Pipeline management system

Abstract

To provide means capable of monitoring a gas composition obtained by a gas separation device by using a small number of sensors installed.SOLUTION: A pipeline management system includes: a pipeline system 2 to which gas is supplied; a control system 1 for controlling the pipeline system; a gas source; a pipe; a gas separation device 5; a first flow sensor Fs for measuring a flow rate of gas to be supplied to a main supply pipe 4; a second flow sensor Fs1 for measuring a flow rate of generation gas flowing out from the gas separation device; and a first concentration sensor Cs1 for measuring a concentration of the generation gas. The control system includes: a recording section 12 that records measurement data obtained by the first and second flow sensors and the first concentration sensor; and a calculation section 11 that calculates a concentration of a gas flow at a position along supply gas and a flow rate and a concentration of a gas flow at a position downstream of return gas in accordance with a mass balance on the basis of measurement results obtained by the first and second flow sensors and the first concentration sensor.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a pipeline management system that monitors fluid composition and flow rate in a pipeline. [Background technology]

[0002] Hydrogen plays an important role in accelerating decarbonization. One of the implementation strategies for hydrogen is to reuse existing natural gas pipelines as hydrogen pipelines. In particular, Patent Document 1 discloses a method for monitoring hydrogen supply pipelines that is useful for this strategy. However, it is expected that natural gas will continue to be an important energy source in the future to maintain energy security. Therefore, rather than completely reusing natural gas pipelines for hydrogen transportation, a more attractive option would be to inject hydrogen into natural gas pipelines and mix the two.

[0003] The resulting hydrogen and natural gas blend is then transported through pipelines to various end users such as homes, factories, institutions, etc. Some end users require hydrogen-rich fuel while others require natural gas-rich fuel, which ultimately requires the installation of gas separators in the pipelines to separate the blend.

[0004] To ensure that the required gas quality is delivered to end users, it is important to monitor the gas composition upstream and downstream of the gas separation unit. However, given the size of existing pipelines, the significant installation and maintenance costs incurred by additional concentration sensors are of concern. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2023-044745 A [Patent Document 2] JP 2022-015364 A Summary of the Invention [Problem to be solved by the invention]

[0006] Patent Document 2 discloses a method for monitoring the composition of a mixed fluid by installing flow sensors upstream and downstream of a gas mixing point. Instead of installing a concentration sensor, the disclosed method calculates the composition using the measured output of the flow sensor.

[0007] The method disclosed in Patent Document 2 can reduce the monitoring cost in a pipeline with a mixing process, but since the document focuses only on determining the composition for gas mixing, it does not disclose monitoring the concentration for separating gas through a gas separation device.

[0008] The present invention has been made in view of the above problems, and an object of the present invention is to provide a means capable of monitoring the gas composition produced by a gas separation device with a small number of installed sensors. [Means for solving the problem]

[0009] The pipeline management system of this embodiment is a pipeline management system for monitoring a pipeline supplying gas to an end user, comprising a pipeline system through which gas is supplied and a control system for controlling the pipeline system, the pipeline system comprising a gas source, a pipe connected to the gas source, a gas separation device connected to the pipe and separating the gas supplied from the gas source into multiple gas streams, a first flow sensor for measuring the flow rate of gas supplied to a main supply pipe of the pipeline, a second flow sensor for measuring the flow rate of generated gas flowing out of the gas separation device, and a first concentration sensor for measuring the concentration of the generated gas, the control system comprising a recording unit for recording measurement data of the first and second flow sensors and the first concentration sensor, and a calculation unit for calculating, based on the measurement results of the first and second flow sensors and the first concentration sensor, the concentration of the gas stream at a position along the supply gas supplied to the gas separation device, and the flow rate and concentration of the gas stream at a downstream position of the return gas returned from the gas separation device to the main supply pipe according to mass balance. Effect of the Invention

[0010] According to the present invention, by calculating the composition at unmeasured points, it becomes possible to monitor the gas composition produced by a gas separation device with a small number of installed sensors. Further features related to the present invention will become apparent from the description of the present specification and the accompanying drawings. Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 shows an example of a system 1 for monitoring a pipeline 2. [Diagram 2] FIG. 2 is a block diagram showing an example of applying mass balance in a pipeline 2. [Diagram 3] FIG. 2 shows a display of the output of a system 1 monitoring a pipeline 2. [Figure 4] A diagram showing an example of a pipeline 2c monitored by the system 1. [Diagram 5] FIG. 1 shows an example of a system 1b for monitoring a pipeline 2b. [Figure 6] FIG. 13 shows the output of system 1b for detecting anomalous measurements of a flow sensor. [Figure 7] FIG. 13 shows the output of system 1b for detecting anomalous measurements of a concentration sensor. [Figure 8A] A diagram showing time delays in a pipeline. [Figure 8B] FIG. 1B shows the output of system 1b for detecting anomalous measurements of a flow sensor taking into account time delay. [Figure 9] FIG. 13 shows an example of a display output for classifying confidence levels. [Figure 10] FIG. 1B shows an example of a pipeline with a compressor and a turbine monitored by the system 1b. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0013] [Example 1] FIG. 1 is a diagram showing an example of the configuration of a system 1 for monitoring the gas flow rate and composition (concentration) in a pipeline 2 equipped with a plurality of gas separation devices 5.

[0014] (Pipeline 2) In this embodiment, the pipeline management system includes a pipeline 2 through which gas is supplied and a system 1 for controlling the pipeline 2. The pipeline 2 includes a first gas source (Gas 1) and a second gas source (Gas 2), pipes connected to the gas source, and a number of gas separation devices 5 connected to the pipes for separating the gas stream supplied from the gas source into a number of gas streams, and supplies gas to an end user 3 through a network of pipes. In this specification, an end user refers to a person / organization that demands gas at the destination of the gas supply. In the figure, the pipes are represented by lines with arrows indicating the direction of gas flow. Gas 1 and Gas 2 are mixed and supplied to each gas separation device 5 through a main supply pipe 4. Gas 1 and Gas 2 have different compositions, and Gas 1 and Gas 2 have known compositions. For example, Gas 1 can be natural gas and Gas 2 can be pure hydrogen. This embodiment also applies to a pipeline 2 with an additional source of gas with a known composition. The additional gas source can be, for example, a natural gas extraction plant, a hydrogen production plant, a methanation plant, etc.

[0015] (Gas Separator 5) As described above, the pipeline 2 includes a plurality of gas separation apparatuses 5 (hereinafter, also simply referred to as separation apparatuses) including the first gas separation apparatus M_1, the second gas separation apparatus M_2, the third gas separation apparatus M_3, and the Nth gas separation apparatus M_N. In this example, the first separation apparatus M_1 is supplied with a gas flow flowing through the main supply pipe 4, and the separation apparatuses M_2 to M_N are supplied with the generated gas 51 flowing out from the separation apparatus M_1. However, the present invention is not limited to this supply form, and for example, the gas flow flowing through the main supply pipe 4 may be supplied to a plurality of separation apparatuses.

