A method, apparatus, device, medium, and product for monitoring a pipeline leak

Abstract

The application discloses a pipeline leakage monitoring method, device, equipment, medium and product, and relates to the technical field of ore pulp pipeline transportation. The method comprises the following steps: acquiring a first group of pressure parameters of different positions of a pipeline and a main pulse frequency of a conveying device; performing time-frequency conversion on the first group of pressure parameters to obtain a plurality of components of different frequency bands; identifying and removing a target component corresponding to the main pulse frequency from the plurality of components of different frequency bands to obtain residual components; reconstructing a second group of pressure parameters based on the residual components; determining a pressure change rate based on the second group of pressure parameters; and determining that the pipeline has a leakage when the pressure change rate is greater than or equal to a preset threshold. The pipeline leakage monitoring method, device, equipment, medium and product provided by the application are used for improving the detection sensitivity of pipeline leakage.

Description

Technical Field

[0001] This application relates to the field of slurry pipeline transportation technology, and in particular to a method, apparatus, equipment, medium and product for monitoring pipeline leaks. Background Technology

[0002] Long-distance pipeline transportation of fly ash slurry typically uses wear-resistant composite pipes co-extruded from high-density polyethylene (HDPE) and polyolefin elastomer (POE). These pipes have excellent corrosion resistance, flexibility, and impact resistance.

[0003] However, this composite wear-resistant pipe is a typical viscoelastic material, exhibiting high elasticity, low modulus, and significant viscoelastic characteristics, which poses challenges to pipe leak monitoring. While existing negative pressure wave and flow balance methods are mature in metal pipes, their direct application to elastic pipes leads to rapid signal attenuation due to the absorption and buffering effect of the pipe wall on the pressure wave. Furthermore, the periodic pressure pulse interference generated by the operation of the water diaphragm pump results in low detection sensitivity and a high false alarm rate. Summary of the Invention

[0004] This application is made in view of the above-mentioned problems. This application provides a method, apparatus, equipment, medium, and product for monitoring pipeline leaks, which can eliminate the interference of pulsating noise generated by the conveying equipment and achieve pipeline leak detection with high sensitivity and low false alarm rate.

[0005] To achieve the above objectives, according to one aspect of this application, the following technical solution is provided: Obtain the first set of pressure parameters at different locations in the pipeline and the main pulse frequency of the conveying equipment; The first set of pressure parameters was subjected to time-frequency transformation to obtain components in multiple different frequency bands; Identify and remove the target component corresponding to the main pulse frequency from multiple components of different frequency bands to obtain the remaining components; The second set of pressure parameters is obtained by reconstructing the remaining components, and the pressure change rate is determined based on the second set of pressure parameters. A pipeline leak is determined when the rate of pressure change is greater than or equal to a preset threshold.

[0006] Compared with existing technologies, the pipeline leakage monitoring method provided in this application firstly acquires a first set of pressure parameters at different locations along the pipeline and the main pulse frequency of the conveying equipment. This allows for comprehensive acquisition of pressure change information along the pipeline and identifies periodic interference characteristics generated by the operation of the conveying equipment, providing a true and complete data foundation for subsequent interference removal and leakage identification. Secondly, performing time-frequency transformation on the first set of pressure parameters and removing the target component corresponding to the main pulse frequency can strip away the strong interference components caused by equipment pulsation at the source, preventing the interference signal from overlapping with the leakage signal and effectively improving the signal-to-noise ratio of the original pressure signal. Thirdly, reconstructing a second set of pressure parameters based on the remaining components can retain the transient pressure disturbance characteristics caused by leakage to the greatest extent, making the extracted pressure change information more accurately reflect the leakage disturbance inside the pipeline. Finally, by comparing the pressure change rate with a preset threshold, the pressure change caused by leakage can be identified sensitively and quickly. Even weak leaks with fast decay and weak amplitude in viscoelastic pipes can be effectively detected. This significantly improves detection sensitivity and reduces false alarm and false alarm rates in the context of strong impulse noise, enabling more stable and reliable real-time leakage monitoring of highly elastic composite pipes.

[0007] According to another aspect of this application, a pipeline leakage monitoring device is provided, comprising: The acquisition module is used to acquire the first set of pressure parameters at different locations in the pipeline and the main pulse frequency of the conveying equipment. The processing module is used to perform time-frequency transformation on the first set of pressure parameters to obtain components in multiple different frequency bands; The processing module is also used to identify and remove the target component corresponding to the main pulse frequency from multiple components of different frequency bands to obtain the remaining components; The processing module is also used to reconstruct a second set of pressure parameters based on the remaining components, and to determine the pressure change rate based on the second set of pressure parameters; The processing module is also used to determine if a pipeline leak has occurred when the rate of pressure change is greater than or equal to a preset threshold.

[0008] According to another aspect of this application, an electronic device is provided, comprising: Processor; and, Memory for stored programs; The program includes instructions that, when executed by a processor, cause the processor to perform the method of this application.

[0009] Compared with the prior art, the beneficial effects of the electronic device provided in this application are the same as those of the pipeline leakage monitoring method described above, and will not be elaborated here.

[0010] According to another aspect of this application, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a method for monitoring pipeline leaks.

[0011] Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the pipeline leakage monitoring method described above, and will not be elaborated here.

[0012] According to another aspect of this application, this application also provides a computer program product, the computer program including a computer program, wherein the computer program, when executed by a computer's processor, is used to cause the computer to perform the method of this application.

[0013] Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the pipeline leakage monitoring method described above, and will not be elaborated here. Attached Figure Description

[0014] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A schematic diagram of the overall structure of a pipeline leakage monitoring system according to an embodiment of this application is shown.

