An intelligent inspection and digital control method and device for a gas drainer

Abstract

The present application provides a method and device for intelligent inspection and digital management and control of a gas drainer, which are applied to the technical field of intelligent inspection and digital management and control of gas drainers. By detecting in real time and converting the liquid level height into an electrical signal, detecting the environmental noise parameters and pipeline corrosion parameters, optimized signal frequency and voltage control parameters are obtained; an electrical signal is output according to the optimized signal frequency and voltage control parameters, and then the output electrical signal is converted into a guided wave signal, and the guided wave signal is converted into a radio frequency signal and transmitted, completing the conversion of the signal form again, realizing the wireless transmission of liquid level monitoring information, and finally achieving the purpose of intelligent inspection and digital management and control of the gas drainer. Therefore, this solution constructs a low-cost, low-power, and highly reliable method for intelligent inspection and digital management and control of the drainer, and has the advantage of simultaneously meeting the requirements of accurate liquid level monitoring and long-term independent operation.

Description

Technical Field

[0001] This application relates to the technical field of intelligent inspection and digital management and control of gas drainers, and particularly to a method and device for intelligent inspection and digital management and control of gas drainers. Background Art

[0002] The underground gas pipeline network in old urban areas undertakes the important responsibility of urban energy transportation. However, with the increase of the operation years, the problems of pipeline aging and corrosion are becoming increasingly prominent, resulting in a significant increase in the risk of gas leakage. In order to ensure the safe and stable operation of the gas pipeline network, as a key accessory equipment, the drainer is widely used to remove the condensate water and impurities accumulated in the pipeline, preventing pipeline blockage and corrosion. However, the leakage problem of the old pipeline network makes it easy for gas to penetrate into the soil around the drainer, forming a potential explosive environment.

[0003] Traditional intelligent inspection devices for drainers usually use non-intrinsically safe sensors and wireless communication modules for liquid level monitoring and data transmission. In the above explosive environment, these electronic devices have great safety hazards. Once electric sparks or overheating occur, it is very easy to ignite the leaked gas, causing serious safety accidents. Although using intrinsically safe sensors is a necessary measure to ensure safety, the existing intrinsically safe sensors generally have technical limitations such as low sensitivity and high power consumption, and it is difficult to meet the requirements of accurate liquid level monitoring and long-term independent operation at the same time. In addition, the manual inspection method is inefficient, and the inspection personnel face potential safety risks. Therefore, realizing the remote wireless monitoring and digital management of the gas drainer liquid level has become an inevitable trend.

[0004] In the complex underground pipeline network environment in old urban areas with explosion risks, how to break through the constraints of the performance of intrinsically safe sensors themselves, overcome the problems of underground environment wireless signal attenuation and interference, and design an intrinsically safe drainer liquid level remote monitoring device with low power consumption, high reliability, low cost and easy large-scale deployment has become a key technical problem to be solved urgently in the intelligent transformation of the old urban area gas pipeline network.

[0005] In view of the above problems, the existing technology needs to be improved urgently. Summary of the Invention

[0006] In view of the deficiencies of the above prior art, this application provides a method and device for intelligent inspection and digital management and control of gas drainers, which are applied to the technical field of intelligent inspection and digital management and control of gas drainers, and have the advantages of meeting the requirements of accurate liquid level monitoring and long-term independent operation at the same time, and improving the intelligent management and control of the old urban area gas pipeline network.

[0007] In the first aspect, a method for intelligent inspection and digital management and control of gas drainers, the method includes the steps:

[0008] S1: Detect the liquid level height in the gas drainer in real time and convert the liquid level height into an electrical signal;

[0009] S2: Detect the noise intensity of the environment around the drainer and the corrosion condition of the metal drain pipe in real time, and output the environmental noise parameters and pipeline corrosion parameters;

[0010] S3: Receive the environmental noise parameters and the pipeline corrosion parameters, and calculate the optimized signal frequency and voltage control parameters;

[0011] S4: Output the electrical signal according to the optimized signal frequency and voltage control parameters;

[0012] S5: Convert the output electrical signal into a guided wave signal to propagate along the metal drain pipe;

[0013] S6: Receive the guided wave signal, convert the guided wave signal into a radio frequency signal and transmit it.