[0016] In general, the gas separator 5 separates the mixed gas supply into two gas streams with different purity. For example, the first gas stream is enriched in gas 1 and the second gas stream is enriched in gas 2. Furthermore, the first gas stream is returned to the pipe network and the second gas stream is either supplied to an end user 3 or consumed by being supplied to another separator 5. The first gas stream returned from one gas separator 5 to the upstream pipe network is hereinafter referred to as return gas 52. The second gas stream exiting the gas separator 5 downstream is hereinafter referred to as product gas 51, and the mixed gas supplied to the separator 5 is hereinafter referred to as feed gas 50. It should be noted that each separator 5 is supplied with a different feed gas 50. The product gas 51 and the return gas 52 all have different flow rates and concentrations.

[0017] (Sensor) The pipeline 2 also includes a number of flow and concentration sensors. The flow sensors measure the flow rate of gas through differential pressure, thermal properties, or other known methods. The concentration sensors may measure gas concentration using gas chromatography, calorimetry, or other known methods. Specifically, as shown in FIG. 1, the pipeline 2 includes a flow sensor Fs that measures the flow rate of gas supplied from a gas source to a main supply pipe 4.

[0018] The pipeline 2 is also provided with a flow rate sensor Fs1 that measures the flow rate of the generated gas 51 flowing out from each gas separation device 5. The pipeline 2 is also provided with a concentration sensor Cs1 that measures the concentration of the generated gas 51. The above-mentioned sensors are included in the elements that constitute a pipeline system including a pipeline to which a gas flow is supplied. Note that, since the composition of the gas source, Gas 1 or Gas 2, is known as described above, a concentration sensor for Gas 1 or Gas 2 is not necessary.

[0019] (System 1) In order to meet end-user requirements for gas quality, the multiple gas separation units 5 in the pipeline 2 must be specifically controlled to produce a product gas 51 that meets a target level of gas purity. Monitoring the gas flow rates and concentrations of the feed gas 50 and the product gas 51 is particularly important in controlling the gas separation units 5.

[0020] As described above, the system 1 monitors the gas and composition in the pipeline 2. The system 1 is connected to the pipeline 2 via a wireless or wired network, and has a calculation unit 11 consisting of a CPU (Central Processing Unit) and a recording unit 12 consisting of a memory. The system 1 can receive and record measurement data of the flow rate sensors Fs, Fs1 and the concentration sensor Cs1 installed in the pipeline 2 via the recording unit 12. The system 1 can visually display the stored measurement data of the flow rate and concentration sensors on the display 14 to enable the user of this embodiment to monitor the gas flow rate and concentration of the gas supplied to the main supply pipe 4, as well as the product gas 51 of each gas separation device 5. The system 1 also enables the calculation of the gas flow rate and concentration at points 111a and 111b upstream of the gas separation device 5 via the calculation unit 11. Note that instead of using sensors, the user of this embodiment can also monitor the gas flow rate and concentration at points 111a and 111b based on calculated conditions.

[0021] (Calculation part 11) Specifically, the calculation unit 11 calculates the concentration at point 111a and the flow rate and concentration at point 111b for each gas separation device 5 using the law of conservation of mass or simply mass balance. The positions of points 111a and 111b of the pipeline 2 are represented by black circles in the figure. Point 111a is located on the pipe through which the feed gas 50 flows. Therefore, the flow rate calculated at point 111a can be used to monitor the flow of the feed gas 50 of the separation device 5. Point 111b is located downstream from the position of the pipe through which the return gas 52 is returned. Therefore, the flow rate and concentration calculated at point 111b can be used to monitor the flow rate and concentration of the gas downstream of the return gas 52 of the separation device 5. Here, each separation device 5 has a corresponding point 111a and point 111b.

[0022] The calculation unit 11 also calculates the concentration and flow rate at point 111c located downstream of the mixing point of gas 1 and gas 2. The calculation unit 11 calculates the gas flow rates and concentrations at points 111a, 111b, and 111c in sequence from the most upstream point to the most downstream point. Thus, in this example, the calculation unit 11 performs calculations in sequence from point 111c located downstream of the joining point of gas 1 and gas 2 to point 111b of the separation device M_N. In general, calculation data at upstream points is required for calculations at downstream points, so it is useful to perform calculations in this order. A common way to evaluate the mass balance is to define a control volume 6 (see FIG. 2). The static overall mass balance of the control volume 6 can be evaluated using equation (1). ΣΣmin = Σmout (1) where min (kg / s) is the flow rate at the inlet of the control volume 6 and m (kg / s) is the flow rate at the outlet of the control volume 6. Since there may be multiple inlets and multiple outlets, equation (1) includes a summation operation (Σ).

[0023] Furthermore, the static mass balance of gas component A in control volume 6 can be defined by equation (2). ΣCin min = ΣCout mout (2) where C (kg / kg) is the concentration of gas component A in the inlet stream and C (kg / kg) is the concentration of gas component A in the outlet stream. In this example, the components of the inlet or outlet stream can be only Gas 1, only Gas 2, or a mixture of Gas 1 and Gas 2.

[0024] FIG. 2 is a block diagram illustrating the evaluation of the mass balance to calculate the conditions at points 111b and 111c.

[0025] (Point 111c) To calculate the flow rate and concentration at point 111c, the calculation unit 11 can define the control volume 6 such that point 111c is located on the outlet side and the inlet flow is a gas source of gas 1 and gas 2. In this example, the control volume 6 (V_0) is defined. By calculating equation (1) for the control volume 6 (V_0) and using the measurement data of the flow sensor Fs of gas 1 and gas 2 as input data, the calculation unit 11 can calculate the flow rate at point 111c. Furthermore, the calculation unit 11 can calculate the concentration at point 111c using equation (2) using the measurement data of the flow sensor Fs of gas 1 and gas 2 and the concentration information of gas 1 and gas 2. As described above, the concentrations of gas 1 and gas 2 are known values ​​and are stored in advance in the recording unit 12.

[0026] (Point 111b) To calculate the condition at point 111b of the separation device 5, the calculation unit 11 can define the control volume 6 so that it surrounds only one separation device 5 and the point 111b is located on the outlet side of the separation device 5. In this example, the calculation unit 11 can define control volumes 6(V_1), 6(V_2), and 6(V_3) to calculate the flow rate and concentration at point 111b of the separation devices M_1, M_2, and M_3, respectively. Although examples of control volumes 6 defined for other points 111b are not shown, the same principle applies. The calculation unit 11 calculates the formulas (1) and (2) for the control volume 6(V_1) and uses the measurement data of the flow rate sensor Fs1 and the concentration sensor Cs1 monitoring the product gas 51 of the separation device M_1 and the flow rate and concentration calculated at point 111c as input data, thereby making it possible to calculate the flow rate and concentration at point 111b of the separation device M_1.

