Thermal power plant pipeline leakage detection device and method based on acoustic emission technology

Abstract

The invention relates to a thermal power plant pipeline leakage detection device and method based on an acoustic emission technology, and relates to the technical field of thermal power plant equipment detection, and the thermal power plant pipeline leakage detection device comprises an acoustic emission sensor module, a signal conditioning module, a data acquisition module, a data analysis and processing module, a leakage positioning module, an alarm module and a power supply module. The high-sensitivity acoustic emission sensor and a corresponding signal processing algorithm are adopted, weak acoustic emission signals can be accurately captured, and the pipeline leakage detection precision is effectively improved. And the leakage positioning module can accurately determine the specific position of the leakage point on the pipeline by using a time difference positioning algorithm, so that accurate information is provided for maintenance personnel, and the maintenance time is shortened. The alarm module can send out sound and light alarm signals in time, remote alarm is achieved, workers are reminded to handle the pipeline leakage problem in time, and accident expansion is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal power plant equipment detection, and in particular to a thermal power plant pipeline leakage detection device and method based on acoustic emission technology. Background Art

[0002] In thermal power plants, pipeline systems are responsible for transporting vital media such as steam, water, and fuel. Leaks in these pipelines not only waste energy but can also cause safety incidents such as fires and explosions, seriously threatening the safe and stable operation of the power plant and the lives of workers.

[0003] Currently, traditional pipeline leak detection methods mainly include pressure monitoring and flow monitoring. The pressure monitoring method determines whether there is a leak by monitoring changes in pressure within the pipeline. However, for small leaks, the pressure change is not obvious, making it difficult to accurately detect. The flow monitoring method determines the leak by comparing the flow rate at the pipeline inlet and outlet. However, this method is significantly affected by factors such as the flow state of the medium within the pipeline, and its detection accuracy is limited.

[0004] Acoustic emission (AE) is a dynamic nondestructive testing technology that generates elastic waves, or AE signals, when materials deform or fracture. When a pipeline leaks, fluid ejected from the leak point generates an AE signal, which can be detected using AE technology. However, existing AE-based pipeline leak detection devices and methods suffer from poor anti-interference capabilities, low detection accuracy, and an inability to accurately locate leaks in the complex environments of thermal power plants. Summary of the Invention

[0005] Purpose of the invention: To provide a thermal power plant pipeline leakage detection device based on acoustic emission technology, and further provide a detection method for the thermal power plant pipeline leakage detection device based on acoustic emission technology, so as to solve the above-mentioned problems existing in the prior art.

[0006] Technical solution: A thermal power plant pipeline leakage detection device based on acoustic emission technology, including seven parts: acoustic emission sensor module, signal conditioning module, data acquisition module, data analysis and processing module, leakage location module, alarm module and power supply module.

[0007] The acoustic emission sensor module includes a plurality of acoustic emission sensors evenly installed on the outer surface of the pipeline to be detected in the thermal power plant, which is used to collect the acoustic emission signal generated by the pipeline leakage and convert it into an electrical signal;

[0008] The signal conditioning module is connected to the acoustic emission sensor module and is used to amplify and filter the electrical signal output by the sensor;

[0009] The data acquisition module is connected to the signal conditioning module to collect and digitally process the conditioned signal;

[0010] The data analysis and processing module is connected to the data acquisition module, receives the collected digital signals, and uses algorithms such as wavelet transform and spectrum analysis to analyze and process them to determine whether the pipeline is leaking and assess the severity of the leak;

[0011] The leakage location module is connected to the data analysis and processing module, and calculates the location of the leakage point using a time difference positioning algorithm based on the arrival time difference of the signals collected by multiple acoustic emission sensors;

[0012] The alarm module is connected to the data analysis and processing module, and emits an audible and visual alarm signal and realizes remote alarm when a pipeline leak is detected;

[0013] The power supply module provides a stable power supply for the acoustic emission sensor module, signal conditioning module, data acquisition module, data analysis and processing module, leakage location module and alarm module.

[0014] In a further embodiment, the acoustic emission sensor has high sensitivity and wide frequency response characteristics, with a sensitivity of 30-36 mv / Pa and a frequency response range of 4 kHz-18 kHz.