[0015] Figure 2 A flowchart illustrating a pipeline leakage monitoring method according to an embodiment of this application is shown; Figure 3 A schematic diagram of the structure of a pipeline leakage monitoring device provided in an exemplary embodiment of this application is shown; Figure 4 A schematic diagram of the structure of an electronic device provided in an exemplary embodiment of this application is shown; Figure 5 A schematic diagram of the structure of a computer system provided in an exemplary embodiment of this application is shown. Detailed Implementation

[0016] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. For example, the first threshold and the second threshold are only used to distinguish different thresholds and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0017] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0018] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, a combination of a and b, a combination of a and c, a combination of b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0019] Long-distance pipeline transportation of fly ash slurry is a crucial step in solid waste treatment at coal-fired power plants. High-density polyethylene (HDPE) and polyolefin elastomer co-extruded composite wear-resistant pipes are widely used in this field due to their excellent corrosion resistance, flexibility, and impact resistance. Water diaphragm pumps, as commonly used power equipment in this transportation system, offer advantages such as stable operation and low wear.

[0020] However, HDPE / POE composite wear-resistant pipes are typical viscoelastic materials, exhibiting high elasticity, low modulus, and significant viscoelastic characteristics, posing new technical challenges to pipeline leak monitoring. Existing pipeline leak monitoring technologies mainly include the negative pressure wave method and the flow balance method. The negative pressure wave method determines the location and scale of the leak by detecting the pressure disturbance wave generated instantaneously during a leak, while the flow balance method determines whether a leak has occurred by comparing the flow rate difference between the pipe inlet and outlet. This technology is relatively mature in the application of metal or rigid pipes.

[0021] However, when the above technologies are directly applied to HDPE / POE high-elasticity pipes, the detection effect decreases significantly. On the one hand, the high-elasticity pipe wall absorbs and buffers pressure waves, causing the negative pressure wave signal generated by leakage to attenuate rapidly during propagation, resulting in extremely low amplitude when it reaches the sensor, making it difficult to effectively identify. On the other hand, water diaphragm pumps generate periodic strong pressure pulses during operation. These pulses are highly similar to the leakage negative pressure wave in the frequency domain, easily leading to false alarms or missed alarms in the detection system. Furthermore, under high-pressure transmission conditions, the pipeline is in a state of elastic expansion. When a minor leak occurs, the pipe wall shrinks back, creating a volume compensation effect, making it difficult for the flow balance method to form an effective criterion.

[0022] To overcome the above problems, this application provides a method, device, medium and product for monitoring pipeline leakage. The method can effectively eliminate the interference of periodic pulsating noise generated by the device itself, extract weak leakage characteristics from the background of strong noise, and realize real-time leakage monitoring of highly elastic pipelines with high sensitivity and low false alarm rate.

[0023] The pipeline leakage monitoring method provided in this application embodiment can be executed by a terminal or by a chip applied to the terminal.

[0024] For example, the aforementioned terminal may include one or more of the following: mobile phone, tablet computer, wearable device, in-vehicle device, laptop computer, ultra-mobile personal computer (UMPC), netbook, PDA, and wearable device based on augmented reality (AR) and / or virtual reality (VR) technology. The exemplary embodiments of this application do not impose specific limitations on this.

[0025] The pipeline leakage monitoring method provided in this application is applied to a pipeline transportation system equipped with a transportation device for transporting media into the pipeline. Figure 1 A schematic diagram of the overall structure of the pipeline leakage monitoring system provided in this application embodiment is shown.

[0026] Specifically, the pipeline leakage monitoring system provided in this embodiment is applied to a process scenario in which fly ash slurry is transported over long distances using a water diaphragm pump and HDPE / POE co-extruded polyolefin composite wear-resistant pipe. This material gives the pipe excellent corrosion resistance, flexibility and impact resistance, but at the same time it also makes it exhibit typical viscoelastic mechanical characteristics, with a high damping attenuation effect on pressure waves.

[0027] like Figure 1As shown, the pipeline leakage monitoring system provided in this application embodiment includes a slurry conveying unit 110, a distributed data acquisition unit 120, a Beidou time synchronization system 130, an OPC server 140, and a background leakage monitoring unit 150. The following is in conjunction with... Figure 1 Each unit, its connections, and its functions are described in detail.

[0028] The aforementioned slurry conveying unit 110 is used to achieve stable, long-distance, high-pressure conveying of fly ash slurry. Specifically, the slurry conveying unit includes a slurry storage tank 111, a feed pump 112, a water diaphragm pump 113, and a long-distance conveying pipeline 114 connected in sequence.

[0029] For example, the aforementioned slurry storage tank 111 is equipped with a stirring mechanism to buffer the fly ash slurry and prevent the solid particles in the slurry from settling through continuous stirring, thereby ensuring the uniformity of the output slurry concentration. The discharge end of the slurry storage tank 111 is connected to the inlet of the feed pump 112. The feed pump 112, as a pre-feeding device, stably supplies the slurry to the subsequent water diaphragm pump 113 with a relatively low head. Its function is to ensure stable inlet pressure of the main pump and prevent cavitation. The water diaphragm pump 113, as the core power source of the entire pipeline system, has its inlet connected to the outlet of the feed pump, and its outlet connected to the starting end of the long-distance conveying pipeline 114. The water diaphragm pump 113 pressurizes the input slurry to the required pressure value through the reciprocating motion of the diaphragm and sends the high-pressure slurry into the conveying pipeline.

[0030] It should be noted that during the operation of the water diaphragm pump 113, the periodic reciprocating motion of its plunger or piston assembly will generate periodic pressure pulse signals in the outlet pipeline and the connected delivery pipeline. The main pulse frequency of this pressure pulse is directly related to the real-time operating parameters of the water diaphragm pump, such as the crankshaft speed and the number of plungers. This periodic pulsation constitutes the main source of interference signals that this system needs to identify and eliminate.

[0031] Considering the high damping attenuation characteristics of HDPE / POE viscoelastic pipes to pressure waves, this application adopts a distributed data acquisition unit 120. The distributed data acquisition unit 120 is set with multiple monitoring points at intervals along the pipe extension direction of the long-distance conveying pipeline 114, according to the limit layout spacing calculated based on the pressure wave attenuation characteristics.

[0032] In this embodiment, five monitoring points, k0, k1, k2, k3, and k4, are shown as an example. However, this application is not limited to this. In actual deployment, the number of monitoring points can be increased or decreased according to the total length of the pipeline and the attenuation characteristics. Each point is equipped with an independent PLC acquisition module.