[0027] The calculation unit 11 also calculates the formulas (1) and (2) for the control volume 6 (V_2) and can calculate the flow rate and concentration at point 111b of the separation device M_2 by using the measurement data of the flow rate sensor Fs1 and the concentration sensor Cs1 monitoring the generated gas 51 of the separation device M_2 and the separation device M_1 located upstream of the separation device M_2 as input data. Furthermore, the calculation unit 11 can calculate the flow rate and concentration at point 111b of the separation device M_3 by calculating the formulas (1) and (2) for the control volume 6 (V_3) and using the measurement data of the flow rate sensor Fs1 and the concentration sensor Cs1 monitoring the generated gas 51 of the separation device M_3 and the calculation conditions at point 111b of the upstream separation device M_2 as input data.

[0028] The calculation of the flow rate and concentration at the points 111b of the separators M_4 to M_N is similar to the calculation described for the point 111b of the separator M_3, so further description will be omitted. Except for the calculation of the flow rate and concentration at the point 111b of the separator M_2, the calculation of the conditions at the point 111b of the separator 5 requires calculation data of the upstream points as input data (measurement data of the flow rate sensor Fs1 and the concentration sensor Cs1 monitoring the product gas 51 of the separator M_1 are used as input data for the calculation of the flow rate and concentration at the point 111b of the separator M_2). This relationship emphasizes the importance of the order of calculation by the calculation unit 11, that is, the calculation from the most upstream point to the most downstream point.

[0029] (Point 111a) The production of feed gas 50 is the result of a simple branching of pipe 4 and does not involve mixing or separation of gas components. Therefore, based on material balance, the gas concentration at point 111a is the same as the gas concentration upstream. This can be mathematically expressed in equation (3): C 111a = C upstream (3) Here, C 111a (kg / kg) is the gas concentration at point 111a, C upstream is the gas concentration upstream of point 111a.

[0030] To define the gas concentration upstream of point 111a, the calculation unit 11 can use measured data or previously calculated data. As a first example, the calculation unit 11 can use the calculated concentration at point 111c to calculate equation (3) for calculating the concentration at point 111a of the separation device M_1. upstream As a second example, when calculating the formula (3) for calculating the concentration at the point 111a of the separation device M_2, the calculation unit 11 calculates C using the measurement data of the concentration sensor Cs1 that monitors the generated gas 51 of the separation device M_1. upstream As a third example, when calculating the formula (3) for calculating the concentration at the point 111a of the separation device M_3, the calculation unit 11 may use the calculated concentration at the point 111b of the upstream separation device M_2 to define Cupstream The following calculations of the formula (3) for calculating the concentration at the point 111a of the separation devices M_4 to M_N are similar to the calculation of the concentration at the point 111a of the separation device M_3, so further explanation will be omitted. Note that the measurement data used for calculating the conditions at the points 111a, 111b, and 111c in these calculations are collected by the recording unit 12.

[0031] Overall, by evaluating an equation that takes into account mass balance through the calculation unit 11, i.e., an equation that assumes that the mass of the gas flowing into a certain gas inlet point is equal to the mass of the gas flowing out of that point, and using the measurement outputs of the sensors Fs, Fs1, and Cs1 in the pipeline 2 as input data, the system 1 allows the user of this embodiment to monitor the composition (concentration) of the feed gas 50 without installing a concentration sensor corresponding to the feed gas 50 supplied to each separation device. Here again, it can be emphasized that the calculated concentration in the feed gas guides the user of this embodiment in controlling the operation of the separation device. Similarly, the user of this embodiment can also monitor the flow rate and concentration of the gas downstream of the return gas 52 of the separation device 5 without installing a concentration sensor and a flow rate sensor corresponding to the pipeline 2. Such information can also be useful for controlling the separation device. In summary, the system 1 can monitor multiple separation devices in a pipeline using a smaller number of sensors. This also means that the system 1 can monitor the pipeline 2 with reduced installation and maintenance costs.

[0032] (Monitoring the output of System 1) Figure 3 shows an example display output by the system 1 for monitoring the flow rate and concentration of gas in a pipeline 2. The display output may include a window 100 that visually indicates the location of monitoring points in the pipeline 2 as shown in Figure 3(a). The window 100 is displayed on the display 14 shown in Figure 1. The monitoring points are represented by black circles that include points 111a, 111b, and the locations of sensors Fs, Fs1, and Cs1.

[0033] Through window 100, a user of this embodiment can distinguish whether a monitored point provides measured or calculated data. Furthermore, a user of this embodiment can identify whether the data provided by the monitored point is gas flow rate or concentration. In this example, the user can identify that the monitored point provides flow rate information if connected to the letter F, and provides concentration information if connected to the letter C. Furthermore, the user can know that the monitored point provides measured information if the letter F or C is surrounded by a light gray box with a thin outline (e.g., the box designated A), and that the monitored point provides calculated information if the letter F or C is surrounded by a light gray box with a thick outline (e.g., the box designated B).

[0034] As shown in FIG. 3(b), the visualization of gas flow rates and concentrations at the monitoring points is displayed on a window 200. In this embodiment, the concentration of the feed gas 50 at the separation device 5 (M_2) is displayed as an example. In particular, the window 200 provides multiple time series plots of measured or calculated gas flow rates and concentrations. The measurement information displayed by the system 1 includes at least the time series flow rates of the gas sources (Gas 1, Gas 2), the time series gas flow rate and composition of the product gas 51. The calculated flow rates and concentrations displayed in the window 200 can be collected by the system 1 from the calculation values ​​of the calculation unit 11. Again, these include at least the calculated concentration of the feed gas 50 (point 111a) of the separation device 5 and the flow rate and composition downstream of the return gas (point 111b). This embodiment also applies to a pipeline 2 in which pressure sensors are arranged at the same positions as the flow sensors Fs and Fs1.

[0035] [Example 2] The gas pipeline may also comprise a compressor to maintain the required gas flow in the pipe and a turbine to power the compressor. The turbine uses gas from the pipeline as fuel. These components were not considered in the previous examples. In this example, the system 1 is used to control a pipeline 2c further comprising a compressor and a turbine for the above mentioned purposes. This example will be described focusing only on the differences from example 1.

[0036] Figure 4 shows an example of a pipeline 2c monitored by the system 1. Here, the pipeline 2c is based on the pipeline 2 which further includes a number of compressors 7 and a number of turbines 8. A compressor 7 is always paired with a turbine 8. As mentioned before, this is because the compressor 7 is powered by the turbine 8.