[0014] An intelligent inspection and digital control method for gas drainers proposed in this application. In step S1, the real-time detection of the liquid level height is performed and the liquid level height is converted into an electrical signal, realizing the preliminary acquisition of liquid level information and the conversion of signal forms, laying a foundation for subsequent signal processing and transmission. In step S2, the real-time detection of the noise intensity of the environment around the drainer and the corrosion condition of the metal drain pipe is performed, and the environmental noise parameters and pipeline corrosion parameters are output. The purpose is to obtain the information of the environment where the drainer is located and the state of the pipeline itself, providing an environmental basis for the optimization of subsequent signal transmission parameters. In step S3, the environmental noise parameters and pipeline corrosion parameters output in step S2 are received, and the optimized signal frequency and voltage control parameters are calculated, realizing the adaptive adjustment of signal transmission parameters to adapt to complex environments and pipeline condition changes and ensuring signal transmission quality. In step S4, the electrical signal is output according to the optimized signal frequency and voltage control parameters calculated in step S3, ensuring that the output electrical signal is optimized and adjusted and can better adapt to environmental and pipeline conditions. In step S5, the output electrical signal is converted into a guided wave signal, and the guided wave signal is propagated along the metal drain pipe, using the metal drain pipe as a signal transmission medium to realize the directional transmission of the signal. In step S6, the guided wave signal propagating along the metal drain pipe is received, and the guided wave signal is converted into a radio frequency signal and transmitted, completing the re-conversion of the signal form, realizing the wireless transmission of liquid level monitoring information, and finally achieving the purpose of intelligent inspection and digital control of gas drainers. Therefore, this solution constructs a low-cost, low-power, and highly reliable intelligent inspection and digital control method for drainers, realizing the real-time, environment-adaptive, and wireless transmission of liquid level information, having the advantages of simultaneously meeting accurate liquid level monitoring and long-term independent operation, and improving the safe operation level and intelligent management ability of gas pipe networks in old urban areas.

[0015] Further, step S2 includes:

[0016] S21: Collect the noise intensity of the surrounding environment of the gas drainer in real time, perform a fast Fourier transform on the noise intensity to obtain the noise power spectral density, and output the noise power spectral density as the environmental noise parameter;

[0017] S22: Detect the corrosion potential and corrosion current at different positions of the metal drain pipe in real time, calculate the corrosion rate according to the corrosion potential and the corrosion current, obtain the corrosion degree level according to the corrosion rate, and output the corrosion degree level as the pipeline corrosion parameter.

[0018] An intelligent inspection and digital control method for gas drainers proposed in this application, by providing specific methods for obtaining environmental noise parameters and pipeline corrosion parameters, makes the environmental noise parameter upgrade from a single noise intensity to a noise power spectral density containing frequency information, and the pipeline corrosion parameter is refined from a general corrosion condition to a quantitative corrosion degree level, realizing the accurate acquisition of environmental noise parameters and pipeline corrosion parameters, and laying a foundation for the subsequent optimization of signal frequency and voltage control parameters based on these parameters.

[0019] Further, step S22 includes:

[0020] S221: Synchronously detect the corrosion potential and corrosion current of multiple monitoring points at different positions of the metal drain pipe at a preset time interval to obtain corresponding multiple sets of the corrosion potential and the corrosion current;

[0021] S222: Substitute each set of the corrosion potential and the corrosion current into the Tafel formula and perform polarization curve fitting to obtain the corresponding corrosion rate;

[0022] S223: Identify the corrosion types at different positions of the detected metal drain pipe;

[0023] S224: Calculate the overall corrosion risk index of the pipeline according to the corrosion rate and the corrosion type, and determine the corrosion degree level of the metal pipeline according to the mapping relationship between the preset corrosion risk index and the corrosion degree level, and output the corrosion degree level as the pipeline corrosion parameter.

