A method and system for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves.

Abstract

This invention discloses a method and system for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves, comprising: S1, acquiring the medium-pressure signal of the medium-pressure pipeline upstream of the pressure regulating box and the low-pressure signal of the low-pressure pipeline downstream of the pressure regulating box; S2, performing discrete wavelet transform on the medium-pressure signal and the low-pressure signal; S3, if the low-pressure signal shows a sudden pressure drop, it is determined that a low-pressure gas leak has occurred under no-gas-use conditions; otherwise, proceed to step S4; S4, if the maximum fluctuation amplitude of the detail signal after two splits of the medium-pressure signal exceeds a set value or the low-pressure signal shows low-frequency changes, it is determined that a low-pressure gas leak has occurred under gas-use conditions. This invention, based on negative pressure waves, only requires collecting and analyzing the internal pressure of the pipeline to achieve real-time online monitoring. Compared with traditional manual inspections, it saves manpower, is highly accurate, safe, and convenient, and has a short response time and high processing efficiency in leak situations.

Description

Technical Field

[0001] This invention pertains to urban low-pressure gas pipeline leakage monitoring technology, and particularly relates to a method and system for monitoring urban low-pressure gas pipeline leakage based on negative pressure waves. Background Technology

[0002] With the increasing scale of natural gas consumption in my country, pipeline transportation is playing an increasingly important role among the five major modes of transportation. However, pipeline transportation has the following problems: pipelines may leak due to factors such as aging pipelines, inadequate sealing rings and welds during construction, corrosion, and damage by third parties. Leaked gas can pollute the air and even cause explosions, endangering urban public safety and causing casualties and property damage.

[0003] Currently, China's long-distance crude oil and refined oil pipelines have achieved full coverage of pipeline leak detection technology, primarily using negative pressure wave method. However, medium and low-pressure gas pipelines lack sufficient attention to leak detection and the application of leak detection technologies. Downstream gas pipeline network leak monitoring mainly relies on manual inspections. For downstream low-pressure pipeline networks with numerous branch lines, this requires significant manpower and time, resulting in high costs, low inspection frequency, and delayed leak detection, leading to poor safety and reliability. Urban gas pipeline networks are long and extensive. If manual inspections are used, they are not only time-consuming, inefficient, and costly, but also difficult to achieve full network coverage within a given timeframe. Furthermore, there is a lack of supervision measures for inspection quality, making it impossible to quantify the quality of the inspectors' process. Additionally, if potential hazards are discovered during inspections, the dispatch center assigns tasks for resolution, but the process of construction, completion, and feedback lacks a streamlined dispatch mechanism, and equipment maintenance and repair lack intelligent management and dispatch. These circumstances bring numerous inconveniences to the daily maintenance and management work of gas companies. Summary of the Invention

[0004] The first objective of this invention is to provide a method for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves that is highly accurate, safe, convenient, and improves processing efficiency.

[0005] The first objective of this invention is achieved through the following technical measures: a method for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves, characterized by comprising the following steps:

[0006] S1. Obtain the medium pressure signal of the medium-pressure pipeline upstream of the pressure regulating box and the low pressure signal of the low-pressure pipeline downstream of the pressure regulating box.

[0007] S2. Perform discrete wavelet transform on the medium-pressure and low-pressure signals;

[0008] S3. If the low-pressure signal shows a sudden drop in pressure, it is determined that a low-pressure pipeline gas leak has occurred under non-gas usage conditions; otherwise, proceed to step S4.

[0009] S4. If the maximum fluctuation amplitude of the intermediate pressure signal after two splits exceeds the set value or the low pressure signal shows low-frequency changes, it is determined that a low-pressure pipeline gas leak has occurred under gas usage conditions.

[0010] This invention is based on negative pressure waves. It can achieve real-time online monitoring of pipelines by simply collecting and analyzing the internal pressure of the pipeline. Compared with traditional manual inspection, it saves manpower, is more accurate, safe and convenient, and has a short response time and high processing efficiency in the event of leakage.

[0011] The discrete wavelet transform described in this invention includes:

[0012] By performing a time-domain shift and a scaling operation on the wavelet function ψ(t), the continuous wavelet basis function ψ(t) is obtained. a,τ :

[0013]

[0014] In the formula: a is the scaling factor; τ is the time shift factor;

[0015] Expanding the function f(t) in an arbitrary square-integrable space L2(R) using continuous wavelet basis functions yields the continuous wavelet transform (CWT):

[0016]

[0017] Where: WT f (a,τ) are the continuous wavelet variation coefficients; It is ψ a，τ The conjugate complex number of (t);

[0018] Discretizing the scale factor a and the time shift factor τ, we get:

[0019]

[0020]

[0021] Discretize the initial values ​​of the scaling factor a and the time shift factor τ, with a0 = 0 and Δτ = 0, to obtain the binary wavelet and the binary wavelet transform:

[0022]

[0023]

[0024] Orthogonal decomposition and multi-resolution analysis were performed on the pressure signal. We obtain approximate signals V1, V2…V n And detailed signals W1, W2…w n ,n≧3.