[0037] At the inlet of each turbine 8, a flow sensor Fs3 and a concentration sensor Cs3 are connected to measure the gas flow rate and concentration, respectively. These sensors are necessary for the safe operation and control of the turbines 8. Furthermore, the recording unit 12 can receive and store the data measured by these sensors. The turbines 8 use gas from the pipeline 2c as fuel and finally discharge the spent gas. This process changes the mass balance of the pipeline 2c compared to a pipeline without the turbine 8 and compressor 7. More specifically, the flows upstream and downstream of the turbine 8 and compressor 7 pair change.

[0038] Taking into account the change in mass balance due to the addition of the turbine 8 and the compressor 7, the calculation unit 11 additionally calculates the flow rate and concentration at a plurality of points 111d located downstream of the compressor 7 by mass balance. This also means that the series of calculations performed by the calculation unit 11 additionally includes the calculation of the flow rate and concentration at the point 111d.

[0039] (Point 111d) To calculate the flow rate and concentration at point 111d, the calculation unit 11 can define an control volume 6 that surrounds a pair of turbines 8 and compressors 7 and that has point 111d located on the outlet side. This defines a control volume 6 (V_4) for each pair of turbines 8 and compressors 7. The calculation unit 11 can calculate equation (1) for the control volume 6 (V_4) and calculate the flow rate at point 111d using the measurement data of the flow sensor Fs3 and the calculated flow rate at the upstream point 111b. It should also be noted that due to mass balance, the gas flow rate entering the turbine 8 is equal to the gas flow rate leaving the turbine 8.

[0040] No mixing or separation process of gas components is involved for the compressor 7 and turbine 8. Therefore, due to mass balance, the gas concentration at point 111d will be the same as the upstream gas concentration. This can be mathematically expressed by equation (3a): C 111d = C upstream (3a) Here, C 111d (kg / kg) is the gas concentration at point 111d, C upstream is the gas concentration upstream of point 111d. To define the gas concentration upstream of point 111a, the calculation unit 11 can use measured data or previously calculated data. In this example, the evaluation of equation (3a) can use the calculated concentration at the upstream point 111b. The explanation given above also applies to pipeline 2b equipped with pressure sensors co-located with the flow sensors Fs, Fs1, and Fs3.

[0041] [Example 3] The measured and calculated information provided by the system 1 depends on the measurement output of the flow sensor Fs1 and the concentration sensor Cs1. However, the sensors are generally susceptible to damage, which may result in anomalous measurements. Such measurement anomalies may reduce the reliability of the system 1 if left undetected. This problem is addressed in the present embodiment. FIG. 5 shows a system 1b for monitoring a pipeline 2b. The pipeline 2b in this embodiment further comprises a number of flow sensors Fs2, which are flow sensors measuring the gas flow rate supplied to the end user 3. The flow sensors Fs2 correspond to gas meters installed in homes to measure personal gas consumption and to calculate gas consumption charges.

[0042] The description of this embodiment can also be applied to the pipeline 2b equipped with the compressor 7 and the turbine 8 described in the embodiment 2. The recording unit 12 further receives and records data measured by the flow sensor Fs2. The system 1b further includes an abnormality detection unit 13 for detecting an abnormal sensor measurement value in the pipeline 2b.

[0043] (Abnormality detection unit 13) The abnormality detection unit 13 detects abnormal measurements by the flow sensor Fs1 and the concentration sensor Cs1 that monitor the generated gas 51 supplied to the end user 3. This means that for the pipeline 2b, the abnormality detection range of the abnormality detection unit 13 is from the separation devices M_2 to M_N. First, the details of detection of abnormal measurements by the flow sensor Fs1 will be described, and then the details of detection of abnormal measurements by the concentration sensor Cs1 will be described.

[0044] (Abnormality in flow sensor Fs1) Due to mass balance, it is assumed that the amount of generated gas 51 flowing out from the separation device 5 is the same as the amount of gas supplied to the end user 3 connected to the separation device 5. Based on this principle, the abnormality detection unit 13 detects an abnormality in the flow sensor Fs1 using an error E1 that indicates an error in the measurement data of the flow sensor Fs1 compared with the measurement data of the flow sensor Fs2 connected to the end user 3. Next, a specific processing example for detecting an abnormality in Fs1 using the error E1 will be described.

[0045] First, the anomaly detector 13 calculates the error E1 of the flow sensor Fs1. The anomaly detector 13 can calculate the error E1 (%) at time t, for example, by calculating the absolute percentage error treating the flow to the end user as the actual value. This can be expressed by equation (4). E1t = (|mpg,t-Σmend,t| / Σmend,t)*100 (4) where mpg,t (kg / s) is the flow rate measured by flow sensor Fs1 at time t, and Σmend,t (kg / s) is the sum of the flows measured by flow sensor Fs2 at the same time t. To simplify the calculations, in equation (4) only the measurement data of flow sensor Fs2 of end user 3 that receives the same product gas 51 monitored by flow sensor Fs1 is used.

[0046] Then, the abnormality detection unit 13 determines whether the measurement data by the flow sensor Fs1 is abnormal based on whether the calculated error E1 exceeds a threshold value 122 (see FIG. 6(b)). Specifically, if the error E1 exceeds the threshold value 122, the abnormality detection unit 13 determines that the measurement data is abnormal. In other cases, the abnormality detection unit 13 determines that the measurement data is not abnormal. The threshold value 122 can be defined in advance by the user of this embodiment.

[0047] Finally, the anomaly detection unit 13 can generate a display output to guide the user about the generated judgment. An example of this display output will be described with reference to FIG. 6. The display output includes a plot 300 and a plot 400. One plot 300 and one plot 400 are generated for one determined flow sensor Fs1. In this example, the plot 300 and the plot 400 show the display output of the anomaly detection unit 13 generated after repeating anomaly judgment according to the trend of the flow sensor Fs1 of the separation device M_2 from time t0.

[0048] Plot 300 in Fig. 6(a) shows gas flow on the y-axis and time on the x-axis. Graph 120 shows the trend of the measured data of flow sensor Fs1. Graph 121 shows the trend of the total measured flow by flow sensor Fs2 (equal to Σmend,t in equation (4)). Meanwhile, plot 400 in Fig. 6(b) shows the calculated error E1 of flow sensor Fs1. Also shown in plot 400 is a plot of threshold value 122.

[0049] During the period from t0 to time t1, the error E1 does not exceed the threshold value 122. Therefore, during that period, the abnormality detection unit 13 determines that there is no abnormality in the measurement data of the flow sensor Fs1. On the other hand, after time t1, the calculated error E1 exceeds the threshold value 122. Therefore, the abnormality detection unit 13 determines that the measurement data of the flow sensor Fs1 is abnormal after time t1. The calculated error E1, Σmend, and the determination result by the abnormality detection unit 13 are stored in the recording unit 12.