[0015] In a further embodiment, the amplification circuit of the signal conditioning module adopts an integrated operational amplifier, and the filtering circuit adopts a combination of a low-pass filter and a high-pass filter to remove noise and interference signals in a predetermined frequency range.

[0016] In a further embodiment, the data acquisition module uses a multifunctional synchronous data acquisition card with a sampling rate of 180kS / s and a resolution of 16-bit ADC.

[0017] In a further embodiment, the data analysis and processing module adopts a modular industrial computer, is installed with special signal processing software, and integrates wavelet transform and spectrum analysis algorithms.

[0018] In a further embodiment, the leakage location algorithm of the leakage location module adopts a time difference location algorithm, which is implemented by writing a corresponding program.

[0019] In a further embodiment, the alarm information is sent to the staff's mobile phone or a monitoring center via the GPRS network.

[0020] In a further embodiment, the power module has an output voltage of 24 VDC and a power of 350 W, and is internally provided with overvoltage and overcurrent protection circuits.

[0021] A detection method for a thermal power plant pipeline leakage detection device based on acoustic emission technology comprises the following steps:

[0022] S1. Install multiple acoustic emission sensors evenly on the outer surface of the pipeline to be inspected in a thermal power plant, and record the installation position of each sensor;

[0023] S2, the acoustic emission sensor collects the acoustic emission signal generated by the pipeline leakage in real time and converts it into an electrical signal. After amplification and filtering by the signal conditioning module, it is collected and digitized by the data acquisition module;

[0024] S3, the data analysis and processing module performs wavelet transform and spectrum analysis on the collected digital signals, extracts the characteristic parameters of the acoustic emission signals, and determines whether the pipeline is leaking and evaluates the severity of the leakage based on the characteristic parameters;

[0025] S4. When it is determined that a pipeline leak occurs, the leak location module calculates the location of the leak point using a time difference positioning algorithm based on the arrival time difference of the signals collected by multiple acoustic emission sensors;

[0026] S5. When a pipeline leak is detected, the alarm module emits an audible and visual alarm signal and sends the alarm information to the staff's mobile phone or monitoring center. The staff will take appropriate maintenance measures based on the location of the leak and the severity of the leak.

[0027] In a further embodiment, in step S4, the leakage locating step specifically includes:

[0028] S401, by processing the signal collected by each sensor, determining the time when the acoustic emission signal arrives at each sensor;

[0029] S402, calculating the difference in signal arrival time between different sensors;

[0030] S403, establishing a mathematical equation for leak point location based on the propagation speed and time difference of the acoustic emission signal in the pipeline;

[0031] S404: Obtain the specific location of the leak point on the pipeline by solving the positioning equation.

[0032] Beneficial effects: The present invention relates to a device and method for detecting pipeline leakage in a thermal power plant based on acoustic emission technology, which has the following beneficial effects:

[0033] High detection accuracy: The present invention adopts a highly sensitive acoustic emission sensor and corresponding signal processing algorithm, which can accurately capture weak acoustic emission signals and effectively improve the accuracy of pipeline leakage detection.

[0034] Strong anti-interference ability: The signal conditioning module filters the collected signals to remove noise and interference components, so that the device can still work stably and reliably in the complex environment of a thermal power plant.

[0035] Accurately locate the leak point: The leak location module uses a time difference positioning algorithm to accurately determine the specific location of the leak point on the pipeline, providing maintenance personnel with accurate information and shortening maintenance time.

[0036] Real-time alarm: The alarm module can send out sound and light alarm signals in time and realize remote alarm to remind staff to deal with pipeline leakage problems in time to avoid the expansion of accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a schematic diagram of the composition framework of the pipeline leakage detection device based on acoustic emission technology described in the present invention.

[0038] Figure 2 The figure is a flow chart of the detection method of the thermal power plant pipeline leakage detection device based on acoustic emission technology according to the present invention.

[0039] Figure 3 The figure is a flow chart of the leakage location steps of the present invention. DETAILED DESCRIPTION

[0040] In the following description, numerous specific details are provided to provide a more thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced without one or more of these details. In other instances, certain technical features well known in the art are not described to avoid confusion with the present invention.

[0041] The applicant believes that the existing pipeline leakage detection devices and methods based on acoustic emission technology have problems such as poor anti-interference ability, low detection accuracy, and inability to accurately locate leakage points in the complex environment of thermal power plants.

