Rapid monitoring and positioning method for leakage point of low-low-temperature economizer

Abstract

The invention discloses a rapid monitoring and positioning method for a leakage point of a low-low-temperature economizer. The method comprises the steps that S1, a monitoring mechanism is arranged, wherein an infrared thermal imaging detection mechanism is arranged on the outer wall of the low-low-temperature economizer; a sonic sensor array is arranged around the low-low-temperature economizer; s2, data fusion analysis: fusing and analyzing infrared thermal imaging and sound wave detection data obtained from a monitoring mechanism; s3, anomaly detection: further analyzing and processing the fused data, and determining the position of a leakage point according to an analysis result; s4, performing strong positioning on the abnormal region or signal by using a phase difference positioning method, and finally determining a leakage point; and S5, when a leakage point is monitored, triggering an alarm signal, and generating a detailed leakage point position and leakage degree report. According to the invention, based on further analysis and research on existing technical problems, through combination of infrared thermal imaging and sound wave detection technologies, rapid and accurate monitoring and positioning of leakage points are realized.

Description

Technical Field

[0001] The present application belongs to the technical field of low-temperature economizers, and specifically relates to a method for quickly monitoring and locating leakage points of low-temperature economizers. Background Art

[0002] With the development of the power industry, low-temperature economizers are important auxiliary equipment for power station boilers. The stability and reliability of their operating status are of great significance to ensuring the safe and economical operation of the entire power station. However, in actual operation, low-temperature economizers are prone to leakage due to long-term influence of high temperature, high pressure and corrosive media. Leakage not only leads to waste of media, but also damages the equipment itself and the surrounding environment, and may even cause safety accidents in serious cases.

[0003] The prior art discloses a system and method for the alarm and prevention of wear and leakage of a low-temperature economizer, including a flue, a compressed air input pipeline, a plurality of bellows, a plurality of groups of dummy pipes and a pressure transmitter for detecting the gas pressure in the bellows; the low-temperature economizer body is located in the flue, one bellows corresponds to a group of dummy pipes, one end of each dummy pipe in each group of dummy pipes is sealed and connected to the inner wall of the flue side, the other end of each dummy pipe in each group of dummy pipes passes through the wall of the flue side and is connected to the corresponding bellows, the compressed air input pipeline is connected to each bellows, and each group of dummy pipes and the low-temperature economizer body are distributed in sequence along the direction of flue gas circulation. The system and method can prevent wear and leakage of the low-temperature economizer.

[0004] Traditional low-temperature economizer leakage monitoring methods mainly rely on manual inspections and regular testing. These methods have problems such as long monitoring cycles, low efficiency, and insufficient accuracy. It is difficult to detect and handle leakage failures in a timely and effective manner. In addition, the pressure monitoring mentioned in the prior art is very easy to change due to the flue gas flow rate, resulting in frequent detection of false leaks. Therefore, how to achieve rapid monitoring and accurate positioning of low-temperature economizer leakage points has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The present application provides a method for quickly monitoring and locating leakage points of a low-temperature economizer, aiming to solve the problem that it is difficult to timely and effectively discover and handle leakage faults in the prior art.

[0006] A method for quickly monitoring and locating a leakage point of a low-temperature economizer, the method comprising:

[0007] S1: Setting up a monitoring mechanism: Setting up an infrared thermal imaging detection mechanism on the outer wall of the low-temperature economizer;

[0008] Arrange an array of acoustic wave sensors around the low-temperature economizer;

[0009] S2: Data fusion analysis: Fusion and analysis of infrared thermal imaging and acoustic wave detection data obtained from monitoring agencies;

[0010] S3: Anomaly detection: further analyze and process the fused data, and determine the location of the leakage point based on the analysis results;

[0011] S4: Use the phase difference positioning method to strongly locate the abnormal area or signal and finally determine the leakage point;

[0012] S5: When a leak is detected, an alarm signal is triggered and a detailed report on the leak location and leak extent is generated.

[0013] Optionally, the S2 specifically includes the following steps:

[0014] S2.1: Data collection: Use an infrared thermal imager to scan the target area, obtain the temperature distribution image of the equipment surface, start the acoustic wave detection equipment, record the acoustic wave signal generated by the leak, and pre-process the temperature distribution image and acoustic wave signal;

[0015] S2.2: Time synchronization: synchronize the time data of the temperature distribution image and the acoustic wave signal;

[0016] S2.3: Spatial registration: Register the temperature distribution image and the acoustic wave signal to ensure the spatial consistency of the two;

[0017] S2.4: Feature extraction: extract temperature features related to leakage from the temperature distribution image, and extract features related to leakage from the acoustic wave signal;

[0018] S2.5: Use a data fusion algorithm to fuse the temperature distribution image and the acoustic wave signal data.