[0033] Depending on the function of each sampling point, the sensor configuration is designed differently. For example, the starting point k0 and the ending point k4 of the pipeline are configured as integrated data acquisition points. Specifically, the PLC acquisition modules located at points k0 and k4 are connected not only to pressure transmitters but also to flow and concentration detection instruments. Therefore, these points can simultaneously acquire real-time medium pressure, instantaneous volumetric or mass flow rate of the slurry, and real-time mass or volumetric concentration of the slurry at their respective locations. Furthermore, the PLC at the starting point k0 is also communicatively connected to the control system of the water diaphragm pump 113 to acquire real-time operating parameters such as the pump's speed and number of plungers, using these parameters as the basis for calculating the real-time main pulse frequency of the water diaphragm pump. Meanwhile, the middle sections k1, k2, and k3 of the pipeline are configured as pure pressure acquisition points. Specifically, the PLC acquisition modules at points k1, k2, and k3 are only connected to pressure transmitters and are specifically used to acquire real-time raw pressure data for their respective pipe sections.

[0034] It should be emphasized that the raw pressure data collected by the pressure transmitters at all the above points are superimposed signals of multiple physical components, including: the normal pipeline static pressure baseline, the periodic pulsating interference signal generated by the operation of the water diaphragm pump 113, and the instantaneous negative pressure disturbance signal induced by the leakage when a leakage event occurs.

[0035] It should be understood that the specific spacing of the aforementioned monitoring points was determined through theoretical calculations based on the pressure wave attenuation coefficient of the HDPE / POE pipeline and the minimum effective detection threshold of the pressure transmitter. This design ensures that the negative pressure wave generated by the leak can be effectively captured by at least one sensor before it attenuates to an unmeasurable threshold, thus overcoming the technical deficiency of rapid pressure wave attenuation in viscoelastic pipelines, which makes it difficult to detect weak leak signals.

[0036] The aforementioned Beidou time synchronization system 130 establishes a communication connection with the PLC acquisition modules of all points in the distributed data acquisition unit 120. Relying on Beidou time synchronization, the data acquisition time of each monitoring point is synchronized, which can ensure that the pressure, flow and concentration data of each acquisition point in the entire pipeline are strictly synchronized in the time dimension. This eliminates the sampling timing deviation caused by the drift of local clocks of each device or the uncertainty of network transmission delay, and provides a guarantee for the subsequent leak location algorithm based on the arrival time difference of pressure waves.

[0037] The aforementioned OPC server 140 is communicatively connected to all field PLC acquisition modules and the background leakage monitoring unit 150. The OPC server is used to receive the raw pressure, flow rate, concentration, and water diaphragm pump operating parameters uploaded by PLCs at various locations, complete the protocol unification, data aggregation and standardization of heterogeneous data from different PLC models, and then forward the standardized full set of monitoring data to the background leakage monitoring unit 150 in real time.

[0038] Figure 2 A flowchart illustrating a pipeline leakage monitoring method provided in an exemplary embodiment of this application is shown. Figure 2 As shown, the pipeline leakage monitoring method provided in this application embodiment is applied to... Figure 1 The pipeline leak monitoring system shown includes the following methods for monitoring pipeline leaks: Step 201: Obtain the first set of pressure parameters at different locations in the pipeline and the main pulse frequency of the conveying equipment.

[0039] This step obtains the original pressure parameters at different locations along the pipeline and the main pulse frequency of the conveying equipment, providing a raw data foundation and noise identification basis for subsequent signal processing. The first set of pressure parameters retains the true pressure state at each cross-section of the pipeline, avoiding information loss that might occur during preprocessing. The main pulse frequency, as a characteristic identifier of the conveying equipment's own pulsating noise, allows subsequent steps to selectively remove equipment noise rather than blindly filtering, thus laying the foundation for improving the accuracy and reliability of leak detection.

[0040] For example, the acquisition of the first set of pressure parameters at different locations in the pipeline and the main pulse frequency of the conveying equipment specifically includes: acquiring pressure parameters at multiple monitoring points spaced apart along the length of the pipeline at different times, as the first set of pressure parameters; and acquiring the operating frequency and number of plungers of the conveying equipment, and determining the main pulse frequency based on the operating frequency and the number of plungers.

[0041] Specifically, within each sampling cycle, pressure transmitters at monitoring points spaced apart along the pipeline length synchronously acquire transient pressure values ​​at their respective locations and transmit the acquired pressure data to the corresponding PLC acquisition module. Each PLC acquisition module aggregates the pressure data acquired within the same sampling cycle according to the point order, forming a set of raw pressure parameters corresponding to that sampling moment. As the sampling cycle repeats, the system continuously acquires multiple sets of raw pressure parameters; these multiple sets of raw pressure parameters organized in chronological order constitute the first set of pressure parameters. Simultaneously, during monitoring, because the PLC acquisition module located at point k0 at the pipeline's starting end is communicatively connected to the water diaphragm pump's control system, it can read the current operating frequency of the water diaphragm pump and the number of plungers specified on the equipment nameplate in real time. The PLC acquisition module multiplies the read operating frequency by the number of plungers to calculate the current main pulse frequency in real time.

[0042] The first set of pressure parameters mentioned above fully records the information on the pressure changes of each monitoring point over time, including various components such as the pipeline static pressure baseline, the periodic pulsation signal generated by the conveying equipment, and the possible leakage negative pressure signal.

[0043] Step 202: Perform time-frequency transformation on the first set of pressure parameters to obtain components in multiple different frequency bands.

[0044] This step involves performing time-frequency transformation on the first set of pressure parameters, decomposing the original pressure signal into multiple components with different frequency bands. This achieves the separation of different frequency components, providing a frequency domain basis for subsequent accurate identification and removal of equipment pulsation noise.

[0045] For example, the above-mentioned time-frequency transformation of the first set of pressure parameters to obtain multiple components of different frequency bands specifically includes: performing a discrete wavelet transform on the first set of pressure parameters, decomposing the first set of pressure parameters into an approximate component and multiple detail components according to a preset number of decomposition levels, thereby obtaining multiple components of different frequency bands. Each detail component corresponds to a different frequency band range.