[0042] To this end, the applicant has designed a thermal power plant pipeline leak detection device and method based on acoustic emission technology. This device, which employs a highly sensitive acoustic emission sensor and corresponding signal processing algorithm, can accurately capture weak acoustic emission signals, effectively improving the accuracy of pipeline leak detection. Furthermore, using a time-difference positioning algorithm, it can precisely determine the specific location of the leak on the pipeline, providing maintenance personnel with accurate information and shortening repair time.

[0043] The present invention relates to a thermal power plant pipeline leak detection device based on acoustic emission technology. The device primarily comprises seven components: an acoustic emission sensor module, a signal conditioning module, a data acquisition module, a data analysis and processing module, a leak location module, an alarm module, and a power supply module. The acoustic emission sensor module comprises multiple acoustic emission sensors uniformly mounted on the outer surface of the thermal power plant pipeline to be inspected. These sensors collect acoustic emission signals generated by pipeline leaks and convert them into electrical signals. The signal conditioning module, connected to the acoustic emission sensor module, amplifies and filters the electrical signals output by the sensors. The data acquisition module, connected to the signal conditioning module, collects and digitizes the conditioned signals. The data analysis and processing module, connected to the data acquisition module, receives the collected digital signals and analyzes and processes them using algorithms such as wavelet transform and spectrum analysis to determine whether a pipeline leak has occurred and assess the severity of the leak. The leak location module, connected to the data analysis and processing module, calculates the location of the leak using a time difference location algorithm based on the arrival time differences of the signals collected by the multiple acoustic emission sensors. The alarm module, connected to the data analysis and processing module, emits an audible and visual alarm signal when a pipeline leak is detected, enabling remote alarming. The power supply module provides a stable power supply for the acoustic emission sensor module, signal conditioning module, data acquisition module, data analysis and processing module, leakage location module and alarm module.

[0044] The acoustic emission sensor has high sensitivity and wide-frequency response characteristics, with a sensitivity of 30-36mv / Pa and a frequency response range of 4kHz-18kHz.

[0045] The amplification circuit of the signal conditioning module adopts an integrated operational amplifier, and the filtering circuit adopts a combination of a low-pass filter and a high-pass filter to remove low-frequency noise and interference signals below 4kHz and remove high-frequency noise and interference signals above 18kHz.

[0046] The data acquisition module uses a multifunctional synchronous data acquisition card with a sampling rate of 180kS / s and a resolution of 16 bits ADC.

[0047] The data analysis and processing module adopts a modular industrial computer, is installed with special signal processing software, and integrates wavelet transformation and spectrum analysis algorithms.

[0048] The leakage location algorithm of the leakage location module adopts a time difference location algorithm, which is realized by writing a corresponding program.

[0049] The alarm information is sent to the staff's mobile phone or monitoring center via the GPRS network.

[0050] The power module has an output voltage of 24VDC and a power of 350W, and is internally provided with overvoltage and overcurrent protection circuits.

[0051] Based on the above-mentioned thermal power plant pipeline leakage detection device based on acoustic emission technology, the present invention proposes a detection method for the thermal power plant pipeline leakage detection device based on acoustic emission technology, and the specific steps are as follows:

[0052] First, multiple acoustic emission sensors are evenly installed on the outer surface of the pipeline to be inspected in the thermal power plant, and the installation position of each sensor is recorded;

[0053] Next, the acoustic emission sensor collects the acoustic emission signal generated by the pipeline leakage in real time and converts it into an electrical signal. After amplification and filtering by the signal conditioning module, it is collected and digitized by the data acquisition module.

[0054] Subsequently, the data analysis and processing module performs wavelet transform and spectrum analysis on the collected digital signals to extract the characteristic parameters of the acoustic emission signals. Based on the characteristic parameters, it determines whether the pipeline is leaking and assesses the severity of the leak.

[0055] Then, when it is determined that a pipeline leak occurs, the leak location module calculates the location of the leak using a time difference positioning algorithm based on the arrival time difference of the signals collected by multiple acoustic emission sensors;

[0056] At the same time, when a pipeline leak is detected, the alarm module emits an audible and visual alarm signal and sends the alarm information to the staff's mobile phone or monitoring center. The staff will take appropriate maintenance measures based on the location of the leak and the severity of the leak.