[0019] Optionally, the S2.5 includes:

[0020] S2.5.1: Determine state variables: According to the data characteristics of the temperature distribution image and the acoustic wave signal, determine that the state variables to be fused are temperature and acoustic wave intensity;

[0021] S2.5.2: Establish state transfer equation: According to the dynamic characteristics of the system, establish the transfer equation of the state variables changing with time;

[0022] S2.5.3: Establish observation equation: Take the temperature distribution image and the acoustic wave signal data as observation values, establish observation equation, and describe the relationship between the observation values ​​and state variables;

[0023] S2.5.4: Set initial conditions: Set the initial values ​​of the state variables and the initial values ​​of their error covariance matrix;

[0024] S2.5.5: Kalman filter iteration: Use the state transfer equation to predict the state variables and their error covariance matrix at the current moment, calculate the Kalman gain, use the observed value and the Kalman gain to update the estimated value of the state variables and their error covariance matrix, use the updated state variables and error covariance matrix as the initial conditions for the next moment, and repeat the prediction and update process until the set number of iterations is reached or the termination condition is met;

[0025] S2.5.6: Through the Kalman filter iteration process, the fused state variable estimate and its error covariance matrix are obtained.

[0026] Optionally, the state transfer equation is a recursive equation, and the setting form is x(k+1)=f(x(k),u(k));

[0027] Where x(k) represents the state variable at time k, and u(k) represents the input or control variable at time k.

[0028] Optionally, the method further includes S6: establishing an equipment status database to store historical monitoring data and analysis results.

[0029] Optionally, the method further includes S7: result verification, if the verification result is consistent with the positioning result, confirming the location of the leakage point;

[0030] If there is any inconsistency, further investigation and analysis will be conducted and feedback will be sent to S2 for reanalysis.

[0031] Optionally, the initial value of the state variable is: the temperature value between the monitoring mechanism and the outer wall of the low-temperature economizer after the low-temperature economizer is in operation.

[0032] Optionally, the acoustic wave sensor array includes at least 2 acoustic wave generators and 9 acoustic wave receivers.

[0033] Optionally, the S4 comprises the following steps:

[0034] S4.1: The receiver records the received signal data, including the signal strength and phase;

[0035] S4.2: Data preprocessing, processing the measured phase difference data to eliminate noise and errors;

[0036] S4.3: Establish a positioning model based on the phase difference data and the geometric relationship between the receivers;

[0037] S4.4: Use the iterative method to solve the equations in the positioning model to obtain the position coordinates of the signal source and thus determine the leak point.

[0038] Compared with the prior art, this application has at least the following beneficial effects:

[0039] This application is based on further analysis and research of existing technical problems, and realizes rapid and accurate monitoring and positioning of leakage points by combining infrared thermal imaging and acoustic wave detection technology;

[0040] 1. By setting up infrared thermal imaging detection mechanism and acoustic wave sensor array, the operating status of the low-temperature economizer can be monitored in real time. Once an abnormality is found, the alarm signal will be triggered immediately, which greatly shortens the time to discover leakage faults.

[0041] 2. The data fusion algorithm is used to fuse and analyze the data of infrared thermal imaging and acoustic wave detection, which improves the accuracy and reliability of leak point positioning. At the same time, the phase difference positioning method is used to strongly locate abnormal areas or signals, further ensuring the accuracy of the leak point location. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A flowchart of a method for rapid monitoring and locating a low-temperature economizer leak provided in one embodiment of the present application;

[0043] Figure 2 A flowchart of data fusion analysis in a method for rapid monitoring and locating leakage points of a low-temperature economizer provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0045] The present application provides a method for rapid monitoring and locating a low-temperature economizer leakage point, comprising the following steps:

[0046] S1: Setting up monitoring mechanism: Setting up infrared thermal imaging detection mechanism on the outer wall of low-temperature economizer. Since heat will be lost at the leakage point, resulting in a local temperature drop, the area with abnormal temperature can be visually observed through infrared thermal imaging, so as to preliminarily determine the location of the leakage point;

[0047] On the basis of infrared thermal imaging, the acoustic wave detection technology is further used to accurately locate the leakage point. When the medium leaks, a specific acoustic wave signal will be generated. The acoustic wave sensor array arranged around the low-temperature economizer receives and analyzes these acoustic wave signals, and the acoustic wave positioning algorithm is used to determine the specific location of the leakage point.