[0024] An intelligent inspection and digital control method for gas drainers proposed in this application, by adopting technical means such as multi-point synchronous detection, Tafel formula and polarization curve fitting, corrosion type identification, and corrosion risk index evaluation, realizes a more accurate and comprehensive quantitative evaluation of the corrosion condition of the metal drain pipe, improves the accuracy and reliability of the pipeline corrosion parameter, and provides a strong guarantee for the effective implementation of subsequent intelligent inspection and digital control methods.

[0025] Further, in step S224, the steps of calculating the corrosion risk index of the overall pipeline according to the corrosion rate and the corrosion type include:

[0026] S2241: Construct a pipeline corrosion assessment model based on a Bayesian network. Take multiple groups of the corrosion rate and the corrosion type as inputs, and use the Bayesian network for probabilistic inference to calculate the corrosion probability distribution at different positions of the pipeline.

[0027] S2242: Obtain the corrosion risk index according to the corrosion probability distribution.

[0028] An intelligent inspection and digital control method for a gas drainer proposed in this application, through the application of a Bayesian network, this technical solution can more accurately and reliably evaluate the pipeline corrosion risk and provide more effective data support for subsequent intelligent inspection and digital control.

[0029] Further, step S3 includes:

[0030] S31: Receive the environmental noise parameters, extract multiple peak frequency points in the noise power spectral density according to the environmental noise parameters, and determine multiple candidate signal frequencies according to the multiple peak frequency points.

[0031] S32: Receive the pipeline corrosion parameters, and calculate the signal attenuation amounts at the multiple candidate signal frequencies according to the pipeline corrosion parameters.

[0032] S33: For each candidate signal frequency, calculate the minimum signal voltage required to ensure reliable signal transmission according to the signal attenuation amount.

[0033] S34: Compare the minimum signal voltage with a preset safety limit voltage, select the candidate signal frequency corresponding to the minimum signal voltage that is less than or equal to the preset safety limit voltage, and use the corresponding candidate signal frequency as the optimized signal frequency and the minimum signal voltage as the optimized signal voltage control parameter.

[0034] Further, step S32 includes:

[0035] S321: For a metal drain pipe, select multiple feature points at a preset interval along the signal propagation direction, and obtain the corrosion degree parameters at the positions where each feature point is located.

[0036] S322: Determine the equivalent resistivity at the positions where each feature point is located according to the corrosion degree parameters.

[0037] S323: Establish a lumped parameter transmission line equation based on the equivalent resistivity.

[0038] S324: For each of the candidate signal frequencies, calculate the signal attenuation by solving the lumped parameter transmission line equation.

[0039] Further, step S323 includes:

[0040] S3231: Along the signal propagation direction, divide the metal drain pipe into multiple pipe segments according to the positions of the selected multiple characteristic points;

[0041] S3232: Calculate the average equivalent resistivity of each pipe segment for the equivalent resistivities at both ends of each pipe segment, and calculate the resistance of the pipe segment according to the average equivalent resistivity;

[0042] S3233: Obtain the length, permeability, outer diameter, and inner diameter of the pipe segment, and calculate the inductance of the pipe segment;

[0043] S3234: Obtain the dielectric constant of the medium around the pipe segment, and calculate the capacitance of the pipe segment according to the dielectric constant, the length of the pipe segment, the outer diameter of the pipe segment, and the inner diameter of the pipe segment;

[0044] S3235: Establish a lumped parameter transmission line equation according to the resistance, inductance, and capacitance of the pipe segment.

[0045] Further, step S33 includes:

[0046] S331: Obtain the waveguide coupling efficiency of the guided wave signal injected into the metal drain pipe and the waveguide impedance of the guided wave signal transmitted in the metal drain pipe during the test experiment;

[0047] S332: For each of the candidate signal frequencies, calculate the minimum signal power required to ensure reliable signal transmission according to the signal attenuation and the waveguide coupling efficiency;

[0048] S333: Calculate the minimum signal voltage corresponding to the minimum signal power according to the minimum signal power and the waveguide impedance.