[0057] The leak location steps include:

[0058] First, the signal collected by each sensor is processed to determine the time when the acoustic emission signal arrives at each sensor;

[0059] Then, the difference in signal arrival time between different sensors is calculated;

[0060] Next, a mathematical equation for leak location is established based on the propagation speed and time difference of the acoustic emission signal in the pipeline;

[0061] Finally, by solving the positioning equation, the specific location of the leak point on the pipeline is obtained.

[0062] In a further preferred embodiment, the present invention proposes a detection method for a thermal power plant pipeline leakage detection device based on acoustic emission technology, and the specific implementation method is as follows:

[0063] Sensor placement: Before installing the acoustic emission sensors, clean the pipe surface to ensure good contact between the sensors and the pipe surface. Install the sensors evenly across the pipe surface according to design requirements, and use a total station or other measuring equipment to accurately record the installation location of each sensor.

[0064] Signal Acquisition: Start the data acquisition system and set sampling parameters, such as sampling rate and time. The acoustic emission sensor collects the acoustic emission signals generated by pipeline leaks in real time and converts them into electrical signals. The signal conditioning module amplifies and filters the electrical signals, and the data acquisition module collects and converts them into digital signals.

[0065] Signal Analysis and Processing: The data analysis and processing module performs a wavelet transform on the collected digital signal, decomposing it into frequency sub-bands. By analyzing the energy distribution of each sub-band, the characteristic parameters of the acoustic emission signal are extracted. Simultaneously, the signal undergoes spectral analysis to determine the primary frequency components. Based on these characteristic parameters and frequency components, the presence of a pipeline leak is determined and the severity of the leak is assessed.

[0066] Leak Location: If a pipeline leak is detected, the leak location module uses a time-difference location algorithm to calculate the leak's location based on the arrival time differences of signals collected by multiple sensors. First, a signal processing algorithm determines the arrival time of the acoustic emission signal at each sensor. Then, the arrival time differences between the signals from different sensors are calculated. Next, a mathematical equation for leak location is established based on the propagation speed of the acoustic emission signal in the pipeline and the time difference. Finally, the location equation is solved to determine the specific location of the leak on the pipeline.

[0067] Alarm and Action: When a pipeline leak is detected, the alarm module emits an audible and visual alarm signal and simultaneously transmits the alarm information to the operator's mobile phone or monitoring center via the wireless communication module. Based on the location and severity of the leak, the operator develops a corresponding repair plan and promptly repairs the pipeline.

[0068] In a further preferred embodiment, the above detection method is explained in detail as follows:

[0069] Step 1: Install multiple acoustic emission sensors evenly on the outer surface of the pipeline to be inspected in the thermal power plant, and record the installation position of each sensor.

[0070] Sensor selection: Choose an acoustic emission sensor with appropriate sensitivity and frequency response range based on the power plant's pipeline material (such as carbon steel, stainless steel, etc.), pipe diameter, operating temperature, pressure, and other operating conditions. For example, for high-temperature pipelines, a high-temperature-resistant acoustic emission sensor is required.

[0071] Determine the number of sensors to be installed: The number of sensors to be installed is determined by the length, shape, and complexity of the pipeline. Generally speaking, for short, straight pipelines, install a sensor every certain distance (e.g., 2-5 meters). For complex branching or curved pipelines, increase the number of sensors installed at key locations such as branch points and elbows to ensure full coverage of the area to be inspected.

[0072] Installation location records: Use high-precision measurement tools (such as laser rangefinders) to accurately measure the relative position of each sensor to specific reference points on the pipeline (such as the pipeline starting point, valve, etc.) and record it in the database. At the same time, each sensor is assigned a unique number to facilitate subsequent data processing and management.

[0073] In step 2, the acoustic emission sensor collects the acoustic emission signal generated by the pipeline leakage in real time and converts it into an electrical signal. After amplification and filtering by the signal conditioning module, it is collected and digitized by the data acquisition module.

[0074] Signal acquisition: The acoustic emission sensor collects the acoustic emission signal generated by the pipeline leak in real time at a certain sampling frequency (e.g., 100kHz-1MHz). The sampling frequency should be determined based on the frequency range of the acoustic emission signal to ensure that the characteristic information of the signal can be accurately captured.

