Gas leakage detection method and device

Abstract

The invention discloses a gas leakage detection method and device. The method comprises the following steps: acquiring a plurality of gas concentration sequences at the same detection time from detection equipment; performing background de-noising processing on each gas concentration sequence to obtain a net concentration sequence after the background signal is removed; respectively solving peak points of each net concentration sequence, and ranking the peak points according to the amplitudes of the peak points to obtain the ranking of the ith peak point; fusing the peak point rankings of the gases to obtain a comprehensive rank; a discrete sequence with the peak value of each net concentration sequence as a dependent variable and the comprehensive ranking as an independent variable is constructed, a sudden drop point with the descending amplitude of the adjacent peak point exceeding a set threshold value in the sequence is calculated, and the sudden drop point and the peak point in front of the sudden drop point are gas leakage points; the method has the advantages that the interference of environmental noise and background signals can be effectively reduced and the detection accuracy and sensitivity of gas leakage can be improved by combining the peak point fusion of various gas concentration sequences and the background denoising and sudden drop point detection method.

Description

Technical Field

[0001] The present invention belongs to the technical field of gas detection, and in particular relates to a gas leakage detection method and device. Background Art

[0002] Traditional gas leak detection methods typically rely on a single gas sensor, resulting in limited detection accuracy and susceptibility to background noise. In recent years, multi-gas sensor fusion detection technology has gradually gained attention, but existing technologies still suffer from inaccurate detection and high false alarm rates in complex environments. Therefore, an efficient and accurate multi-gas leak detection method is urgently needed. Summary of the Invention

[0003] The purpose of the present invention is to solve the problem that in actual detection, the gas concentration sequence may be interfered with by environmental noise, resulting in inaccurate detection data. Background denoising processing can eliminate the interference of environmental noise, making the net concentration sequence more reliable, thereby improving the accuracy of gas leak detection. This solution uses a sliding window method to denoise the background signal, thereby obtaining more accurate concentration change data.

[0004] The present invention achieves the above-mentioned purpose through the following technical solutions: A gas leak detection method includes:

[0005] Step 1: Obtain multiple gas concentration sequences with the same detection time from the detection equipment;

[0006] Step 2: Perform background denoising on each gas concentration sequence to obtain a net concentration sequence after removing the background signal;

[0007] Step 3: Calculate the peak points of each net concentration sequence respectively, rank the peak points according to their amplitudes, and obtain the ranking of the i-th peak point;

[0008] Step 4: Combine the peak point rankings of each gas to obtain a comprehensive ranking;

[0009] Step 5: Construct a discrete sequence with the peak value of each net concentration sequence as the dependent variable and the comprehensive ranking as the independent variable, and calculate the sudden drop point in the sequence where the drop amplitude of adjacent peak points exceeds the set threshold. The sudden drop point and the peak point before it are both gas leakage points.

[0010] Furthermore, the method also includes the step of preprocessing the data obtained from the detection device: supplementing missing data, removing duplicate data, and eliminating abnormal data.

[0011] Furthermore, the background denoising method includes: inputting each gas concentration sequence into a sliding time window of equal length, calculating the minimum value of the data in the sliding time window at each moment; inputting the minimum value into a sliding time window of equal length, calculating the average value of the data in the sliding time window at each moment, and obtaining the background value; calculating the net concentration sequence = original concentration sequence - background value, and obtaining the net concentration sequence after removing the background signal.

[0012] Furthermore, the calculation formula for the sliding time window length is: N = int(l×f / v), where N is the window length, which is a multiple of the data acquisition period or the number of data in the sliding time window; l is the detection distance covered by the sliding time window, in meters; v is the moving speed of the detection device, in meters per second; f is the data acquisition frequency, in Hz, and int represents rounding operation.

[0013] Furthermore, the comprehensive ranking method includes: ranking in a weighted sum manner to obtain a comprehensive ranking, wherein the weighting coefficient is dynamically adjusted according to the gas type and the detection environment.