[0048] S2: Data fusion analysis: The infrared thermal imaging and acoustic wave detection data obtained from the monitoring agency are integrated and analyzed to improve the accuracy and reliability of leak point location;

[0049] The specific steps include:

[0050] S2.1: Data collection: Use an infrared thermal imager to scan the target area, obtain the temperature distribution image of the equipment surface, start the acoustic wave detection equipment, record the acoustic wave signal generated by the leak, and pre-process the temperature distribution image and acoustic wave signal;

[0051] S2.2: Time synchronization: synchronize the time data of the temperature distribution image and the acoustic wave signal so that they can correspond accurately in subsequent analysis;

[0052] S2.3: Spatial registration: Register the temperature distribution image and the acoustic wave signal to ensure that the two are spatially consistent;

[0053] S2.4: Feature extraction: Extract temperature features related to leakage from the temperature distribution image, such as abnormal temperature area, temperature gradient, etc.; extract features related to leakage from the acoustic wave signal, such as acoustic wave frequency, amplitude, arrival time difference, etc.;

[0054] S2.5: Use data fusion algorithm to fuse the temperature distribution image and the acoustic wave signal data. The fused data will contain richer information, which will help improve the accuracy and reliability of leak point location.

[0055] Specifically, the steps of fusing the temperature distribution image and the acoustic wave signal using Kalman filtering include:

[0056] S2.5.1: Determine state variables: According to the data characteristics of the temperature distribution image and the acoustic wave signal, determine the state variables that need to be fused. Here, temperature and acoustic wave intensity are selected;

[0057] S2.5.2: Establish state transfer equation: According to the dynamic characteristics of the system, establish the transfer equation of the state variable changing with time, where the recursive formula is selected, and the form can be set as x(k+1)=f(x(k),u(k)), where x(k) represents the state variable at time k, and u(k) represents the input or control variable at time k;

[0058] S2.5.3: Establish observation equation: Take the temperature distribution image and the acoustic wave signal data as observation values, establish observation equation, and describe the relationship between the observation values ​​and state variables;

[0059] S2.5.4: Set initial conditions: Set the initial values ​​of the state variables and the initial values ​​of their error covariance matrix. The initial values ​​of the state variables are generally based on the temperature between the monitoring mechanism and the outer wall of the low-temperature economizer after the low-temperature economizer is working, and the initial value of the error covariance matrix is ​​set based on current experience;

[0060] S2.5.5: Kalman filter iteration: Use the state transfer equation to predict the state variables and their error covariance matrix at the current moment, calculate the Kalman gain, which represents the influence of the observation value on the state variable estimate, use the observation value and the Kalman gain to update the estimated value of the state variable and its error covariance matrix, use the updated state variables and error covariance matrix as the initial conditions for the next moment, and repeat the prediction and update process until the set number of iterations is reached or the termination condition is met;

[0061] S2.5.6: Through the Kalman filter iteration process, the fused state variable estimation value and its error covariance matrix are obtained. These fused data contain complementary information of infrared thermal imaging and acoustic wave detection data, which improves the accuracy and reliability of the data;

[0062] S3: Anomaly detection: further analyze and process the fused data, and determine the location, size and other parameters of the leak point based on the analysis results;

[0063] S4: Use the phase difference positioning method to strongly locate the abnormal area or signal and finally determine the leakage point;

[0064] Specifically include:

[0065] S4.1: The receiver records the received signal data, including the signal strength and phase;

[0066] S4.2: Data preprocessing, processing the measured phase difference data to eliminate noise and errors;

[0067] S4.3: Establish a positioning model based on the phase difference data and the geometric relationship between the receivers;

[0068] S4.4: Use the iterative method to solve the equations in the positioning model to obtain the position coordinates of the signal source, thereby determining the leak point;

[0069] S5: When a leak is detected, an alarm signal is triggered and a detailed report on the location and extent of the leak is generated;

[0070] S6: Establish an equipment status database to store historical monitoring data and analysis results to provide reference for subsequent equipment maintenance;

[0071] S7: Result verification: verify the positioning result through field investigation or other detection methods. If the verification result is consistent with the positioning result, the location of the leak point is confirmed; if not, further investigation and analysis are required.