[0075] Signal Conditioning: The signal conditioning module amplifies and filters the weak electrical signals output by the sensor. The amplification factor is adjusted based on the strength of the sensor output signal and the input requirements of the subsequent data acquisition module. Filtering uses a bandpass filter to remove noise and interference signals while retaining the effective frequency components of the acoustic emission signal.

[0076] Data acquisition and digitization: The data acquisition module converts the conditioned analog signal into a digital signal and stores it in a certain format (such as a binary file) on the local hard disk or transmits it to the data analysis and processing module for further processing.

[0077] Step 3: The data analysis and processing module performs wavelet transform, spectrum analysis and other processing on the collected digital signals, extracts the characteristic parameters of the acoustic emission signals, and determines whether the pipeline is leaking and evaluates the severity of the leakage based on the characteristic parameters.

[0078] Wavelet transform: Performs wavelet decomposition on the collected digital signal, breaking it down into different frequency subbands. Appropriate wavelet basis functions (such as Daubechies wavelets) and the number of decomposition levels are selected to highlight the characteristic information of the acoustic emission signal. The time-frequency characteristics of the signal are extracted by analyzing the amplitude and energy of the wavelet coefficients.

[0079] Spectrum analysis: Use Fast Fourier Transform (FFT) to perform spectrum analysis on the signal to obtain the signal spectrum. Analyze the peak frequency, frequency distribution and other characteristics in the spectrum to determine the main frequency components of the acoustic emission signal.

[0080] Characteristic parameter extraction: Extract characteristic parameters from the signal after wavelet transform and spectrum analysis, such as signal amplitude, energy, frequency, duration, etc. Establish a characteristic parameter database to store characteristic parameter values ​​under normal operating conditions and different leakage levels.

[0081] Leakage determination and severity assessment: Extracted characteristic parameters are compared with normal operating parameters in the characteristic parameter database, and methods such as threshold judgment and pattern recognition are used to determine whether a pipeline leak has occurred. Based on the degree of change in characteristic parameters, empirical formulas or machine learning models are used to assess the severity of the leak, such as minor, moderate, or severe.

[0082] Step 4: When it is determined that a pipeline leak occurs, the leak location module calculates the location of the leak point using a time difference positioning algorithm based on the arrival time difference of the signals collected by multiple acoustic emission sensors.

[0083] (1) Determine the time when the acoustic emission signal reaches each sensor by processing the signal collected by each sensor

[0084] Signal preprocessing: De-noise the signals collected by each sensor, using methods such as wavelet threshold denoising and adaptive filtering to remove noise interference and improve signal quality.

[0085] Arrival time determination: Various methods are used to determine the time when the acoustic emission signal arrives at each sensor, such as the threshold method and correlation analysis method. The threshold method sets a signal amplitude threshold. When the signal amplitude exceeds the threshold, the signal is considered to have arrived. The correlation analysis method performs a correlation analysis between the signal collected by the sensor and a reference signal, and determines the signal arrival time by calculating the peak position of the correlation coefficient.

[0086] (2) Calculate the difference in signal arrival time between different sensors

[0087] Time Difference Calculation: Based on the determined arrival time of the signal at each sensor, calculate the difference in signal arrival time between any two sensors. To improve the calculation accuracy, you can use the method of taking the average of multiple measurements.

[0088] (3) Based on the propagation speed and time difference of the acoustic emission signal in the pipeline, a mathematical equation for leak point location is established

[0089] Propagation velocity determination: The propagation velocity of the acoustic emission signal in the pipeline is determined through experimental measurement or theoretical calculation. Experimental measurement can be performed by artificially creating an acoustic emission source on the pipeline and measuring the propagation time of the signal between different sensors to calculate the propagation velocity. Theoretical calculation can be performed based on parameters such as the pipe material, diameter, and wall thickness, using relevant acoustic theory formulas.

[0090] Mathematical equation establishment: Based on the propagation characteristics and time delay of the acoustic emission signal in the pipeline, a mathematical equation for leak location is established. For straight pipelines, the equation can be established using the hyperbolic positioning method; for complex pipelines, the equation can be established using a three-dimensional spatial positioning model.