[0014] In a second aspect, the present invention provides a gas leak detection device: a data acquisition module for acquiring a plurality of gas concentration sequences at the same detection time from a detection device;

[0015] The background denoising module is used to perform background denoising on each gas concentration sequence to obtain a net concentration sequence after removing the background signal;

[0016] The ranking fusion module is used to solve the peak points of each net concentration sequence separately, rank the peak points according to their amplitudes, and fuse the rankings of each gas to obtain a comprehensive ranking;

[0017] The leakage detection module is used to construct a discrete sequence with the peak value of each net concentration sequence as the dependent variable and the comprehensive ranking as the independent variable, and calculate the sudden drop point where the drop amplitude of adjacent peak points in the sequence exceeds the set threshold. The sudden drop point and the peak point before it are both gas leakage points.

[0018] Furthermore, the device also includes a preprocessing module for preprocessing the data obtained from the detection equipment: supplementing missing data, removing duplicate data, and eliminating abnormal data.

[0019] Furthermore, the background denoising method includes:

[0020] Input each gas concentration sequence into a sliding time window of equal length, and calculate the minimum value of the data in the sliding time window at each moment;

[0021] Input the minimum value into a sliding time window of equal length, calculate the average value of the data in the sliding time window at each moment, and obtain the background value;

[0022] Calculate the net concentration sequence = original concentration sequence - background value to obtain the net concentration sequence after removing the background signal.

[0023] Furthermore, the calculation formula for the sliding time window length is: N = int(l×f / v), where N is the window length, which is a multiple of the data acquisition period or the number of data in the sliding time window; l is the detection distance covered by the sliding time window, in meters; v is the moving speed of the detection device, in meters per second; f is the data acquisition frequency, in Hz, and int represents rounding operation.

[0024] Furthermore, a comprehensive ranking is obtained by ranking in a weighted sum manner, wherein the weighting coefficient is dynamically adjusted according to the gas type and the detection environment.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] 1. By fusing the peak points of multiple gas concentration sequences, combined with background denoising and sudden drop point detection methods, this method can effectively reduce interference from environmental noise and background signals, improving the accuracy and sensitivity of gas leak detection. A comprehensive ranking and dynamically adjusted weighting coefficient method enables accurate location of leaks of different gases in different detection environments, particularly in complex environments.

[0027] 2. The dynamic adjustment of the weighting coefficients in this method automatically optimizes the algorithm based on the gas type and detection environment, allowing the detection device to maintain high accuracy and adaptability in different environments and gas types. Therefore, whether in industrial, residential, or other application scenarios, it can effectively monitor and locate gas leaks;

[0028] 3. Through early pre-processing (such as supplementing missing data, removing duplicate data, and eliminating abnormal data) and background denoising, the quality and stability of the data are greatly improved. This processing method can effectively eliminate unnecessary noise and irrelevant signals, reduce the risk of false alarms, ensure the reliability of the test results, and provide a solid foundation for subsequent accurate leak point determination;

[0029] 4. This method uses parallel processing of multiple gas concentration sequences and rapid peak point analysis to rapidly acquire key leak data points. Efficient calculations are performed based on comprehensive rankings. Combined with background denoising using a sliding time window and peak point drop detection, this method enables real-time monitoring and rapid response, significantly shortening the time from detection to leak location and improving the efficiency of emergency handling and response.

[0030] 5. The detection device integrates multiple modules (such as data acquisition, background denoising, ranking fusion, and leak detection) and automatically performs data analysis and judgment, eliminating the need for manual intervention. This makes the detection process more automated and intelligent. Through preprocessing and dynamic weighting adjustment, the system can adaptively adjust to different environments, reducing the workload of manual adjustments and improving the overall intelligence of the detection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Schematic diagram of the detection method of the present invention;

[0032] Figure 2 is a schematic diagram of various gas concentration curves of the present invention;

[0033] Figure 3 Schematic diagram of a time domain curve including a peak point according to the present invention. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] In the description of the present invention, it should be understood that the terms "longitudinal", "transverse", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0036] Combine Figure 1-Figure 3 As shown, a gas leak detection method and device:

[0037] Example 1:

[0038] This embodiment provides a specific implementation plan of a gas leak detection method to more clearly illustrate the working principle and steps of the method.

[0039] Step 1: Data Acquisition

[0040] First, a detection device is set up to continuously sample the concentrations of multiple gases within a specific detection area. The detection device can collect concentration data of different gas types within the same time interval. For example, the detection device can simultaneously obtain concentration sequence data of gases such as methane (CH4), ammonia (NH3) and carbon monoxide (CO). The concentration data of each gas at the same time point is stored and prepared for subsequent processing. The data acquisition frequency is set to 10Hz, that is, data is collected 10 times per second.