[0046] Specifically, this application embodiment uses wavelet transform to achieve time-frequency transformation. The basic principle of wavelet transform is: let the original pressure signal collected at a certain monitoring point be... x ( t Select the mother wavelet. ψ ( t In this embodiment, the mother wavelet ψ ( t The db4 wavelet from the Daubechies wavelet family is used. The db4 wavelet has tight support and good regularity, and its mathematical expression can be obtained recursively from the wavelet filter coefficients of the multi-scale equation. For details, please refer to well-known literature in the field of wavelet analysis.

[0047] In this embodiment, time-frequency features are first analyzed using continuous wavelet transform. The formula for continuous wavelet transform is:

[0048] In the formula, CWT ( a,b The wavelet coefficients () represent the energy distribution of the signal at different scales and locations. x ( t The signal is the raw time-domain pressure signal of the pipeline acquired by the PLC, including the static pressure baseline, pump periodic pulsation, leakage negative pressure wave, and high-frequency noise. Mother wavelet function ψ ( t The complex conjugate of ) a For scaling parameters, b This is the time shift parameter, which controls the position of the wavelet on the time axis.

[0049] The above scaling parameters aThis is used to control the stretching or compression of the mother wavelet. When |a|>1, the mother wavelet is stretched, the time domain width increases, and the frequency band narrows, corresponding to low-frequency components in the signal (such as the overall trend of pipeline pressure, slow water hammer waves). When |a|<1, the mother wavelet is compressed, the time domain width decreases, and the frequency band widens, corresponding to high-frequency components in the signal (such as random noise, bubble bursting, and turbulent flow). The value of 'a' is usually discretized according to powers of 2, i.e., a=2^j (j is an integer).

[0050] The above time shift parameters b This is used to control the position of the mother wavelet on the time axis, allowing the wavelet to traverse the entire time range of the signal. Through... b The continuous values, CWT ( a,b It can reflect the frequency distribution of a signal at different times.

[0051] The above wavelet coefficients CWT ( a,b This reflects the original signal. x ( t Within the frequency band corresponding to scale a, at the time position b The magnitude of the energy component in the vicinity. CWT ( a,b The larger the absolute value of ), the more significant the frequency component is at that moment.

[0052] The continuous wavelet transform described above fully describes the energy distribution of a signal at different scales and time locations, making it suitable for theoretical analysis and feature visualization. However, the continuous wavelet transform is computationally intensive and contains information redundancy, such as the high correlation between wavelet coefficients between adjacent scales and adjacent time locations, making it unsuitable for the high real-time requirements of industrial applications.

[0053] Therefore, in the engineering implementation of this application, discrete wavelet transform is used as a time-frequency transformation method. Discrete wavelet transform converts the scale parameter in continuous wavelet transform... a Translation parameters b Discretization is typically performed by taking... a =2^j (j is an integer), b =k·2^j· T s (where k is an integer), forming a binary discrete grid. This discretization method allows the wavelet family to form an orthogonal basis, which can uniquely and without redundancy represent the original signal. x ( t The discrete wavelet transform is calculated using the Mallat fast algorithm, which decomposes the signal layer by layer through a set of low-pass and high-pass filters, significantly reducing the computational load and making it suitable for real-time operation in PLCs or embedded devices in industrial settings.

[0054] Based on the scale-frequency mapping relationship of continuous wavelets, the hierarchical decomposition rule of discrete wavelets is determined, and thus the number of decomposition levels J is determined: the main pulse frequency of the conveying equipment. f The pulse can fall completely within the frequency band of a specific detail component. This embodiment sets the sampling frequency. f s =100Hz, f With pulse = 3.6Hz, calculations show that when J = 5, the D4 frequency band is 3.125Hz~6.25Hz, including... f With pulse = 3.6 Hz, the number of decomposition layers J = 5 is set.

[0055] According to Mallat's algorithm for discrete wavelet transform, x ( t The decomposition is performed layer by layer. The first layer of decomposition will... x ( t The process is decomposed into a first-level approximate component A1 and a first-level detail component D1; the second-level decomposition further decomposes A1 into a second-level approximate component A2 and a second-level detail component D2; and so on, up to the Jth level. The final decomposition result is as follows: x ( t )=A J (t)+D1(t)+D2(t)+…+D J (t) Among them, A J (t) is the J-th layer approximation component, corresponding to the lowest frequency component in the original signal, reflecting the overall trend and slow change of pipeline pressure, D1(t) to D J (t) represents the detail components from layer 1 to layer J, and the frequency band range corresponding to each detail component decreases sequentially as the number of layers increases.

[0056] For example, let the sampling frequency be... f s=100Hz, decomposition level J=5. According to the Nyquist sampling theorem, the effective frequency range of the original signal is 0Hz~50Hz. After discrete wavelet transform, the frequency band ranges corresponding to each component are as follows: D1 corresponds to 25Hz~50Hz (highest frequency), D2 corresponds to 12.5Hz~25Hz, D3 corresponds to 6.25Hz~12.5Hz, D4 corresponds to 3.125Hz~6.25Hz, D5 corresponds to 1.5625Hz~3.125Hz, and A5 corresponds to 0Hz~1.5625Hz (lowest frequency). If the main pulse frequency of the water diaphragm pump calculated in step 201 is 3.6Hz, then this frequency falls within the frequency band range of the D4 component (3.125Hz~6.25Hz). If the main pulse frequency is 2Hz, then it falls within the frequency band range of the D5 component (1.5625Hz~3.125Hz). The negative pressure wave generated by leakage contains rich frequency components, and its energy is distributed in multiple low-frequency components such as A5 and D5.

[0057] It should be noted that the aforementioned approximate components refer to the components obtained after low-pass filtering of the original signal, reflecting the slowly changing parts of the signal; while the detail components refer to the components obtained after high-pass filtering of the original signal, reflecting the rapidly changing parts of the signal. The detail components obtained from each decomposition layer capture the signal fluctuation characteristics within that layer's frequency band. Through the above decomposition, the periodic pulsating noise generated by the transmission equipment is concentrated into one or several detail components corresponding to its main pulse frequency, while the negative pressure wave characteristics generated by leakage are distributed in other components, thereby achieving effective separation of noise and signal.