[0091] (4) By solving the positioning equation, the specific location of the leak point on the pipeline is obtained

[0092] Equation solving: Numerical calculation methods are used to solve the mathematical equations for leak point location, such as the Newton iteration method and the least squares method. During the solution process, the convergence and stability of the equations need to be considered to ensure the accuracy of the solution.

[0093] Result verification: Verify the leak point location obtained by the solution, and use other detection methods (such as ultrasonic detection, infrared thermal imaging detection, etc.) for auxiliary detection to ensure the reliability of the positioning results.

[0094] Step 5: When a pipeline leak is detected, the alarm module emits an audible and visual alarm signal and sends the alarm information to the staff's mobile phone or monitoring center. The staff will take appropriate maintenance measures based on the location of the leak and the severity of the leak.

[0095] Sound and light alarm: The alarm module uses high-brightness indicator lights and high-decibel alarms to emit sound and light alarm signals to alert on-site staff.

[0096] Alarm information transmission: Alarm information (including leak location, leak severity, etc.) is sent to the staff's mobile phone or monitoring center through wireless communication modules (such as GPRS, WiFi, etc.). Alarm information can be sent via SMS, APP push, etc.

[0097] Developing repair measures: Staff will develop appropriate repair measures based on the location and severity of the leak. Minor leaks can be treated with temporary plugging measures; moderate and severe leaks require immediate cessation of pipeline operations for comprehensive repairs.

[0098] In a further preferred embodiment, the leak location step in the above detection method is specifically detailed as follows:

[0099] T401, Signal Processing:

[0100] Signal preprocessing: De-noise the signal collected by each acoustic emission sensor, and use a filter (such as a low-pass filter or a band-pass filter) to remove high-frequency noise and interference signals.

[0101] Signal feature extraction: Extract characteristic parameters of each sensor signal, such as peak value, energy, frequency, etc., to facilitate subsequent time judgment.

[0102] T402, time difference calculation:

[0103] Timestamp recording: The timestamp of the acoustic emission signal arrival is recorded for each sensor to ensure time synchronization.

[0104] Calculate time difference: By comparing the timestamps of signals received by different sensors, the time difference (Δt) of the signals arriving at each sensor is calculated.

[0105] T403, establish positioning equation:

[0106] Propagation velocity determination: Determine the propagation velocity (v) of the acoustic emission signal in the pipeline based on the properties of the medium in the pipeline (such as temperature, pressure, etc.).

[0107] Mathematical model establishment: Based on the installation positions and time differences of multiple sensors, a mathematical equation for leak point location is established. Triangulation positioning method or multi-point positioning method can be used. The specific equation form is:

[0108] d ij =v·Δt ij

[0109] Among them, d ij is the distance between sensors i and j, Δt ij is the difference in signal arrival time.

[0110] T404, Solve the positioning equation

[0111] Solving the equations: Use the least squares method or other numerical solution methods to solve the established equations and obtain the coordinates (x, y, z) of the leakage point.

[0112] Positioning accuracy verification: Verify the accuracy of the positioning algorithm by comparing the actual location of the known leak point, and adjust the algorithm parameters as needed to improve positioning accuracy.

[0113] Another implementation of alarm and response:

[0114] Alarm signal generation: When the leak point is successfully located, the alarm module generates an audible and visual alarm signal to ensure that on-site staff can discover it in time.

[0115] Information transmission: The alarm information is sent to the staff's mobile phone or monitoring center via wireless network or other communication methods, including the specific location of the leak, the severity of the leak and the recommended treatment measures.

[0116] Emergency response: Based on the information received, staff will quickly assess the on-site situation and take appropriate maintenance measures, such as closing valves, evacuating personnel, and conducting on-site inspections.

[0117] By refining the above steps, the accuracy and response speed of leak detection can be improved, ensuring the safe operation of thermal power plants.