[0041] Step 2: Background denoising

[0042] In order to eliminate the interference of environmental noise on the detection results, background denoising is performed on each collected gas concentration sequence. Specifically, each gas concentration sequence is first input into a sliding time window with a window length of 5 seconds. The sliding window processes the gas concentration data at each moment:

[0043] Calculate the minimum value of the data in each sliding window;

[0044] These minimum values are then input into a new sliding time window, and the average value of the data in the window is calculated to obtain the background value;

[0045] By calculating the net concentration sequence, that is, subtracting the background value from the original concentration sequence, the net concentration sequence after removing the background signal is obtained.

[0046] Step 3: Peak point extraction and ranking

[0047] In the net concentration sequence after background denoising, all peak points are found. By applying the peak detection algorithm to each net concentration sequence, the peak points in each gas concentration sequence are extracted, and the amplitude of each peak point is calculated. The peak points of each gas are ranked according to the amplitude. For example, for the methane concentration sequence, the peak points with larger amplitudes are ranked in front, and the peak points with smaller amplitudes are ranked in the back. Similarly, the same processing is performed on the ammonia and carbon monoxide concentration sequences to obtain the corresponding peak point rankings.

[0048] Step 4: Overall ranking

[0049] To improve detection accuracy, the peak point rankings of all gases are integrated. A weight is assigned to the ranking of each gas based on its concentration sequence and the amplitude of its peak point. The weight is dynamically adjusted based on the type of gas and the detection environment. For example, a methane gas leak may be more dangerous than an ammonia leak, so the methane peak point ranking will be given a higher weight in the comprehensive ranking. Finally, a weighted sum method is used to obtain a comprehensive peak point ranking.

[0050] Step 5: Detection of sudden drop points

[0051] Based on the comprehensive ranking, the peak value of each gas is used as the dependent variable and the comprehensive ranking is used as the independent variable to construct a discrete sequence. By calculating the decline amplitude of adjacent peak points in the discrete sequence, the sudden drop points where the decline amplitude between adjacent peak points exceeds the set threshold are detected. The threshold is set to 5%, that is, if the decline amplitude between two adjacent peak points exceeds 5%, it is regarded as a sudden drop point.

[0052] After the sudden drop point is detected, the sudden drop point and the peak point before it are marked as possible gas leakage points in combination with the position of the previous peak point.

[0053] Example 2: Application of the detection device

[0054] This embodiment provides a device for implementing the above-mentioned gas leak detection method.

[0055] Data acquisition module

[0056] The data acquisition module is used to obtain concentration data of multiple gases from the detection equipment. The module can obtain concentration sequences of gases such as methane, ammonia and carbon monoxide from the detection equipment according to a set time interval (for example, 10 times per second) and transmit the data to the background denoising module.

[0057] Background denoising module

[0058] This module performs background denoising on the concentration sequence of each gas through a sliding time window. The calculation unit in the module first calculates the minimum value of the data at each moment, and averages the minimum value through another sliding time window to obtain the background value. Finally, the background value is removed from the original concentration sequence to obtain the net concentration sequence.

[0059] Ranking Fusion Module

[0060] This module detects the peak points of each gas concentration sequence after denoising and ranks them according to the amplitude of the peak points. After integrating the rankings of each gas, the module generates a comprehensive ranking and transmits it to the leak detection module.

[0061] Leak detection module

[0062] The leakage detection module uses the net concentration peak point of each gas as the dependent variable and the comprehensive ranking as the independent variable to construct a discrete sequence. It determines whether a sudden drop point occurs based on the decline amplitude of adjacent peak points. If the amplitude of the sudden drop point exceeds the set threshold, the module marks the sudden drop point and the peak point before it as a gas leakage point, and promptly issues an alarm or takes other safety measures.

[0063] Preprocessing module

[0064] The preprocessing module is responsible for cleaning the acquired data, including supplementing missing data, removing duplicate data, and eliminating abnormal data to ensure the effectiveness and accuracy of subsequent processing.