[0025] This invention estimates the amount of gas leakage based on the pressure data fluctuation range when a low-pressure pipeline gas leak occurs under no-gas conditions.

[0026] When a low-pressure pipeline gas leak occurs under gas usage conditions, this invention estimates the gas leakage amount based on the low-frequency change period of the approximate signal after two splits of the low-pressure signal, or based on the maximum fluctuation amplitude, average value, and variance of the detail signal after two splits of the medium-pressure signal.

[0027] This invention can estimate the amount of gas leakage, thus enabling the estimation of the scale of a leakage accident and providing a reference for accident handling.

[0028] The set value described in this invention is 0.3.

[0029] The second objective of this invention is to provide a system using the above-described method for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves.

[0030] The second objective of this invention is achieved through the following technical measures: a system using the above-mentioned method for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves, characterized in that it comprises:

[0031] A medium-pressure sensor is used to be installed on the medium-pressure pipeline upstream of the pressure regulating box to collect medium-pressure signals;

[0032] A low-pressure sensor is used to be installed on the low-pressure pipeline downstream of the pressure regulating box to collect low-pressure signals;

[0033] The data extraction module is used to extract medium-pressure and low-pressure signals;

[0034] The analysis module is used to perform discrete wavelet transform on the medium-pressure and low-pressure signals and determine whether a low-pressure pipeline gas leak has occurred.

[0035] The analysis module described in this invention estimates the amount of gas leakage in low-pressure pipelines.

[0036] The data extraction module of this invention uses a paperless recorder.

[0037] Compared with the prior art, the present invention has the following significant effects:

[0038] (1) This invention is based on negative pressure waves. It only requires collecting and analyzing the internal pressure of the pipeline to achieve real-time online monitoring of the pipeline. Compared with traditional manual inspection, it saves manpower, is more accurate, safe and convenient, and has a short response time and high processing efficiency in leakage conditions.

[0039] (2) This invention can estimate the amount of gas leakage, thus enabling the estimation of the scale of leakage accidents and providing a reference for accident handling.

[0040] (3) The system structure of the present invention is simple, low in cost, easy to implement, and suitable for widespread promotion and use. Attached Figure Description

[0041] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0042] Figure 1 This is a specific example of the invention, showing the pressure change curve of a low-pressure pipeline experiencing gas leakage under no-gas conditions;

[0043] Figure 2 This is a waveform transform result of a low-pressure signal in a specific embodiment of the present invention under gas usage conditions and in the presence of gas leakage;

[0044] Figure 3 This is a waveform transform result of the medium-pressure signal in a specific embodiment of the present invention under gas usage conditions and without gas leakage.

[0045] Figure 4 This is a waveform transform result of the medium-pressure signal in a specific embodiment of the present invention under gas usage conditions and in the presence of gas leakage;

[0046] Figure 5 This is a schematic diagram of the system composition of the present invention. Detailed Implementation

[0047] The present invention will now be described in detail with reference to the embodiments and accompanying drawings to help those skilled in the art better understand the inventive concept of the present invention. However, the scope of protection of the claims of the present invention is not limited to the following embodiments. For those skilled in the art, all other embodiments obtained without creative effort without departing from the inventive concept of the present invention are within the scope of protection of the present invention.

[0048] like Figure 5 As shown, the system of the present invention using a method for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves includes:

[0049] Medium pressure sensor 1 is used to be installed on the medium pressure pipeline upstream of the pressure regulating box and to collect medium pressure signals;

[0050] Low-pressure sensor 2 is used to be installed on the low-pressure pipeline downstream of the pressure regulating box and to collect low-pressure signals;

[0051] The data extraction module is used to extract medium-pressure and low-pressure signals;

[0052] The analysis module is used to perform discrete wavelet transform on the medium-pressure and low-pressure signals and determine whether a low-pressure pipeline gas leak has occurred.

[0053] The data extraction module specifically employs a paperless recorder 3. The paperless recorder is powered by a 220V power supply and continuously records data collected by the sensor after startup, outputting the data via a USB port. The pressure transmitter mainly consists of three parts: a pressure sensing element, a measuring circuit, and process connectors. It converts the gas pressure parameters sensed by the pressure sensing element into data signals for recording by the paperless recorder, primarily used for pressure detection in low- and medium-pressure gas pipelines.