[0050] (Abnormality in concentration sensor Cs1 for produced gas supplied to end users) Next, the details of detection of a measurement abnormality by the concentration sensor Cs1 in the separation device 5 that supplies gas to the end user 3 will be described. First, the anomaly detection unit 13 generates a correlation plot of flow rate and concentration using the end user's historical flow rate and concentration data. The end user's historical flow rate and concentration data can be stored and updated in advance using the recording unit 12 by the user or vendor of this embodiment. The generated correlation plot shows various ranges of gas flow rates for various concentration ranges. An example of the generated correlation between flow rate and concentration will be described later with reference to FIG. 7.

[0051] Next, the anomaly detector 13 collects the calculated total gas flow rate (=Σmend,t) to the end user 3 at time t, which was previously calculated and stored in the recorder 12 (for clarity, said end user is the end user to which the product gas 51 monitored by the concentration sensor Cs1 is supplied).

[0052] Next, the anomaly detection unit 13 estimates the expected range of the concentration measured by the concentration sensor Cs1 at time t. Specifically, the anomaly detection unit 13 uses the generated correlation plot and the collected total gas flow rate to the end user to estimate the expected range of the concentration measured by the concentration sensor Cs1. An example of this estimation process will also be described later with reference to FIG. 7.

[0053] Finally, the abnormality detection unit 13 judges whether the measurement data by the concentration sensor Cs1 is abnormal. Specifically, the abnormality detection unit 13 judges that the measurement data is not abnormal if the measured concentration is within the range of expected concentrations. Otherwise, the abnormality detection unit 13 judges that the measurement data is abnormal.

[0054] If the measured concentration is determined to be abnormal, the anomaly detection unit 13 can calculate an error E2 of the concentration sensor Cs1, which indicates the error of the measurement data by the concentration sensor Cs1 compared to the expected range of concentrations. The error E2 (%) at time t can be calculated, for example, by treating the average of the expected concentration range as the actual value and calculating the absolute percentage error. This is mathematically expressed in equation (5): E2t = (|Cpg,t-Cexpected,t| / Cexpected,t)*100 (5) where Cpg,t (kg / kg) is the concentration measured by the concentration sensor Cs1 and Cexpected,t (kg / kg) is the average of the expected concentration range at time t. The calculated error E2 is also stored in the recorder 12. Finally, the anomaly detector 13 generates a display output to guide the user of the generated decision.

[0055] FIG. 7 shows an example of a display output by the anomaly detection unit 13 for detecting an anomaly in the concentration sensor Cs1. The display output may include a plot 500 in FIG. 7(a), a plot 600 in FIG. 7(b), and a plot 700 in FIG. 7(c). One plot 500, one plot 600, and one plot 700 may be generated for one determined concentration sensor Cs1. The plot 500 shows gas flow rate on the y-axis and time on the x-axis. The generated correlation plots of flow rate and concentration are represented by graphs 123a and 124a and regions 123 and 124.

[0056] In this example, the graph 123a shows historical gas flow rate data consumed by the end user when the gas concentration of gas 2 in the mixed gas is very high, i.e., the gas 2 concentration is [90%, 100%]. Meanwhile, the graph 124a shows historical flow rate data consumed by the end user when the gas concentration of gas 2 is low, i.e., the gas concentration of gas 2 is [70%, 90%]. Based on the maximum gas flow rate and the minimum gas flow rate of the graph 123a, the anomaly detection unit 13 can generate and display the region 123 showing the flow boundary of the high gas 2 concentration. Similarly, the region 124 is generated and displayed by the anomaly detection unit 13 based on the graph 124a showing the flow boundary of the low gas 2 concentration. By visualizing the generated correlation plot of flow rate and concentration, the user of this example can understand the history of the time series trend of the gas flow rate at different gas 2 concentration levels. The correlation plot may include additional regions such as the gas flow rate trend when the gas 2 concentration is [60%, 70%].

[0057] Plot 500 also includes graph 121', which is a trend of the calculated total gas flow rate of product gas 51 to the end user (which is similar to graph 121 of FIG. 6). By observing plot 500, a user of this embodiment can recognize the expected range of concentrations measured by concentration sensor Cs1. For example, if graph 121' is within region 123, the expected concentration range of gas 2 measured by concentration sensor Cs1 will be within [90%, 100%]. If graph 121' is within region 124, the expected gas 2 concentration range of product gas 51 is within [70, 90%].

[0058] Meanwhile, plot 600 shows concentration values ​​of Gas 2 on the y-axis and time on the x-axis, and further includes a graph 125 which is a trend of Gas 2 concentration based on measurement data by concentration sensor Cs1.

[0059] From time t0 to time t2, the graph 125 is below the gas 2 concentration 90% line. However, the plot 500 shows that the graph 121' is within the region 123 from the same time t0 to time t2. This indicates that the expected gas 2 concentration range is within [90%, 100%]. The anomaly detection unit 13 determines that the measured gas 2 concentration by the concentration sensor Cs1 is abnormal because the measured gas 2 concentration by the concentration sensor Cs1 is outside the expected gas 2 concentration range. On the other hand, after time t2, the graph 125 is above the gas 2 concentration 90% line, which is within the expected concentration range. Therefore, the anomaly detection unit 13 determines that the measurement data by the concentration sensor Cs1 after time t2 is not abnormal. In this way, the correlation plot of the generated flow rate and the concentration is described based on the concentration of gas 2. However, the correlation plot can also be based on gas 1 (or other gas components of the generated gas 51).

[0060] Meanwhile, plot 700 shows the error E2 calculated for the concentration sensor Cs1. Note that the error E2 is calculated only when the measurement data of the concentration sensor Cs1 is determined to be abnormal, so values ​​after time t2 are not displayed. By visualizing this plot, a user of this embodiment can evaluate the error of the measurement data by the concentration sensor Cs1.

[0061] To summarize this embodiment, by displaying the plots 500 and 600, the user of this embodiment can understand the determination of the abnormality detection unit 13 regarding the concentration sensor Cs.

[0062] [Example 4] As already explained, the amount of product gas 51 flowing out of the separation device 5 is expected to be the same as the amount of gas supplied to the end user 3 connected to the separation device 5 due to mass balance. This means that if an increase in product gas 51 flowing out of the separation device 5 is observed at time t, a similar increase in the amount of gas flowing to the end user 3 is expected to be observed at the same time. However, due to the distance between the separation device 5 and the end user 3, the increase in the amount of gas flowing to the end user 3 may be observed later than the increase in product gas 51 flowing out of the separation device 5. This phenomenon is a time delay and can be particularly significant in large pipelines.

[0063] Figure 8A shows an example where there is a time delay in the monitored pipeline, where graph 120a in Figure 8A(a) shows the trend of the measurement data from flow sensor Fs1, and graph 121a shows the trend of the total flow measured by flow sensor Fs2.