[0049] Further, after step S333 includes:

[0050] S334: Construct an adaptive safety margin correction model based on environmental parameters, where the environmental parameters include temperature, humidity, and corrosive gas concentration;

[0051] S335: Real-time collect the temperature, humidity, and corrosive gas concentration of the environment around the intrinsically safe sensor device to obtain the corresponding environmental parameter values;

[0052] S336: Input the environmental parameter values into the adaptive safety margin correction model, and calculate the safety margin adjustment coefficient corresponding to the current environmental parameters;

[0053] S337: Adjust the minimum signal voltage according to the safety margin adjustment coefficient to obtain the compensated minimum signal voltage.

[0054] In a second aspect, an intelligent inspection and digital control device for a gas drainer is applied to any one of the above-mentioned intelligent inspection and digital control methods for a gas drainer, and is characterized in that the device includes:

[0055] Liquid level detection module: used to detect the liquid level height in the gas drainer in real time and convert the liquid level height into an electrical signal;

[0056] Noise parameter detection module: used to detect the noise intensity of the surrounding environment of the drainer and the corrosion condition of the metal drain pipe in real time, and output the environmental noise parameters and pipeline corrosion parameters;

[0057] Parameter calculation module: used to receive the environmental noise parameters and the pipeline corrosion parameters and calculate the optimized signal frequency and voltage control parameters;

[0058] Signal output module: used to output the electrical signal according to the optimized signal frequency and voltage control parameters;

[0059] Waveguide conversion module: used to convert the output electrical signal into a waveguide signal to propagate along the metal drain pipe;

[0060] Signal transmission module: used to receive the waveguide signal, convert the waveguide signal into a radio frequency signal and transmit it.

[0061] Advantageous effects: An intelligent inspection and digital control method and device for a gas drainer proposed in this application, by detecting in real time and converting the liquid level height into an electrical signal, detecting the noise intensity of the surrounding environment of the drainer and the corrosion condition of the metal drain pipe, and outputting the environmental noise parameters and pipeline corrosion parameters, obtaining the optimized signal frequency and voltage control parameters, realizes the adaptive adjustment of signal transmission parameters to adapt to complex environments and pipeline condition changes, outputs an electrical signal according to the optimized signal frequency and voltage control parameters, converts the output electrical signal into a waveguide signal, and makes the waveguide signal propagate along the metal drain pipe, receives the waveguide signal propagating along the metal drain pipe, and converts the waveguide signal into a radio frequency signal and transmits it, completing the re-conversion of the signal form, realizing the wireless transmission of liquid level monitoring information, and finally achieving the purpose of intelligent inspection and digital control of the gas drainer. Therefore, this solution realizes the real-time, environment-adaptive and wireless transmission of liquid level information by constructing a low-cost, low-power and highly reliable intelligent inspection and digital control method for the drainer, has the advantages of simultaneously meeting accurate liquid level monitoring and long-term independent operation, and improves the safe operation level and intelligent management ability of the gas pipeline network in old urban areas. Brief Description of the Drawings

[0062] Figure 1 It is a flowchart of an intelligent inspection and digital control method for a gas drainer proposed in this application.

[0063] Figure 2 It is a structural diagram of an intelligent inspection and digital control device for a gas drainer proposed in this application.