[0054] 1. Connect the signal input port of the medium-pressure sensor to the medium-pressure pipeline.

[0055] Before closing the switch at the threaded interface on the medium-pressure pipeline side, wrap the medium-pressure sensor with raw rubber tape and install it at the pressure gauge branch interface of the medium-pressure pipeline. The connection thread type is M20×1.5. After installation, open the switch at the threaded interface on the medium-pressure pipeline side and check whether there is any leakage at the interface.

[0056] 2. Connect the low-pressure sensor signal input port to the low-pressure pipeline.

[0057] Before closing the switch at the low-pressure pipeline side threaded interface, wrap the low-pressure sensor 2 with raw rubber tape and install it at the low-pressure pipeline pressure gauge branch interface. The connection thread type is M20×1.5. After installation, open the switch at the medium-pressure pipeline side threaded interface and check whether there is any leakage at the interface.

[0058] 3. Connect the signal output ports of the medium and low pressure sensors to the paperless recorder.

[0059] Connect the signal output ports of the medium-pressure and low-pressure sensors to the signal input port of the paperless recorder. The paperless recorder is powered by a 220V AC power supply and outputs data through the USB output port. After connection, perform debugging to ensure that the signal input is correct and stable.

[0060] 4. The paperless recorder draws power from a 220V AC power source and supplies power to the medium and low pressure sensors via a 24V feed output. Input terminals B, C, and G in the paperless recorder's input channels receive 4-20mA signals from the pressure sensors and convert them into pressure signals.

[0061] This invention discloses a method for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves, comprising the following steps:

[0062] S1. Obtain the medium pressure signal of the medium-pressure pipeline upstream of the pressure regulating box and the low pressure signal of the low-pressure pipeline downstream of the pressure regulating box.

[0063] S2. Perform discrete wavelet transform on the medium-pressure and low-pressure signals;

[0064] Specifically, by performing a time-domain shift and a scaling operation on the wavelet function ψ(t), the wavelet basis function ψ(t) is obtained. a,τ Its expression is:

[0065]

[0066] In the formula: a is the scaling factor, which reflects the width and amplitude changes of the wavelet function; τ is the time shift factor, which reflects the translation position of the wavelet function on the time axis.

[0067] Expanding the function f(t) in an arbitrary square-integrable space L2(R) under the continuous wavelet basis functions yields the continuous wavelet transform (CWT), whose expression is:

[0068]

[0069] Where: WT f (a,τ) are the continuous wavelet variation coefficients; It is ψ a，τ The conjugate complex number of (t).

[0070] Simultaneously, the scaling factor 'a' and the time shift factor 'τ' are discretized to ensure that the time-domain and frequency-domain information obtained after wavelet transform are both discrete, resulting in the expression:

[0071]

[0072]

[0073] Specialized discretization is performed on the initial values ​​of the scaling factor and time shift factor, with a0 = 0 and Δτ = 0, to obtain the binary wavelet and binary wavelet transform:

[0074]

[0075]

[0076] The expression for orthogonal decomposition and multiresolution analysis of the signal is as follows:

[0077]

[0078] By setting j=5, we can obtain the approximate signals V1, V2…V6 and the detail signals W1, W2…W6 after 6 decompositions.

[0079] S3. When there is a sudden drop in pressure in the low-pressure signal (for example, the pressure drops by 100Pa within 1 second, which is an empirical value that can be obtained from experiments), it is determined that a low-pressure pipeline gas leak has occurred under no-gas conditions; otherwise, proceed to step S4.

[0080] S4. If the maximum fluctuation amplitude of the intermediate pressure signal after two splits exceeds the set value or the low pressure signal shows low-frequency changes, it is determined that a low-pressure pipeline gas leak has occurred under gas usage conditions.

[0081] 1. Gas leak detection under no-gas conditions:

[0082] The low and medium pressures at the inlet and outlet of the pressure regulator exhibit different characteristics during gas consumption and leakage processes. During leakage, the low-pressure outlet of the pressure regulator shows high-frequency fluctuations and low-frequency periodic changes; the fluctuation amplitude and periodicity increase with increasing leakage flow rate. The fluctuation amplitude of the medium-pressure outlet of the pressure regulator is relatively small. However, during gas consumption, the low-pressure outlet of the pressure regulator exhibits irregular high-frequency fluctuations without low-frequency periodic changes; the medium-pressure outlet of the pressure regulator exhibits large fluctuations, with a much larger amplitude than during leakage. The specific identification method is as follows:

[0083] The presence of a sudden pressure drop in the data received by the low-pressure sensor indicates a leak. When there are no gas-consuming devices downstream of the regulator, the low-pressure curve exhibits a stable, fluctuating trend. When a leak occurs in the downstream pipeline, a sudden pressure drop will occur at the leak point, followed by fluctuations within a relatively large range depending on the leakage flow rate. The amplitude of the fluctuation increases with the increase in leakage flow rate. The negative pressure wave disappears after the leak stops; the duration of this negative pressure wave fluctuation is the duration of the leak. Therefore, if the low-pressure sensor receives data showing a sudden pressure drop when there is no gas consumption, it can be determined that a leak has occurred in the low-pressure pipeline section downstream of the regulator.

[0084] 2. Gas leak detection under gas usage conditions:

[0085] When a leak occurs during gas usage, the low-pressure changes at the inlet and outlet of the pressure regulator exhibit characteristics typical of a leak, which are significantly different from those observed during gas usage. Specifically, the low-pressure changes are periodic, while the medium-pressure fluctuations are smaller. Therefore, the occurrence of a leak can be determined by comparing the results obtained through wavelet transform of the pressure signals—specifically, the periodicity of the low-pressure approximation signal and the fluctuation amplitude of the medium-pressure detail signal. The specific determination method is as follows:

[0086] The medium and low voltage signals are decomposed to obtain the approximate signals a1, a2…a6 and the detail signals d1, d2…d6 of the medium and low voltage signals, respectively.

[0087] The extreme values ​​of the medium-pressure detail signal d2 obtained from wavelet transform and the presence of low-frequency variations in the low-pressure signal are chosen as criteria for determining whether a leak has occurred. Regardless of whether there are gas-using devices downstream of the regulator, as long as a leak exists in the pipeline, the maximum fluctuation amplitude of the medium-pressure detail signal d2 will not exceed a certain experimentally determined value. When at least two devices are using gas simultaneously, the maximum fluctuation amplitude of the medium-pressure detail signal d2 before the regulator is greater than this determined value, and the fluctuations are more unstable. If the maximum fluctuation amplitude of the medium-pressure detail signal d2 exceeds this determined value, a leak is determined to have occurred.

[0088] When a leak occurs in the pipeline, the low-pressure downstream of the pressure regulator will exhibit low-frequency changes. These low-frequency changes are even more pronounced during gas usage, whereas they are absent during gas usage. Therefore, the presence of a low-frequency change can be determined using an approximate signal obtained through wavelet transform. If a low-frequency change is observed, a leak is identified.

[0089] 3. Estimation of gas leakage flow rate under no-gas conditions:

[0090] When a leak occurs in the downstream pipeline of the pressure regulator, it will cause a sudden pressure drop at the leak point, followed by fluctuations within a wide range depending on the magnitude of the leak flow. The amplitude of these fluctuations will increase with the increase in the leak flow. The magnitude of the leak can be estimated based on the range of pressure fluctuations.

[0091] 4. Estimation of gas leakage flow rate under gas usage conditions:

[0092] The medium and low voltage signals are decomposed to obtain the approximate signals a1, a2…a6 and the detail signals d1, d2…d6 of the medium and low voltage signals, respectively.

[0093] As the leakage flow increases, the low-frequency variation period of the low-pressure approximation signal a2 increases, and the magnitude of the leakage flow can be estimated based on the low-frequency variation period of the low-pressure approximation signal a2.

[0094] As the leakage flow rate increases, the extreme values, average values, and variance of the medium-pressure detail signal d2 all increase, meaning that the fluctuation of the medium-pressure signal also increases with the increase in leakage flow rate. The magnitude of the leakage flow rate can be estimated based on the extreme values, average values, and variance of the medium-pressure detail signal d2.

[0095] Specific examples and explanations of principles:

[0096] Leakage identification under no-gas conditions:

[0097] Under no-gas operation conditions, repeated leakage tests with different flow rates were conducted over a certain period of time. The change in the low-pressure output of the pressure regulator was as follows: Figure 1 As shown.

[0098] The graph shows the variation of the low-pressure outlet of the pressure regulator under the following operating conditions from left to right: leakage flow rates of 480 L / h, 420 L / h, 360 L / h, 300 L / h, 240 L / h, 180 L / h, and 120 L / h. Figure 1 As shown, when a leak occurs, the low-pressure will experience a sudden change, followed by continuous fluctuations and gradually stabilizing within a certain range. The amplitude of these fluctuations is related to the amount of leakage.