[0118] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the present invention itself. Various changes may be made to it in form and detail without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A thermal power plant pipeline leakage detection device based on acoustic emission technology, characterized by include: The acoustic emission sensor module includes multiple acoustic emission sensors evenly installed on the outer surface of the pipeline to be inspected in the thermal power plant, which is used to collect the acoustic emission signals generated by pipeline leakage and convert them into electrical signals; A signal conditioning module, connected to the acoustic emission sensor module, for amplifying and filtering the electrical signal output by the sensor; A data acquisition module, connected to the signal conditioning module, collects and digitizes the conditioned signal; A data analysis and processing module is connected to the data acquisition module, receives the collected digital signals, and uses algorithms such as wavelet transform and spectrum analysis to analyze and process them to determine whether a pipeline leaks and assess the severity of the leak; A leakage location module is connected to the data analysis and processing module and calculates the location of the leakage point using a time difference location algorithm based on the arrival time difference of the signals collected by multiple acoustic emission sensors; An alarm module is connected to the data analysis and processing module, and emits an audible and visual alarm signal and realizes remote alarm when a pipeline leak is detected; The power supply module provides a stable power supply for the acoustic emission sensor module, signal conditioning module, data acquisition module, data analysis and processing module, leakage location module and alarm module.

2. The thermal power plant pipeline leakage detection device based on acoustic emission technology according to claim 1 is characterized by: The acoustic emission sensor has high sensitivity and wide-frequency response characteristics, with a sensitivity of 30-36mv / Pa and a frequency response range of 4kHz-18kHz.

3. The thermal power plant pipeline leakage detection device based on acoustic emission technology according to claim 1 is characterized by: The amplifying circuit of the signal conditioning module adopts an integrated operational amplifier, and the filtering circuit adopts a combination of a low-pass filter and a high-pass filter to remove noise and interference signals within a predetermined frequency range.

4. The thermal power plant pipeline leakage detection device based on acoustic emission technology according to claim 1 is characterized by: The data acquisition module uses a multifunctional synchronous data acquisition card with a sampling rate of 180kS / s and a resolution of 16 bits ADC.

5. The thermal power plant pipeline leakage detection device based on acoustic emission technology according to claim 1 is characterized by: The data analysis and processing module adopts a modular industrial computer, is installed with special signal processing software, and integrates wavelet transformation and spectrum analysis algorithms.

6. The thermal power plant pipeline leakage detection device based on acoustic emission technology according to claim 1 is characterized by: The leakage location algorithm of the leakage location module adopts a time difference location algorithm, which is realized by writing a corresponding program.

7. The thermal power plant pipeline leakage detection device based on acoustic emission technology according to claim 1 is characterized by: The alarm information is sent to the staff's mobile phone or monitoring center via the GPRS network.

8. The thermal power plant pipeline leakage detection device based on acoustic emission technology according to claim 1 is characterized by: The power module has an output voltage of 24VDC and a power of 350W, and is internally provided with overvoltage and overcurrent protection circuits.

9. A detection method for a thermal power plant pipeline leakage detection device based on acoustic emission technology according to any one of claims 1 to 8, characterized in that The following steps are involved: S1. Install multiple acoustic emission sensors evenly on the outer surface of the pipeline to be inspected in a thermal power plant, and record the installation position of each sensor; S2, the acoustic emission sensor collects the acoustic emission signal generated by the pipeline leakage in real time and converts it into an electrical signal. After amplification and filtering by the signal conditioning module, it is collected and digitized by the data acquisition module; S3, the data analysis and processing module performs wavelet transform and spectrum analysis on the collected digital signals, extracts the characteristic parameters of the acoustic emission signals, and determines whether the pipeline is leaking and evaluates the severity of the leakage based on the characteristic parameters; S4. When it is determined that a pipeline leak occurs, the leak location module calculates the location of the leak point using a time difference positioning algorithm based on the arrival time difference of the signals collected by multiple acoustic emission sensors; S5. When a pipeline leak is detected, the alarm module emits an audible and visual alarm signal and sends the alarm information to the staff's mobile phone or monitoring center. The staff will take appropriate maintenance measures based on the location of the leak and the severity of the leak.

10. The detection method of a thermal power plant pipeline leakage detection device based on acoustic emission technology according to claim 9, characterized in that: In step S4, the leakage location step specifically includes: S401, by processing the signal collected by each sensor, determining the time when the acoustic emission signal arrives at each sensor; S402, calculating the difference in signal arrival time between different sensors; S403, establishing a mathematical equation for leak point location based on the propagation speed and time difference of the acoustic emission signal in the pipeline; S404: Obtain the specific location of the leak point on the pipeline by solving the positioning equation.

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