[0064] Label Description: 201, liquid level detection module; 202, noise parameter detection module; 203, parameter calculation module; 204, signal output module; 205, waveguide conversion module; 206, signal transmission module. Detailed Embodiments

[0065] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Usually, the components of the embodiments of the present application described and marked in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0066] It should be noted that: similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0067] In the complex and explosion-risky underground pipe network environment in old urban areas, how to break through the constraints of the performance of intrinsically safe sensors themselves, overcome the problems of underground environment wireless signal attenuation and interference, and design an intrinsically safe drainer liquid level remote monitoring device with low power consumption, high reliability, low cost and easy large-scale deployment has become a key technical problem that urgently needs to be solved in the intelligent transformation of the gas pipe network in old urban areas. Therefore, this application proposes an intelligent inspection and digital control method and device for gas drainers, which are as follows:

[0068] Please refer to Figure 1 , on the first aspect, an intelligent inspection and digital control method for a gas drainer, the method includes the steps:

[0069] S1: Real-time detect the liquid level height in the gas drainer and convert the liquid level height into an electrical signal;

[0070] S2: Detect the noise intensity of the environment around the drainer and the corrosion condition of the metal drain pipe in real time, and output the environmental noise parameters and the pipe corrosion parameters;

[0071] S3: Receive the environmental noise parameters and the pipe corrosion parameters, and calculate the optimized signal frequency and voltage control parameters;

[0072] S4: Output an electrical signal according to the optimized signal frequency and voltage control parameters;

[0073] S5: Convert the output electrical signal into a guided wave signal to propagate along the metal drain pipe;

[0074] S6: Receive the guided wave signal, convert the guided wave signal into a radio frequency signal and transmit it.

[0075] Among them, in step S1, the liquid level height detection can be realized by using a pressure sensor, an ultrasonic sensor or a capacitive sensor, etc. The pressure sensor can be installed at the bottom of the drainer, and the liquid level height is deduced by measuring the bottom pressure; the ultrasonic sensor can be installed at the top of the drainer to measure the liquid level height in a non-contact manner; the capacitive sensor can obtain the liquid level height by measuring the capacitance value related to the liquid level height.

[0076] In step S2, the noise intensity detection can use an acoustic sensor, such as a microphone, arranged in the environment around the drainer to collect noise signals; the corrosion condition detection of the metal drain pipe can adopt an electrochemical method, such as the polarization curve method or the electrochemical impedance spectroscopy method, by arranging corrosion sensors on the surface of the metal drain pipe to monitor the corrosion potential and corrosion current of the pipe in real time.

[0077] In step S3, the calculation of the optimized signal frequency and voltage control parameters can be obtained by means of a look-up table method, formula calculation or model prediction, etc., based on the preset signal frequency selection range and voltage control parameter adjustment strategy, combined with the environmental noise parameters and the pipe corrosion parameters.

[0078] In step S4, the output of the electrical signal can be realized by a signal generator or a microcontroller, etc. The signal generator generates a corresponding electrical signal according to the optimized signal frequency and voltage control parameters determined in step S3; the microcontroller can output an electrical signal with a preset waveform and amplitude through program control.

[0079] In step S, the conversion of the electrical signal into a guided wave signal can be realized by a guided wave transducer. The guided wave transducer couples the electrical signal to the metal drain pipe to excite and transmit the guided wave signal; the installation position of the guided wave transducer can be selected according to the actual application scenario and the signal transmission distance requirement. For example, it can be directly clamped on the outer wall of the metal drain pipe.

[0080] In step S6, the reception of the guided wave signal can be achieved by another guided wave transducer, which receives the guided wave signal propagating along the metal drain pipe and converts the guided wave signal back into an electrical signal; the transmission of the radio frequency signal can be achieved by a wireless communication module, such as an NB-IoT, LoRa or ZigBee module. The wireless communication module modulates the received electrical signal onto a radio frequency carrier wave and transmits it through an antenna.