[0058] The parameters such as the number of decomposition levels and the mother wavelet type in the discrete wavelet transform can be predetermined according to the actual engineering conditions and fixed in the data processing unit, eliminating the need for recalculation during each monitoring session. Those skilled in the art can select appropriate wavelet bases and the number of decomposition levels based on factors such as the characteristics of the pipeline transport medium, the sampling frequency, and the distribution range of the main pulse frequency of the transport equipment, through experiments or theoretical analysis. For example, for a fly ash slurry transport pipeline driven by a water diaphragm pump, the sampling frequency is typically set to 100Hz, the number of decomposition levels is set to 5, and the mother wavelet is selected as the db4 wavelet, which can effectively separate the equipment pulsation noise and leakage signal into different detail components.

[0059] Step 203: Identify and remove the target component corresponding to the main pulse frequency from multiple components of different frequency bands to obtain the remaining components.

[0060] Since the periodic pulsating noise generated by the conveying equipment is mainly concentrated in the frequency band of the main pulse frequency and its harmonics, while the negative pressure wave characteristics generated by leakage are distributed in other frequency bands, this step uses the main pulse frequency of the conveying equipment obtained in step 201 to identify the target component corresponding to the equipment pulsating noise from the multiple components of different frequency bands obtained in step 202 and remove it. This can effectively eliminate the main sources of interference in the original pressure signal while retaining the leakage characteristic information.

[0061] For example, the process of identifying and removing the target component corresponding to the main pulse frequency from multiple components in different frequency bands to obtain the remaining components specifically includes: First, determining the frequency band range where the main pulse frequency is located. Then, identifying the components in the multiple components in different frequency bands whose frequency band range falls within the frequency band range where the main pulse frequency is located as target components. Finally, removing the target components from the multiple components in different frequency bands to obtain the remaining components.

[0062] Specifically, based on the main pulse frequency calculated in step 201 f pulse, and the frequency band range corresponding to each detail component in step 202, to determine f The pulse falls within the frequency band of a specific detail component. For example, in the aforementioned example with a sampling frequency of 100Hz and 5 decomposition layers, if... f If pulse = 3.6Hz, then this frequency falls within the frequency band of component D4 (3.125Hz~6.25Hz), therefore D4 is identified as the target component. If f If pulse=2Hz, it falls within the frequency band of component D5 (1.5625Hz~3.125Hz), therefore D5 is identified as the target component.

[0063] After identifying the target component, all coefficients of the target component are set to zero, or attenuation is performed as needed. After removing the target component, the remaining components include the approximate component A. J This includes other detail components that were not identified as targets (such as D1, D2, D3, D5, etc.). These remaining components have largely eliminated interference from the conveying equipment's pulsating noise, but retain leakage negative pressure waves and other non-equipment noise components. This operation is performed in the wavelet domain, which precisely targets the frequency band where the equipment noise is located, avoiding the excessive smoothing of the leakage signal by traditional filtering. The remaining components will be used in subsequent steps to reconstruct a clean pressure signal.

[0064] Step 204: Reconstruct the second set of pressure parameters based on the remaining components, and determine the pressure change rate based on the second set of pressure parameters.

[0065] This step involves inversely transforming the remaining components obtained in step 203 to resynthesize them into a pressure signal after removing equipment pulsation noise. Based on this, the pressure change rate is calculated, reflecting the transient characteristics of pipeline pressure. When the pipeline is operating normally, even with equipment pulsation noise and turbulent flow, the pressure change rate typically remains at a low level. When a leak occurs in the pipeline, the pressure drops rapidly, causing the pressure change rate to surge. Therefore, the pressure change rate can serve as an effective characteristic quantity for determining whether a leak has occurred.

[0066] For example, the above-mentioned method of reconstructing the second set of pressure parameters based on the residual components and determining the pressure change rate based on the second set of pressure parameters specifically includes: First, performing an inverse wavelet transform on the residual components to obtain the second set of pressure parameters. Then, determining the pressure change rate based on the pressure difference and time interval between adjacent time points of the second set of pressure parameters.

[0067] Specifically, for the remaining components obtained in step 203 (including approximate component A) J The inverse wavelet transform is performed on the components (including the detail components not identified as targets). The inverse wavelet transform is the reverse process of the discrete wavelet transform, which recombines the components according to the original decomposition structure to restore a complete pressure signal. Since the target component (i.e., the component where the equipment pulsation noise is mainly concentrated) has been removed before reconstruction, the amplitude of the equipment pulsation noise in the second set of pressure parameters obtained by reconstruction is significantly reduced, while the characteristics of the leakage negative pressure wave are preserved.

[0068] After obtaining the second set of pressure parameters, the rate of pressure change is further determined. The rate of pressure change refers to the amount of pressure change per unit time, used to characterize the severity of pressure fluctuations. Let the sequence of pressure values ​​in the second set of pressure parameters over time be... P ( t If the sampling time interval is Δt, then the rate of pressure change between two adjacent sampling points can be calculated using the following formula: Pressure change rate = | P ( t +Δ t )- P ( t )| / Δ t .

[0069] In the formula, P ( t )for t Real-time pressure value after noise reduction and reconstruction. P ( t +Δ t () is the next sampling time t +Δ t The corresponding pressure value.

[0070] In practical engineering applications, to eliminate random noise and interference from single-point abnormal data, a fixed-duration moving average window method can be used for optimization calculation: N consecutive sampling points are selected to form a moving time window, and the average pressure change rate is calculated within the window. The window mean is used as the final judgment criterion. Here, N is the number of sampling points within the window, for example, N=5 or N=10. Under stable pipeline transport conditions, affected by low-frequency pump pulsation and slurry turbulence, the average pressure change rate remains in a low range for a long time. Once a pipeline leaks, the leakage negative pressure wave will cause a short-term rapid drop in pressure, which instantaneously and significantly increases in sync with the average pressure change rate.

[0071] Step 205: When the rate of pressure change is greater than or equal to a preset threshold, a pipeline leak is determined.

