values of both respectively;

[0123] Curve fitting is performed again on the second flux prediction value and the actual second flux value as the X value and the Y value respectively to obtain the correction parameters.

[0124] After obtaining the correction values of the first fitting, we perform quadratic curve fitting on the second flux prediction value and the actual value again as the X value and the Y value. Solve the parameters a, b, and c of the quadratic equation such that

[0125]

[0126] where, x i and y i are the predicted value and the actual value of the second flux respectively, a, b, and c are parameters, and S is the sum of the squares of the errors.

[0127] The Fifth Embodiment

[0128] Based on the foregoing embodiments, a method for detecting the natural gas flux of a gasification station is disclosed in an example. It is used in a gasification station, and the gasification station includes a gasifier and multiple pipeline devices. The gasifier and the pipeline devices are connected through a gas transmission pipeline.

[0129] For reference Figure 7 For understanding, in this embodiment, the pipeline device at least includes a heater 3, such as Figure 7The situation is illustrated. Each of the vaporizers 2 is connected to at least one heater 3. It is easy to understand that the vaporizers 2, heaters 3, and other equipment all have corresponding detectors or sensors. The inlet of each vaporizer 2 is connected to a liquefied natural gas storage tank 1, and the outlet of each vaporizer 2 is connected to at least one heater 3.

[0130] It should be understood that the detection methods described in the foregoing embodiments can all include simple natural gas flux detection methods, such as conventional gas flux numerical detection, which determines whether the equipment or pipeline is faulty by detecting whether the value exceeds a threshold. This can be achieved using devices such as pressure sensors or flow meters. The aforementioned detection methods can be combined with conventional detection methods without contradicting them.

[0131] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting the gas flow rate of a gasification station, wherein the gasification station includes a gasifier and multiple pipeline devices, characterized in that: The gas flow rate at the gasifier outlet is obtained as a first flow rate value, the gas flow rate of each of the pipeline devices is obtained as a second flow rate value, the change of the first flow rate over time is obtained as a first change, and the change of each of the second flow rate values ​​over time is obtained as a second change. Output the difference between the second flux and the first flux, and the ratio of the first change to the second change; The difference and ratio results are collected separately. If the difference and ratio results do not meet the standard, it is determined that there is at least one fault between the gasifier and the pipeline equipment corresponding to the second change. Obtain the difference and ratio results, and establish the change curves of the difference and ratio results over time; The fluctuation difference algorithm is used to detect the fluctuation change of the curve. The gas flow value of adjacent time points of the change curve is differentially calculated. The difference calculation determines whether the fluctuation of the change curve meets the standard. If it does not meet the standard, the result of the fault is output. The first flux, the first change, and several second fluxes and second changes are sent to the terminal, which performs result judgment; when the terminal outputs a fault result, it screens the location of the fault and identifies the pipeline equipment to be tested corresponding to the difference result or ratio result; the terminal determines whether the first flux exceeds the limit, and if it does, it outputs that the vaporizer is abnormal. Determine whether the second flow rate exceeds the limit; if it does, output that the pipeline equipment under test is abnormal. If no abnormalities are found, sequentially determine whether there is a fault in the pipeline equipment between the vaporizer and the pipeline equipment under test. If there is, output the corresponding pipeline equipment abnormality. If all adjacent equipment faults of the pipeline under test are identified, determine whether the adjacent equipment is unique. If the adjacent equipment is unique, output the pipeline fault between the pipeline equipment under test and the adjacent equipment. If the adjacent equipment is not unique, obtain the third flux value of each of the adjacent equipment, obtain the judgment difference result between the third flux value and the second flux value, and output the pipeline fault between the adjacent equipment with the largest difference and the pipeline equipment under test. The pipeline equipment includes at least a heater; the inlet end of the gasifier is connected to a liquefied natural gas storage tank, and the outlet end of the gasifier is connected to at least one heater; the inlet end of the pipeline equipment and the outlet end of the gasifier are equipped with gas flow detection equipment.

2. The gas flow detection method for a gasification station according to claim 1, characterized in that: The pipeline equipment has a rated throughput. When the detection result does not output a fault result, the fluctuation range of the ratio result is obtained. The endpoints of the fluctuation range are the upper threshold and the lower threshold, respectively. The ratio of the first flux to the upper threshold and the lower threshold at the current time is calculated to obtain the predicted value of the second flux at the next time. When the second flux prediction value exceeds the rated flux, the detection result is output as a fault result.

3. The gas flow detection method for a gasification station according to claim 1, characterized in that: The rate of change of the gas flux of the first flux over a period of time is obtained based on the first change amount; Based on the first flux and rate of change at the current moment, predict the predicted value of the first flux at the next moment; The second flux prediction value is obtained by predicting the first flux prediction value. If the second flux prediction value exceeds the rated flux of the equipment, the detection result is output as a fault result.

4. The gas flow detection method for a gasification station according to claim 2, characterized in that: When no fault result is output in the detection result, the absolute value of the difference between the second flux prediction value at the previous moment and the second flux value at the current moment is obtained. If the absolute value exceeds the preset value, a correction parameter is introduced. Multiply the shown rate of change by the correction factor to obtain the corrected rate of change; Multiply the upper and lower thresholds by the correction coefficients respectively, and use the adjusted upper and lower thresholds to calculate the first flux at the current time to obtain the corrected ratio result.

5. The gas flow detection method for a gasification station according to claim 4, characterized in that: The correction coefficients are obtained using the least squares method, specifically including: The second flux prediction value and the actual second flux value are respectively curve-fitted using the least squares method; Substitute the data into the fitted formula to obtain the correction values ​​for both; The predicted flux value and the actual flux value are then subjected to curve fitting again, which are the X and Y values, respectively, to obtain the correction parameters.

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