[0081] In some specific embodiments, the liquid level sensor is an intrinsically safe pressure sensor, which is installed at the bottom of the gas drainer to monitor the pressure at the bottom of the drainer in real time. The pressure signal is converted into a voltage signal of 0-5V through a signal conditioning circuit, representing a liquid level height range of 0-2 meters. The noise sensor is an intrinsically safe MEMS microphone, which is arranged on the inner wall of the inspection well of the drainer to collect the ambient noise signal. The noise signal is amplified and filtered, and then converted into a digital signal through an analog-to-digital converter for subsequent noise spectrum analysis. The corrosion sensor is an intrinsically safe corrosion probe with a three-electrode system, which is installed on the outer wall of the metal drain pipe to monitor the corrosion potential and corrosion current of the pipe in real time. The parameter calculation module uses a low-power microcontroller and pre-sets an optimization algorithm for signal frequency and voltage control parameters. According to the received noise parameters and corrosion parameters, it calculates and outputs an optimized signal frequency of 10 kHz and a voltage control parameter of 3V in real time. The signal output module is an intrinsically safe signal generator, which generates a sine wave electrical signal with a frequency of 10 kHz and a voltage amplitude of 3V according to the optimized parameters output by the parameter calculation module. The guided wave conversion module uses a piezoelectric ceramic guided wave transducer, which is closely attached to the metal drain pipe wall through a coupling agent to convert the electrical signal output by the signal generator into a longitudinal guided wave signal propagating along the pipe. The signal transmission module uses an intrinsically safe NB-IoT wireless communication module, which receives the electrical signal received and converted by the guided wave transducer and sends the liquid level data, noise parameters and corrosion parameters to the cloud platform through the NB-IoT network to achieve remote monitoring and management of the data.

[0082] The method provided by this application first detects the liquid level height in the gas drainage device in real time through step S1, and converts the liquid level information into an electrical signal form that is easy to process and transmit, which is the basis for realizing intelligent inspection and digital control. Subsequently, in step S2, the noise intensity of the surrounding environment of the drainage device and the corrosion condition of the metal drainage pipe are synchronously detected to obtain real-time information on environmental interference and the state of the pipeline itself, providing a basis for optimizing subsequent signal transmission. Step S3 receives the environmental noise parameters and pipeline corrosion parameters obtained in step S2, and uses them as inputs to calculate the optimized signal frequency and voltage control parameters suitable for the current environment and pipeline conditions, realizing the adaptive adjustment of signal transmission parameters and ensuring the reliability and effectiveness of signal transmission. Step S4 outputs an electrical signal according to the optimized parameters calculated in step S3 to ensure that the output signal is optimized according to the environmental and pipeline conditions. Step S5 converts the electrical signal into a guided wave signal and uses the metal drainage pipe as the guided wave transmission medium to realize the directional and efficient transmission of the signal, reducing the attenuation and interference of the signal in the complex underground environment. Finally, step S6 receives the guided wave signal and converts it into a radio frequency signal for transmission, realizing the wireless remote transmission of liquid level monitoring information and finally completing the intelligent inspection and digital control of the gas drainage device.

[0083] Compared with the prior art, this solution has the beneficial effects of low cost, low power consumption and high reliability of the transmitted signal, realizes the real-time acquisition of liquid level information, environment-adaptive optimized transmission and wireless remote monitoring, and realizes the automatic control of the gas pipeline network in the old city.

[0084] Further, step S2 includes:

[0085] S21: Collect the noise intensity of the surrounding environment of the gas drainage device in real time, perform a fast Fourier transform on the noise intensity to obtain the noise power spectral density, and output the noise power spectral density as the environmental noise parameter;

[0086] S22: Detect the corrosion potential and corrosion current at different positions of the metal drainage pipe in real time, calculate the corrosion rate according to the corrosion potential and corrosion current, obtain the corrosion degree level according to the corrosion rate, and output the corrosion degree level as the pipeline corrosion parameter.

[0087] Among them, in step S21, the collected noise intensity is converted from the time-domain noise signal to the frequency domain through a fast Fourier transform, and the noise power spectral density is obtained. The noise power spectral density can reflect the energy distribution of the noise at different frequencies.

[0088] In step S22, the corrosion potential and corrosion current at different positions of the metal drainage pipe are detected in real time. The detected corrosion potential and corrosion current are then used to calculate the corrosion rate. The corrosion degree level is determined according to the corrosion rate. The corrosion potential and corrosion current are important parameters in electrochemical corrosion detection and can reflect the corrosion state and corrosion rate of metal materials.