[0072] For example, determining a pipeline leak when the pressure change rate is greater than or equal to a preset threshold specifically includes: comparing the pressure change rate calculated in step 204 with the preset threshold. When the pressure change rate is greater than or equal to the preset threshold, it indicates an abnormally rapid drop in pipeline pressure, and a leak is determined; when the pressure change rate is less than the preset threshold, it indicates that the pipeline pressure is within the normal fluctuation range, and no leak is determined. The preset threshold can be preset based on the statistical characteristics of pressure fluctuations during normal pipeline operation, historical leak data, or engineering experience.

[0073] Specifically, the aforementioned preset threshold can be determined in advance based on the statistical characteristics of the pressure change rate under normal pipeline operation. For example, during the pipeline installation and commissioning phase, pressure data is collected over a period of time (e.g., 72 hours) during which the pipeline operates normally (without leakage). The pressure change rate at each moment is calculated using a 1-second sliding window, and the maximum or average value of this data is multiplied by a certain safety factor (e.g., 1.5~2.0) as the preset threshold. Alternatively, it can be set directly based on pressure change rate data from historical leakage events or in conjunction with engineering experience.

[0074] During real-time monitoring, the system calculates the pressure change rate point by point at a fixed frequency (e.g., 100Hz) and compares each calculated value with a preset threshold. Once the system detects that the pressure change rate continuously or instantaneously exceeds the threshold, it immediately issues a leak alarm signal and records the current time and corresponding pressure data for subsequent leak location and emergency response.

[0075] It should be noted that the preset threshold is not fixed and can be dynamically adjusted according to actual operating conditions. For example, when the operating frequency of the conveying equipment changes, the pressure fluctuation level in the pipeline may change accordingly. In this case, the threshold can be adjusted accordingly to adapt to the new operating conditions. In addition, to balance detection sensitivity and false alarm rate, multiple threshold levels can be set. When the pressure change rate exceeds the lower threshold, an early warning is triggered; when it exceeds the higher threshold, an alarm is triggered.

[0076] In some feasible embodiments, the spacing between the monitoring points in this application is not arbitrarily determined, but is set according to the theoretically calculated limit spacing based on the high damping attenuation characteristics of HDPE / POE high elasticity pipes for pressure waves.

[0077] First, the propagation speed of the pressure wave in the slurry pipe is calculated using the Koltack-Mennabry formula, as follows:

[0078] in, c This indicates the propagation speed of pressure waves in the slurry pipeline, expressed in m / s. K The bulk modulus of elasticity of fly ash slurry is expressed in Pa. ρ This indicates the density of the conveyed slurry, in kg / m³. 3 ; E This indicates the elastic modulus of the pipe, expressed in Pa. D This indicates the nominal inner diameter of the pipe, in meters (m). e Indicates the pipe wall thickness; C 1 represents the pipe wall constraint correction coefficient, which is determined by the pipe laying and fixing method.

[0079] Unlike rigid metal pipes, HDPE / POE viscoelastic pipes have an equivalent modulus of elasticity of [missing information]. E As the frequency of the pressure wave changes, the propagation speed of negative pressure waves of different frequencies becomes inconsistent, resulting in a dispersion effect, which, combined with the slurry... K , ρ Due to the characteristic of fluctuations in concentration, the pressure wave velocity inside the pipeline under this working condition can be reduced to 200~400m / s, which is much lower than that of steel pipelines.

[0080] After obtaining the propagation speed of the pressure wave c Subsequently, combining the viscoelastic pipe wall damping loss and the friction loss along the slurry, the exponential attenuation law of the pressure wave along the pipeline can be derived: the pressure amplitude decreases exponentially with the increase of the propagation distance, and the attenuation coefficient... α The propagation speed of the pressure wave in the slurry pipe described above c The damping coefficient of the pipeline and the viscosity coefficient of the medium are used to determine the damping coefficient.

[0081] Then, based on the above attenuation law, this application determines the maximum sensor spacing. The residual amplitude of the initial pressure wave signal generated at the leak point must be greater than the sensor's minimum detectable threshold when it propagates to the farthest sensor. Therefore, the maximum sensor spacing is calculated using the following formula:

[0082] in, x This represents the maximum effective spacing between sensors, in meters (m).α Pressure wave amplitude attenuation coefficient (m) - ¹); P 0 represents the initial pressure wave amplitude (Pa) generated at the leak point. P This is the minimum detectable pressure (Pa) of the pressure sensor. k This is a safety factor (usually taken as 1.2~2.0).

[0083] It should be noted that the above α=α 壁 +α 摩擦 ,in, α 壁 The pipe wall damping loss coefficient (0.002~0.005 m for HDPE / POE pipes) is given. -1 ), α 摩擦 The friction loss coefficient of the slurry along the friction path is calculated using the Darcy-Weisbach formula.

[0084] The spacing determined by the above formula ensures that the negative pressure wave generated by the leak can be effectively captured by at least one sensor before it decays to an unmeasurable threshold, thus overcoming the technical defect that the rapid attenuation of pressure waves in viscoelastic pipes makes it difficult to detect weak leak signals.

[0085] It should be noted that in the aforementioned Koltack-Mennabry formula for the propagation velocity of pressure waves, the bulk elastic modulus of the slurry... K With pulp density ρ The difference is directly determined by the slurry concentration. When the concentration changes gradually along the pipeline transport direction, it will directly lead to differences in the propagation speed of pressure waves in different pipe sections. If a single fixed wave speed is used, it will introduce significant positioning errors.

[0086] Therefore, in some embodiments, to further improve the accuracy of leak location, the pipeline leak monitoring method of this application further includes: first, obtaining the inlet concentration and outlet concentration of the pipeline; second, determining the medium concentration distribution within the pipeline based on the inlet and outlet concentrations; then, correcting the propagation velocity of the pressure wave in the pipeline based on the medium concentration distribution; and finally, determining the location of the pipeline leak based on the corrected propagation velocity of the pressure wave.