[0064] At time t3, graph 120a shows a peak in gas flow, indicating an increase and then decrease in gas flowing in product gas 51. Due to mass balance, gas flowing to the end user should show a similar trend, and graph 121a is expected to show a similar peak at the same time t3. However, due to time delays in the pipeline, graph 121a shows an expected peak in gas flow at time t4, later than t3.

[0065] In the above-described embodiment, the determination by the anomaly detection unit 13 did not take into account the time delay. This may cause a large error E1 that exceeds the threshold value 122, as in the case from time t5 to time t3 in FIG. 8A(b). As a result, the anomaly detection unit 13 may erroneously determine that the measurement data of the generated gas 51 by the flow rate sensor Fs is abnormal. However, the large error E1 that exceeds the threshold value 122 from time t5 to time t3 is actually caused by a time delay and is not a measurement abnormality.

[0066] In this embodiment, the anomaly detection unit 13 can also calculate the error E1 at time t according to equation (4b). E1t = (|mpg,t-Σmend,t+tlay| / Σmend,t+tdelay)*100 (4b) Here, Σmend,t+tlay (kg / s) is the sum of the flow rates measured by the flow sensor Fs2 at time t+tlay. Furthermore, the abnormality detection unit 13 can calculate tdelay(s), for example, using equation (4c). tdelay = L / v (4c) where L is the distance between the flow sensors Fs1 and Fs2, and v is the average velocity in the gas pipe. The information required to evaluate equation (4c) can be stored in the storage unit 12 in advance.

[0067] FIG. 8B shows an example of a display output by the anomaly detection unit 13 taking into account the time delay. In FIG. 8B(a), a graph 120a shows the trend of the measurement data by the flow sensor Fs1 for the generated gas 51. A graph 121b shows the trend of the measurement data by the flow sensor Fs2 for the end user connected to the generated gas 51, taking into account the calculated time delay. At time t3, the peaks of the graphs 120a and 121b coincide, and it can be seen that the time delay is eliminated. Furthermore, as shown in FIG. 8B(b), since the error E1 calculated from time t5 to t3 is below the threshold value 122, it is determined that there is no anomaly. Therefore, inaccurate determination by the anomaly detection unit 13 due to the time delay is avoided.

[0068] [Example 5] Some measurement anomalies are very serious, while others are minor. Major anomalies are much less reliable to monitor than minor anomalies. Also, depending on the scale of the anomaly, the maintenance work by the user of this embodiment may change. By visualizing the errors E1 and E2, the user of this embodiment can evaluate the scale of the anomaly of the sensor in the monitored pipeline. However, displaying all plots of the errors E1 and E2 may place a heavy load on the CPU. Furthermore, the previous embodiment did not evaluate the impact of the sensor measurement anomaly on the calculation data by the calculation unit 11. This embodiment addresses these issues. Note that the present embodiment will also be described with a focus on the differences from the previous embodiment.

[0069] In this embodiment, the anomaly detection unit 13 based on the embodiment 3 or embodiment 4 further classifies the reliability levels of the sensors and the calculation data by the calculation unit 11 based on the calculated errors E1 and E2. Specifically, the anomaly detection unit 13 calculates a weighted error Ew based on the errors E1 and E2 to classify the reliability of the measurements at the sensors Fs1, Cs1 and the points 111a and 111b.

[0070] More specifically, the abnormality detection unit 13 calculates the weighted errors Ew (%) of the flow rate sensor Fs1 and the concentration sensor Cs1 using equations (6a) and (6b), respectively. Ew_Fs1 = wE1 (6a) Ew_Cs1 = wE2 (6b) where E1 is the calculated error E1 of Fs1, E2 (%) is the calculated error E2 of Cs1, and w is the weighting factor assigned to the error E1 or E2. In equations (6a) and (6b), w is set to 1.

[0071] The abnormality detection unit 13 also calculates the weighted error Ew (%) of the calculated flow rate at the point 111b using the formula (6c). Ew_F = ΣwEw_Fs1 (6c) where Ew_Fs1(%) is the weighted error Ew calculated for the flow sensor Fs1 located upstream of the calculation point 111b, while w is the weighting fraction assigned to Ew_Fs1.

[0072] Furthermore, the anomaly detection unit 13 calculates the weighted error Ew (%) of the calculated concentration at the point 111a or 111b using the formula (6d). Ew_C = ΣwεEw_Fs1 - ΣwEw_Cs1 (6d) Here, Ew_Fs1 / Ew_Cs1 (%) is the weighted error Ew calculated for the flow sensor Fs1 / concentration sensor Cs1 located upstream of said point 111a or 111b, and w is the weighting portion assigned to the error Ew_Fs1 / Ew_Cs1.

[0073] In equations (6c) and (6d), the weighting portion w is assigned so that the errors used to evaluate the equations have equal weighting. For example, if four Ew values ​​are used to evaluate equation (6c) (or (6d)), w is assigned as 0.25.

[0074] Overall, a larger weighted error Ew indicates greater anomalies and lower reliability. The anomaly detection unit 13 then uses the calculated Ew to proceed to classify the reliability levels of the monitoring points in the pipeline 2b. Specifically, the anomaly detection unit 13 classifies the reliability levels as either "high", "medium", or "low" reliability.

[0075] For example, if the calculated weighted error Ew is within a low error range a, the confidence level is classified as high, if the calculated weighted error Ew is within a medium error range b, the confidence level is classified as medium, and if the calculated weighted error Ew is within a high error range c, the confidence level is classified as low.

[0076] The error ranges a, b, and c are defined so as not to overlap each other. This allows for clear classification of confidence levels as high, medium, or low only. For example, the error range a can be defined as [0%, 10%], the error range b as [10%, 30%], and the error range c as [30%, 100%]. The values ​​of the ranges a, b, and c can be predefined by the user or vendor of this embodiment. The anomaly detection unit 13 further generates a display output to guide the user of this embodiment about the result of the confidence level classification.

[0077] 9 shows an example of a display output of the anomaly detection unit 13 that visualizes the reliability classification at time t. The display output includes a window 100b displayed on the display 14 (see FIG. 1, etc.). The components of the display output are similar to the components of the window 100 described with reference to FIG.

[0078] The difference between window 100 and window 100b is that window 100b adds a visualization of the confidence scale divided into high, medium and low. The confidence scale is designed with different colors for high, medium and low. In this example, "high" confidence is represented by vertical hatching, "medium" confidence by horizontal hatching and "low" confidence by diagonal hatching. Also displayed are the error range values ​​for high, medium and low confidence levels.