[0065] Sliding time window length calculation

[0066] In background denoising, the length N of the sliding time window is calculated using the formula: N = int(l × f / v), where l is the detection distance covered by the sliding time window, f is the data acquisition frequency, and v is the moving speed of the detection device. This calculation formula ensures that the window size can adapt to different detection environments and device configurations.

[0067] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

[0068] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A gas leak detection method, characterized in that: The following steps are involved: Step 1: Obtain multiple gas concentration sequences with the same detection time from the detection equipment; Step 2: Perform background denoising on each gas concentration sequence to obtain a net concentration sequence after removing the background signal; Step 3: Calculate the peak points of each net concentration sequence respectively, rank the peak points according to their amplitudes, and obtain the ranking of the i-th peak point; Step 4: Combine the peak point rankings of each gas to obtain a comprehensive ranking; Step 5: Construct a discrete sequence with the peak value of each net concentration sequence as the dependent variable and the comprehensive ranking as the independent variable, and calculate the sudden drop point in the sequence where the drop amplitude of adjacent peak points exceeds the set threshold. The sudden drop point and the peak point before it are both gas leakage points.

2. A gas leak detection method according to claim 1, characterized in that: The method further comprises the steps of pre-processing the data obtained from the detection device: supplementing missing data, removing duplicate data, and eliminating abnormal data.

3. A gas leak detection method according to claim 2, characterized in that: The background denoising method includes: inputting each gas concentration sequence into a sliding time window of equal length, calculating the minimum value of the data in the sliding time window at each moment; inputting the minimum value into a sliding time window of equal length, calculating the average value of the data in the sliding time window at each moment, and obtaining the background value; calculating the net concentration sequence = the original concentration sequence - the background value, and obtaining the net concentration sequence after removing the background signal.

4. A gas leak detection method according to claim 3, characterized in that: The calculation formula for the sliding time window length is: N = int(l×f / v), where N is the window length, which is a multiple of the data acquisition period or the number of data in the sliding time window; l is the detection distance covered by the sliding time window, in meters; v is the moving speed of the detection device, in meters per second; f is the data acquisition frequency, in Hz, and int represents rounding operation.

5. A gas leak detection method according to claim 4, characterized in that: The comprehensive ranking method includes: ranking in a weighted sum manner to obtain a comprehensive ranking, wherein the weighting coefficient is dynamically adjusted according to the gas type and the detection environment.

6. A gas leak detection device according to claim 5, characterized in that: A data acquisition module is used to obtain multiple gas concentration sequences at the same detection time from the detection equipment; The background denoising module is used to perform background denoising on each gas concentration sequence to obtain a net concentration sequence after removing the background signal; The ranking fusion module is used to solve the peak points of each net concentration sequence separately, rank the peak points according to their amplitudes, and fuse the rankings of each gas to obtain a comprehensive ranking; The leakage detection module is used to construct a discrete sequence with the peak value of each net concentration sequence as the dependent variable and the comprehensive ranking as the independent variable, and calculate the sudden drop point where the drop amplitude of adjacent peak points in the sequence exceeds the set threshold. The sudden drop point and the peak point before it are both gas leakage points.

7. A gas leak detection device according to claim 6, characterized in that: The device also includes a preprocessing module for preprocessing the data obtained from the detection equipment: supplementing missing data, removing duplicate data, and eliminating abnormal data.

8. A gas leak detection device according to claim 7, characterized in that: The background denoising method includes: Input each gas concentration sequence into a sliding time window of equal length, and calculate the minimum value of the data in the sliding time window at each moment; Input the minimum value into a sliding time window of equal length, calculate the average value of the data in the sliding time window at each moment, and obtain the background value; Calculate the net concentration sequence = original concentration sequence - background value to obtain the net concentration sequence after removing the background signal.

9. A gas leak detection device according to claim 8, characterized in that: The calculation formula for the sliding time window length is: N = int(l×f / v), where N is the window length, which is a multiple of the data acquisition period or the number of data in the sliding time window; l is the detection distance covered by the sliding time window, in meters; v is the moving speed of the detection device, in meters per second; f is the data acquisition frequency, in Hz, and int represents rounding.

10. A gas leak detection device according to claim 9, characterized in that: The comprehensive ranking method includes: ranking in a weighted sum manner to obtain a comprehensive ranking, wherein the weighting coefficient is dynamically adjusted according to the gas type and the detection environment.

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