[0072] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A method for rapid monitoring and locating leakage points of low-temperature economizers, characterized in that: The method comprises: S1: Setting up a monitoring mechanism: Setting up an infrared thermal imaging detection mechanism on the outer wall of the low-temperature economizer; Arrange an array of acoustic wave sensors around the low-temperature economizer; S2: Data fusion analysis: Fusion and analysis of infrared thermal imaging and acoustic wave detection data obtained from monitoring agencies; S3: Anomaly detection: further analyze and process the fused data, and determine the location of the leakage point based on the analysis results; S4: Use the phase difference positioning method to strongly locate the abnormal area or signal and finally determine the leakage point; S5: When a leak is detected, an alarm signal is triggered and a detailed report on the leak location and leak extent is generated.

2. A method for rapid monitoring and locating leakage points of a low-temperature economizer according to claim 1, characterized in that: The S2 specifically includes the following steps: S2.1: Data collection: Use an infrared thermal imager to scan the target area, obtain the temperature distribution image of the equipment surface, start the acoustic wave detection equipment, record the acoustic wave signal generated by the leak, and pre-process the temperature distribution image and acoustic wave signal; S2.2: Time synchronization: synchronize the time data of the temperature distribution image and the acoustic wave signal; S2.3: Spatial registration: Register the temperature distribution image and the acoustic wave signal to ensure the spatial consistency of the two; S2.4: Feature extraction: extract temperature features related to leakage from the temperature distribution image, and extract features related to leakage from the acoustic wave signal; S2.5: Use a data fusion algorithm to fuse the temperature distribution image and the acoustic wave signal data.

3. A method for rapid monitoring and locating leakage points of a low-temperature economizer according to claim 1, characterized in that: The S2.5 includes: S2.5.1: Determine state variables: According to the data characteristics of the temperature distribution image and the acoustic wave signal, determine that the state variables to be fused are temperature and acoustic wave intensity; S2.5.2: Establish state transfer equation: According to the dynamic characteristics of the system, establish the transfer equation of the state variables changing with time; S2.5.3: Establish observation equation: Take the temperature distribution image and the acoustic wave signal data as observation values, establish observation equation, and describe the relationship between the observation values ​​and state variables; S2.5.4: Set initial conditions: Set the initial values ​​of the state variables and the initial values ​​of their error covariance matrix; S2.5.5: Kalman filter iteration: Use the state transfer equation to predict the state variables and their error covariance matrix at the current moment, calculate the Kalman gain, use the observed value and the Kalman gain to update the estimated value of the state variables and their error covariance matrix, use the updated state variables and error covariance matrix as the initial conditions for the next moment, and repeat the prediction and update process until the set number of iterations is reached or the termination condition is met; S2.5.6: Through the Kalman filter iteration process, the fused state variable estimate and its error covariance matrix are obtained.

4. A method for rapid monitoring and locating leakage points of a low-temperature economizer according to claim 3, characterized in that: The state transfer equation is a recursive equation, and the setting form is x(k+1)=f(x(k),u(k)); Where x(k) represents the state variable at time k, and u(k) represents the input or control variable at time k.

5. The method for rapid monitoring and locating leakage points of a low-temperature economizer according to claim 1, characterized in that: The method further comprises S6: establishing a device status database to store historical monitoring data and analysis results.

6. A method for rapid monitoring and locating leakage points of a low-temperature economizer according to claim 5, characterized in that: The method further comprises S7: result verification, if the verification result is consistent with the positioning result, confirming the location of the leakage point; If there is any inconsistency, further investigation and analysis will be conducted and feedback will be sent to S2 for reanalysis.

7. A method for rapid monitoring and locating leakage points of a low-temperature economizer according to claim 3, characterized in that: The initial value of the state variable is: the temperature value between the monitoring mechanism and the outer wall of the low-temperature economizer after the low-temperature economizer is in operation.

8. A method for rapid monitoring and locating leakage points of a low-temperature economizer according to claim 1, characterized in that: The acoustic wave sensor array includes at least two acoustic wave generators and nine acoustic wave receivers.

9. A method for rapid monitoring and locating leakage points of a low-temperature economizer according to claim 1, characterized in that: The S4 comprises the following steps: S4.1: The receiver records the received signal data, including the signal strength and phase; S4.2: Data preprocessing, processing the measured phase difference data to eliminate noise and errors; S4.3: Establish a positioning model based on the phase difference data and the geometric relationship between the receivers; S4.4: Use the iterative method to solve the equations in the positioning model to obtain the position coordinates of the signal source and thus determine the leak point.

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