[0087] Specifically, firstly, this application utilizes Figure 1 Flow meters and slurry concentration detectors are installed at points k0 at the beginning of the pipeline and k4 at the end to collect inlet concentration, outlet concentration, inlet flow rate, and outlet flow rate. Next, based on the collected inlet concentration, outlet concentration, inlet flow rate, and outlet flow rate as boundary conditions, the concentration distribution throughout the pipeline is iteratively solved according to the partial differential equation of slurry convection and diffusion. The equation expression is as follows:

[0088] In the formula, C For medium concentration, t For time, r This represents the radial coordinate of the pipe (i.e., the distance from the central axis of the pipe to the pipe wall). u(r) Let r be the flow velocity at the radial direction of the pipe. x This represents the distance along the length of the pipe. D is the diffusion coefficient.

[0089] For example, for fly ash slurry with a mass concentration of 40% to 65%, the above diffusion coefficient... D The value range is 1×10 -5 ~5×10 -5 m 2 / s.

[0090] Based on this, the finite difference method is used for discretization, and the entire long-distance pipeline is divided into segments of 5-10m, with the average slurry concentration of each segment output. C It should be understood that the density of the slurry in each segment is calculated based on its concentration value. ρ and bulk modulus K Then, the density of the slurry was calculated. ρ and bulk modulus K By substituting the formula for pressure wave velocity back into the Kirtak-Mennabry formula, we can obtain the propagation velocity of the pressure wave in each segment. c This replaces the traditional practice of using a fixed wave velocity for the entire pipeline.

[0091] Finally, when a leak occurs, the time difference between the negative pressure wave detected by pressure sensors upstream and downstream of the leak point is used, combined with the corrected pressure wave propagation velocity for each pipe section. c A time-difference positioning algorithm is used to calculate the precise location of the leak point. This method eliminates the measurement deviation caused by the inconsistency of wave velocity along the entire pipeline due to the variation in slurry concentration, and overcomes the positioning inaccuracy problem caused by wave velocity dispersion in HDPE / POE viscoelastic pipelines, effectively improving the positioning accuracy of leak points in long-distance fly ash slurry transportation pipelines. It should be understood that this time-difference positioning algorithm adopts the existing time-difference positioning algorithm, which will not be elaborated here.

[0092] The foregoing primarily describes the solutions provided in this application from the perspective of the server. It is understood that, in order to implement the above functions, the server includes the corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0093] The foregoing mainly describes the solutions provided by the embodiments of this application. It is understood that, in order to achieve the above functions, the electronic device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0094] This application embodiment can divide the electronic device into functional units according to the above method example. For example, each function can be divided into a separate functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0095] By dividing each functional module according to its corresponding function, an exemplary embodiment of this application provides a pipeline leakage monitoring device, which can be a terminal or a chip applied to a terminal. Figure 3 A schematic diagram of the structure of a pipeline leakage monitoring device provided in an exemplary embodiment of this application is shown. Figure 3 As shown, the device 300 includes: The acquisition module 301 is used to acquire the first set of pressure parameters at different locations in the pipeline and the main pulse frequency of the conveying equipment. The processing module 302 is used to perform time-frequency transformation on the first set of pressure parameters to obtain components of multiple different frequency bands; The processing module 302 is also used to identify and remove the target component corresponding to the main pulse frequency from multiple components of different frequency bands to obtain the remaining components; The processing module 302 is also used to reconstruct a second set of pressure parameters based on the remaining components, and to determine the pressure change rate based on the second set of pressure parameters; The processing module 302 is also used to determine that a pipeline leak has occurred when the rate of pressure change is greater than or equal to a preset threshold.

[0096] In some embodiments, the acquisition module 301 is further configured to acquire pressure parameters of multiple monitoring points spaced apart along the length of the pipeline at different times, as a first set of pressure parameters; and to acquire the operating frequency and number of plungers of the conveying equipment, and determine the main pulse frequency based on the operating frequency and the number of plungers.

[0097] In some embodiments, the processing module 302 is further configured to perform discrete wavelet transform on the first set of pressure parameters, decomposing the first set of pressure parameters into an approximate component and multiple detail components to obtain multiple components with different frequency bands; wherein each detail component corresponds to a different frequency band range.

[0098] In some embodiments, the processing module 302 is further configured to determine the frequency band range in which the main pulse frequency is located; Among multiple components with different frequency bands, the component whose frequency band falls within the frequency band of the main pulse frequency is identified as the target component; The target component is removed from components in multiple different frequency bands to obtain the remaining components.

[0099] In some embodiments, the processing module 302 is further configured to perform inverse wavelet transform on the remaining components to obtain a second set of pressure parameters; The pressure change rate is determined based on the pressure difference and time interval between adjacent time points of the second set of pressure parameters.

[0100] In some embodiments, the processing module 302 is further configured to obtain the inlet concentration and the outlet concentration of the pipeline; The concentration distribution of the medium within the pipeline is determined based on the inlet and outlet concentrations. Based on the medium concentration distribution, the propagation speed of pressure waves in the pipeline is corrected; The location of the pipeline leak is determined based on the propagation speed of the corrected pressure wave.

[0101] Figure 4 A schematic diagram of the structure of an electronic device provided in an exemplary embodiment of this application is shown. For example... Figure 4 As shown, the electronic device 400 includes at least one processor 401 and a memory 402 coupled to the processor 401. The processor 401 can perform the corresponding steps in the methods disclosed in the embodiments of this application.

[0102] The processor 401 described above can also be called a Central Processing Unit (CPU), which can be an integrated circuit chip with signal processing capabilities. Each step in the method disclosed in this application can be implemented by the integrated logic circuitry in the processor 401 or by software instructions. The processor 401 can be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this application can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can be located in the memory 402, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor 401 reads the information in the memory 402 and, in conjunction with its hardware, completes the steps of the above method.

[0103] Furthermore, the various operations / processes according to this application, when implemented via software and / or firmware, can be transmitted from a storage medium or network to a computer system with a dedicated hardware architecture, for example, Figure 5 The computer system 500 shown is equipped with the programs that constitute the software. When various programs are installed, the computer system is able to perform various functions, including functions such as those mentioned above. Figure 5 A schematic diagram of the structure of a computer system provided in an exemplary embodiment of this application is shown.