[0099] from Figure 1 It is known that the larger the leakage flow rate, the greater the pressure fluctuation during leakage. When the leakage flow rate is small, such as at 180 L / h and 120 L / h, the pressure fluctuation is almost negligible. During leakage, the fluctuation of low-pressure is related to the magnitude of the leakage flow rate.

[0100] Leakage identification under gas usage conditions:

[0101] Leakage tests were conducted under useful gas conditions. Figure 2 The wavelet transform result is the low-pressure signal under the condition of leakage flow rate of 450L / h.

[0102] The reconstructed signal after wavelet transform denoising retains the variation characteristics of the pressure signal, while the approximate signal reflects the low-frequency variation characteristics of the signal, and the detail signal reflects the high-frequency variation characteristics of the signal.

[0103] When a gas leak occurs during gas usage, the approximate signal exhibits low-frequency pressure changes, most notably in approximate signal a5. Comparing the low-frequency change period of the approximate signal across 1000 data points reveals that the low-frequency change period is 29 seconds when the leakage flow rate is 450 L / h.

[0104] The same wavelet transform was performed on the pressure signals of the gas-only operating condition and the gas-using condition with a leakage flow rate of 450 L / h. The results are as follows: Figure 3 , Figure 4 As shown. Based on the comparison of the above results, it can be found that the fluctuation amplitudes of the detail signals d2 and d3 during the gas consumption process are both greater than 0.4, while during leakage, the fluctuation amplitudes of the detail signals d2 and d3 are approximately 0.1. Comparing the detail signals at the d4 to d6 scales, it can be found that the fluctuation amplitudes of the detail signals during the gas consumption process are significantly greater than those during the leakage process. However, for the leakage process, the waveforms and patterns of the detail signals are almost identical under different flow rates. Therefore, when a leak occurs during gas consumption, the presence of a leak can be determined by the detail signal of the medium-pressure signal. Taking a fixed value of 0.3, in this case, the fluctuation amplitude of the detail signal of the medium-pressure signal is greater than 0.3, which indicates that a leak has occurred.

Claims

1. A method for monitoring leaks in urban low-pressure gas pipelines based on negative pressure waves, characterized in that... Includes the following steps: S1. Obtain the medium pressure signal of the medium-pressure pipeline upstream of the pressure regulating box and the low pressure signal of the low-pressure pipeline downstream of the pressure regulating box. S2. Perform discrete wavelet transform on the medium-pressure and low-pressure signals; The discrete wavelet transform includes: For wavelet functions By performing time-domain translation and scaling, continuous wavelet basis functions are obtained. : In the formula: Scale factor; It is the time shift factor; For any square-integrable space under continuous wavelet basis functions functions in Expanding the wavelet transform yields a continuous wavelet transform. : In the formula: These are continuous wavelet variation coefficients; yes The conjugate of complex numbers; scale factor and time shift factor After discretization, we get: ； ; for scaling factor and time shift factor The initial values ​​are discretized. This yields the binary wavelet and the binary wavelet transform: ; Orthogonal decomposition and multi-resolution analysis were performed on the pressure signal. To obtain an approximate signal and detailed signals ; S3. If the low-pressure signal shows a sudden drop in pressure, it is determined that a low-pressure pipeline gas leak has occurred under non-gas usage conditions; otherwise, proceed to step S4. When a low-pressure pipeline gas leak occurs under no-gas conditions, the amount of gas leak is estimated based on the pressure data fluctuation range. S4. If the maximum fluctuation amplitude of the intermediate pressure signal after two splits exceeds the set value or the low pressure signal shows low-frequency changes, it is determined that a low-pressure pipeline gas leak has occurred under gas usage conditions. The set value is 0.3; When a low-pressure pipeline gas leak occurs under gas usage conditions, the amount of gas leak can be estimated based on the low-frequency variation period of the approximate signal after the low-pressure signal is split twice, or based on the maximum fluctuation amplitude, average value, and variance of the detail signal after the medium-pressure signal is split twice.

2. A system using the urban low-pressure gas pipeline leakage monitoring method based on negative pressure waves as described in claim 1, characterized in that... include: A medium-pressure sensor is used to be installed on the medium-pressure pipeline upstream of the pressure regulating box to collect medium-pressure signals; A low-pressure sensor is used to be installed on the low-pressure pipeline downstream of the pressure regulating box to collect low-pressure signals; The data extraction module is used to extract medium-pressure and low-pressure signals; The analysis module is used to perform discrete wavelet transform on the medium-pressure and low-pressure signals and determine whether a low-pressure pipeline gas leak has occurred.

3. The system according to claim 2, characterized in that: The analysis module estimates the amount of gas leakage in low-pressure pipelines.

4. The system according to claim 3, characterized in that: The data extraction module uses a paperless recorder.

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