[0079] By observing this display output, the user of this embodiment can quickly evaluate the current reliability level of the measured data of the sensors in the pipeline 2b and the calculated data by the calculation unit 11. For example, if a monitoring point is connected to a rectangle with diagonal hatching, the user can evaluate that the current reliability of the measured / calculated flow rate / concentration at that monitoring point is low, with a weighted error within 30-100%. As a result, the user can plan maintenance or control actions to address the low reliability at said monitoring point. Furthermore, the user can determine which data to trust when monitoring the pipeline 2b. For monitoring points with unclassified reliability, the rectangle is shaded.

[0080] [Example 6] As mentioned above, the system 1b can also be used to monitor a pipeline 2b that includes a compressor 7 and a turbine 8. Figure 10 is an example of such a pipeline. In this embodiment, the anomaly detection unit 13 detects measurement anomalies and classifies the reliability level by further using the measurement data of the concentration sensor Cs3 connected upstream of the turbine 8. This is expected to improve the accuracy of anomaly detection and reliability classification.

[0081] Due to the mass balance around the control volume V_5 (FIG. 10), the gas concentration at point 111b should be the same as the gas concentration fed to the turbine 8. This means that the calculated concentration at point 111b should be the same as the measured concentration. Using this relationship, the anomaly detection unit 13 further calculates an error E3 at point 111b. The error E3 indicates the error of the calculated concentration at point 111b compared to the measurement data of the concentration sensor Cs3 monitoring the turbine 8 downstream of point 111b. The anomaly detection unit can calculate the error E3 (%) of the point 111b using the absolute percentage error, with the measurement data of the concentration sensor Cs3 being the actual measurement value.

[0082] (Anomaly detection) From here on, details of additionally using the error E3 to detect an abnormality in the flow sensor Fs1 will be described. In the above-described embodiment, the abnormality detection unit 13 checks whether the calculated error E1 exceeds the threshold value 122 to determine whether the measurement data obtained by the flow sensor Fs1 is abnormal. In this embodiment, the abnormality detection unit 13 further checks whether the error E3 at the upstream point 111b of the flow sensor Fs1 exceeds a threshold value 122b to determine whether the measurement data by the flow sensor Fs1 is abnormal. Specifically, when the error E1 exceeds the threshold value 122 or when the error E3 at the upstream point 111b of the flow sensor Fs1 exceeds the threshold value 122b, the abnormality detection unit 13 determines that the measurement data of the flow sensor Fs1 is abnormal. In other cases, the abnormality detection unit 13 determines that the measurement data is not abnormal.

[0083] In the above-described embodiment, the abnormality detection unit 13 determines whether the measurement data of the concentration sensor Cs1 is abnormal based on whether the measurement data of the concentration sensor Cs1 exceeds an expected concentration range. On the other hand, in this embodiment, the abnormality detection unit 13 further checks whether the error E3 of the point 111b upstream of the concentration sensor Cs1 exceeds the threshold value 122c, thereby determining whether the measurement data by the concentration sensor Cs1 is abnormal. Specifically, the abnormality detection unit 13 determines that the measurement data of the concentration sensor Cs1 is abnormal when the measurement data of the concentration sensor Cs1 exceeds the expected concentration range or when the error E3 of any point 111b upstream of the concentration sensor Cs1 exceeds the threshold value 122c. In other cases, the abnormality detection unit 13 determines that the measurement data is not abnormal. The threshold values ​​122b and 122c can be defined in advance by the user of this embodiment.

[0084] By adding the error E3, the anomaly detection unit 13 can detect measurement anomalies that could not be detected by only the error E1 or the flow rate vs. concentration correlation plot. Furthermore, in the above-mentioned embodiment, the anomaly detection unit 13 can detect only anomalies in the flow rate sensor Fs1 and the concentration sensor Cs1 that monitor the generated gas 51 supplied to the end user 3. This limits the anomaly detection of the separation devices M_2 to M_N. By using the error E3 for anomaly detection, the anomaly detection unit 13 can detect anomalies in the flow rate sensor Fs1 and the concentration sensor Cs1 even in the separation device M_1.

[0085] (Confidence Level) The weighted error Ew of the flow sensor Fs1 and the concentration sensor Cs1 is calculated by using the equations (7a) and (7b), respectively. Ew_Fs1 = wE1 + ΣwE3ε (7a) Ew_Cs1 = wE2 + ΣwE3ε (7b) Here, E3 (%) is the error E3 at the point 111b upstream of the flow sensor Fs1 or the concentration sensor Cs1. Since there may be multiple points 111b upstream of the flow sensor Fs1 or the concentration sensor Cs1, an addition operation is performed on the error E3. By adding the error E3, the accuracy of the reliability classification can be improved. Furthermore, the classification range of the reliability level can be expanded.

[0086] According to the embodiment of the present invention described above, the following advantageous effects are obtained. (1) A pipeline management system according to the present invention is a pipeline management system for monitoring a pipeline supplying gas to an end user, comprising: a pipeline system to which gas is supplied; and a control system for controlling the pipeline system, the pipeline system comprising: a gas source; a pipe connected to the gas source; a gas separation device connected to the pipe and separating the gas supplied from the gas source into multiple gas streams; a first flow sensor for measuring the flow rate of gas supplied to a main supply pipe of the pipeline; a second flow sensor for measuring the flow rate of generated gas flowing out from the gas separation device; and a first concentration sensor for measuring the concentration of the generated gas, the control system comprising: a recording unit for recording measurement data of the first and second flow sensors and the first concentration sensor; and a calculation unit for calculating, based on the measurement results of the first and second flow sensors and the first concentration sensor, the concentration of the gas stream at a position along the supply gas supplied to the gas separation device, and the flow rate and concentration of the gas stream at a downstream position of the return gas returned from the gas separation device to the main supply pipe according to mass balance.

[0087] With the above configuration, it becomes possible to monitor the gas composition in the gas separation device with a small number of sensors installed by calculating the composition at unmeasured points.

[0088] (2) The pipeline system further includes a compressor for maintaining the flow of gas in the pipeline, a turbine for supplying power to the compressor, and a third flow rate sensor and a second concentration sensor for measuring the flow rate and concentration of gas supplied to the turbine, the recording unit is further configured to record measurement data of the third flow rate sensor and the second concentration sensor, and the calculation unit is further configured to calculate the flow rate and concentration of the gas flow downstream of the compressor based on the measurement results of the third flow rate sensor and the second concentration sensor. In this way, compressors and turbines are often installed in pipelines, but by applying the present invention, it becomes possible to monitor the gas composition without increasing the number of sensors installed even if the number of compressors and turbines increases.

[0089] (3) The pipeline system further includes a pressure sensor at the same position as the first flow sensor and / or the second flow sensor, and the recording unit is further configured to record measurement data of the pressure sensor, which makes it possible to more accurately measure the gas composition using the measurement data of the pressure sensor as well.