[0104] Computer system 500 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0105] like Figure 5As shown, the computer system 500 includes a computing unit 501, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. The RAM 503 may also store various programs and data required for the operation of the computer system 500. The computing unit 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0106] Multiple components in the computer system 500 are connected to the I / O interface 505, including: an input unit 506, an output unit 507, a storage unit 508, and a communication unit 509. The input unit 506 can be any type of device capable of inputting information into the computer system 500. The input unit 506 can receive input digital or character information and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 507 can be any type of device capable of presenting information and may include, but is not limited to, a monitor, speaker, video / audio output terminal, vibrator, and / or printer. The storage unit 508 may include, but is not limited to, a hard disk and an optical disk. The communication unit 509 allows the computer system 500 to exchange information / data with other devices via a network such as the Internet, and may include, but is not limited to, a modem, network card, infrared communication device, wireless communication transceiver, and / or chipset, such as Bluetooth™ devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0107] The computing unit 501 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above. For example, in some embodiments, the methods disclosed in the embodiments of this application can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on an electronic device via ROM 502 and / or communication unit 509. In some embodiments, the computing unit 501 can be configured to perform the methods disclosed in the embodiments of this application by any other suitable means (e.g., by means of firmware).

[0108] This application also provides a computer-readable storage medium, wherein when the instructions in the computer-readable storage medium are executed by the processor of an electronic device, the electronic device is able to perform the methods disclosed in the embodiments of this application.

[0109] The computer-readable storage medium in this application embodiment may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. The aforementioned computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specifically, the aforementioned computer-readable storage medium may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing.

[0110] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0111] This application also provides a computer program product, including a computer program, wherein the computer program, when executed by a processor, implements the methods disclosed in the embodiments of this application.

[0112] In embodiments of this application, computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include, but are not limited to, object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)), or it can be connected to an external computer.

[0113] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0114] The modules, components, or units described in the embodiments of this application can be implemented in software or hardware. The names of the modules, components, or units do not necessarily constitute a limitation on the module, component, or unit itself.

[0115] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that can be used include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0116] The above description is merely an embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

[0117] While specific embodiments of this application have been described in detail by way of examples, those skilled in the art should understand that the above examples are for illustrative purposes only and are not intended to limit the scope of this application. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of this application. The scope of this application is defined by the appended claims.

Claims

1. A method for monitoring pipeline leaks, characterized in that, A method applicable to a pipeline conveying system equipped with conveying equipment for conveying a medium into the pipeline includes: Obtain the first set of pressure parameters at different locations in the pipeline and the main pulse frequency of the conveying equipment; The first set of pressure parameters is subjected to time-frequency transformation to obtain components in multiple different frequency bands; Identify and remove the target component corresponding to the main pulse frequency from the multiple components of different frequency bands to obtain the remaining components; The second set of pressure parameters is reconstructed based on the remaining components, and the pressure change rate is determined based on the second set of pressure parameters. When the rate of change of pressure is greater than or equal to a preset threshold, it is determined that the pipeline is leaking.

2. The method for monitoring pipeline leakage according to claim 1, characterized in that, The acquisition of the first set of pressure parameters at different locations in the pipeline and the main pulse frequency of the conveying equipment includes: At different times, pressure parameters of multiple monitoring points distributed at intervals along the length of the pipeline are acquired as the first set of pressure parameters; The operating frequency and number of plungers of the conveying device are obtained, and the main pulse frequency is determined based on the operating frequency and the number of plungers.

3. The method for monitoring pipeline leakage according to claim 1, characterized in that, The time-frequency transformation of the first set of pressure parameters yields multiple components in different frequency bands, including: The first set of pressure parameters is subjected to discrete wavelet transform to decompose the first set of pressure parameters into an approximate component and multiple detail components to obtain multiple components with different frequency bands; wherein each detail component corresponds to a different frequency band range.

4. The method for monitoring pipeline leakage according to claim 1, characterized in that, The process of identifying and removing the target component corresponding to the main pulse frequency from the multiple components of different frequency bands to obtain the remaining components includes: Determine the frequency band range of the main pulse frequency; The component whose frequency band falls within the frequency band of the main pulse frequency among the multiple components of different frequency bands is identified as the target component; The target component is removed from the components of the multiple different frequency bands to obtain the remaining components.

5. The method for monitoring pipeline leakage according to claim 1, characterized in that, The process of reconstructing a second set of pressure parameters based on the remaining components and determining the pressure change rate based on the second set of pressure parameters includes: Perform inverse wavelet transform on the remaining components to obtain the second set of pressure parameters; The pressure change rate is determined based on the pressure difference and time interval between adjacent time points of the second set of pressure parameters.

6. The method for monitoring pipeline leakage according to any one of claims 1 to 5, characterized in that, The method further includes: Obtain the inlet concentration and the outlet concentration of the pipeline; The medium concentration distribution within the pipeline is determined based on the inlet concentration and the outlet concentration. Based on the medium concentration distribution, the propagation speed of the pressure wave in the pipeline is corrected; The location of the pipeline leak is determined based on the propagation speed of the corrected pressure wave.

7. A device for monitoring pipeline leaks, characterized in that, include: The acquisition module is used to acquire the first set of pressure parameters at different locations in the pipeline and the main pulse frequency of the conveying equipment. The processing module is used to perform time-frequency transformation on the first set of pressure parameters to obtain multiple components in different frequency bands; The processing module is also used to identify and remove the target component corresponding to the main pulse frequency from the multiple components of different frequency bands to obtain the remaining components; The processing module is also used to reconstruct a second set of pressure parameters based on the remaining components, and to determine the pressure change rate based on the second set of pressure parameters; The processing module is also used to determine that the pipeline is leaking when the pressure change rate is greater than or equal to a preset threshold.

8. An electronic device, characterized in that, include: processor; as well as, Memory for stored programs; The program includes instructions that, when executed by the processor, cause the processor to perform the pipeline leakage monitoring method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the pipeline leakage monitoring method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program, wherein the computer program, when executed by a computer processor, implements the pipeline leakage monitoring method according to any one of claims 1 to 6.

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