[0090] (4) The control system further includes an anomaly detection unit that detects an anomaly in the gas flow flowing through the pipeline, the pipeline system further including a fourth flow sensor that measures a gas flow rate of the produced gas at the end user, and the recording unit is further configured to record measurement data of the fourth flow sensor, and the anomaly detection unit determines a measurement anomaly by a second flow sensor that measures the flow rate of the produced gas based on whether a first error of the measurement data of the second flow sensor compared to a sum of measurement data of a fourth flow sensor that measures the flow rate of the same produced gas at the end user exceeds a threshold value, generates a measurement anomaly by a first concentration sensor that measures the flow rate of the produced gas from the gas separation device based on historical flow rate and concentration data of the end user, estimates an expected concentration range of the produced gas using the generated correlation plot and a sum of the measurement data of a fourth flow sensor that measures the flow rate of the same produced gas at the end user, and determines whether the measurement data of the first concentration sensor is outside the expected concentration range and calculates a second error of the measurement data of the first concentration sensor compared to the expected concentration range of the concentration sensor that measures the flow of the produced gas from the gas separation device. This allows accurate prediction of the sensor measurement error based on data already calculated or based on data actually obtained in the past.

[0091] (5) The anomaly detection unit is further configured to calculate a time delay of the pipeline, and the calculated time delay is further used in the calculation of the first error for anomaly detection. As the distance of the pipeline increases, the distance between the sensors increases, and the time delay becomes an issue. Therefore, it is necessary to perform an error calculation that takes the time delay into account in this way.

[0092] (6) The anomaly detection unit is further configured to classify the reliability levels of the measurement data of the first, second, and third flow rate sensors and the first concentration sensor in the pipeline and the calculation data by the calculation unit based on the first error. This makes it possible to determine the reliability based on the error and appropriately select maintenance measures, etc. according to the reliability.

[0093] (7) The pipeline system further includes a compressor for maintaining a flow of the gas flow in the pipeline, a turbine for powering the compressor, and a third flow rate sensor and a second concentration sensor for measuring the flow rate and concentration of the gas supplied to the turbine, and the abnormality detection unit further calculates a third calculated error in the downstream of the return gas compared with measurement data of a second concentration sensor of the turbine located downstream of the return gas, and classifies the reliability level based on the third error in addition to the first error. This increases the number of judgment criteria, making it possible to judge the reliability more accurately.

[0094] The present invention is not limited to the above-described embodiments, and various modifications are possible. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to an embodiment having all of the configurations described. It is also possible to replace a part of the configuration of one embodiment with the configuration of another embodiment. It is also possible to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to delete a part of the configuration of each embodiment, or to add or replace another configuration. [Explanation of symbols]

[0095] 1 Pipeline management system, 2 Pipeline, 4 Main supply pipe, 5 Gas separation device, 7 Compressor, 8 Turbine, 11 Calculation unit, 12 Recording unit, 13 Anomaly detection unit, Fs, Fs1, Fs2, Fs3 Flow rate sensors, Cs1, Cs3 Concentration sensors

Claims

1. A pipeline management system for monitoring a pipeline supplying gas to an end user, the pipeline management system comprising: a pipeline system through which the gas is supplied; and a control system for controlling the pipeline system, The pipeline system includes a gas source, a pipe connected to the gas source, a gas separation device connected to the pipe and configured to separate gas supplied from the gas source into a plurality of gas streams, a first flow sensor for measuring a flow rate of gas supplied to a main supply pipe of the pipeline, a second flow sensor for measuring a flow rate of a product gas flowing out of the gas separation device, and a first concentration sensor for measuring a concentration of the product gas, The control system has a recording unit that records measurement data of the first and second flow rate sensors and the first concentration sensor, and a calculation unit that calculates, based on the measurement results of the first and second flow rate sensors and the first concentration sensor, a concentration of the gas flow at a position along the supply gas supplied to the gas separation device, and a flow rate and concentration of the gas flow at a downstream position of the return gas returned from the gas separation device to the main supply pipe according to mass balance. A pipeline management system comprising:

2. 2. The pipeline management system according to claim 1, the pipeline system further comprising a compressor for maintaining a flow of the gas stream in the pipeline, a turbine for powering the compressor, and a third flow sensor and a second concentration sensor for measuring a flow rate and a concentration of the gas supplied to the turbine; The recording unit is further configured to record measurement data of the third flow rate sensor and the second concentration sensor; The calculation unit is further configured to calculate a flow rate and a concentration of the gas flow downstream of the compressor based on the measurement results of the third flow rate sensor and the second concentration sensor. A pipeline management system comprising:

3. 2. The pipeline management system according to claim 1, the pipeline system further comprising a pressure sensor co-located with the first flow sensor and / or the second flow sensor; The recording unit is further configured to record the measurement data of the pressure sensor. A pipeline management system comprising:

4. 2. The pipeline management system according to claim 1, The control system further includes an anomaly detection unit that detects an anomaly in a gas flow through the pipeline, the pipeline system further comprising a fourth flow sensor for measuring a gas flow rate of the produced gas at an end user; The recording unit is further configured to record measurement data of the fourth flow sensor; the anomaly detection unit determines a measurement anomaly by the second flow sensor measuring the flow rate of the generated gas based on whether a first error of the measurement data of the second flow sensor compared to a sum of measurement data of the fourth flow sensor measuring the same flow rate of the generated gas at the end user exceeds a threshold value; generating a correlation plot of flow rate and concentration based on historical flow rate and concentration data of the end user's gas stream, estimating an expected concentration range of the product gas using the generated correlation plot and a sum of measurement data of a fourth flow sensor measuring the flow rate of the same product gas at the end user, and determining whether the measurement data of the first concentration sensor is outside the expected concentration range; calculating a second error of the measurement data of the first concentration sensor compared to an expected concentration range of the concentration sensor measuring the product gas flow from the gas separation apparatus; A pipeline management system comprising:

5. 5. The pipeline management system according to claim 4, The anomaly detection unit is further configured to calculate a time delay of the pipeline, and the calculated time delay is further used in the calculation of the first error for anomaly detection. A pipeline management system comprising:

6. 5. The pipeline management system according to claim 4, The anomaly detection unit is further configured to classify reliability levels of the measurement data of the first, second, and third flow rate sensors and the first concentration sensor in the pipeline and the calculation data by the calculation unit based on the first error. A pipeline management system comprising:

7. 7. The pipeline management system according to claim 6, the pipeline system further comprising a compressor for maintaining a flow of the gas stream in the pipeline, a turbine for powering the compressor, and a third flow sensor and a second concentration sensor for measuring a flow rate and a concentration of the gas supplied to the turbine; The anomaly detection unit further calculates a third calculated error in the downstream of the return gas compared with measurement data of the second concentration sensor of the turbine located downstream of the return gas, and classifies the confidence level based on the third error in addition to the first error. A pipeline management system comprising:

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