[0089] In some specific embodiments, in step S21, the acquisition of environmental noise can be achieved by using a multi-channel acoustic analyzer of model AWA6290T and a microphone of model MPA416 to collect the noise intensity in real time. The specific implementation process of the fast Fourier transform can be to select the radix-2 FFT algorithm, set the number of FFT points to 1024 points, and select the Hanning window as the window function to ensure the frequency resolution and suppress the spectral leakage.

[0090] In step S22, the detection of the corrosion potential and corrosion current can be carried out by using an electrochemical workstation with a three-electrode system, such as the Princeton VersaSTAT series electrochemical workstation. The working electrode is connected to the metal drainage pipe, and the reference electrode and the auxiliary electrode are placed in the soil around the drain. The corrosion rate is calculated using the Tafel formula, and the polarization curve fitting is completed by the least squares method. The classification standard of the corrosion degree level can refer to the standard formulated by the construction technical specifications in this field. Thus, the environmental noise parameters and the pipeline corrosion parameters can be accurately and effectively obtained, providing a data basis for the optimization of the subsequent signal frequency and voltage control parameters.

[0091] Furthermore, step S22 includes:

[0092] S221: At a preset time interval, synchronously detect the corrosion potential and corrosion current at multiple monitoring points at different positions of the metal drainage pipe to obtain corresponding multiple sets of corrosion potential and corrosion current;

[0093] S222: Substitute each set of corrosion potential and corrosion current into the Tafel formula and perform polarization curve fitting to obtain the corresponding corrosion rate;

[0094] S223: Identify the corrosion types at different positions of the detected metal drainage pipe;

[0095] S224: Calculate the overall corrosion risk index of the pipeline according to the corrosion rate and the corrosion type, and determine the corrosion degree level of the metal pipeline according to the mapping relationship between the preset corrosion risk index and the corrosion degree level, and output the corrosion degree level as the pipeline corrosion parameter.

[0096] Among them, in step S221, multiple monitoring points are deployed along different positions of the metal drainage pipe to comprehensively obtain the corrosion information of the pipeline.

[0097] Synchronous detection realizes the instant assessment of the corrosion state by ensuring the acquisition of data at different positions at the same time point.

[0098] The setting of the preset time interval, for example, can be set to detect once per hour or per day, allowing the system to adjust the detection frequency according to actual needs.

[0099] In step S222, the Tafel formula and polarization curve fitting are used as means to calculate the corrosion rate. Specifically, the polarization curve is obtained by applying a varying potential and measuring the current response, and the Tafel formula is applied to analyze the linear part of the polarization curve to extract the corrosion current density, and finally the corrosion rate is calculated.

[0100] In step S223, the identification of the corrosion type can be completed with the help of electrochemical methods or surface analysis techniques. For example, by observing the morphology of the corrosion products or analyzing the characteristics of electrochemical noise, different types of corrosion such as uniform corrosion, pitting corrosion or crevice corrosion can be distinguished.

[0101] In step S224, for the calculation of the overall corrosion risk index of the pipeline, the weighted average method can be adopted, where different weights are assigned to the corrosion rate and the corrosion type. The mapping relationship of the corrosion degree levels can be established in advance. For example, the corrosion risk index is divided into three levels: low, medium, and high, and each level corresponds to different maintenance measures.

[0102] Specifically, by arranging multiple corrosion sensors on the metal drain pipe, multi-point monitoring of the pipeline corrosion state is realized. In the data processing link, the application of the Tafel formula and polarization curve fitting technology ensures the accuracy of the corrosion rate calculation. The identification of the corrosion type makes the corrosion assessment more comprehensive. The introduction of the corrosion risk index realizes the quantitative assessment of the corrosion state. The division of the corrosion degree levels provides a basis for subsequent maintenance decisions. Thus, the accuracy and reliability of the pipeline corrosion parameters are improved.

[0103] Furthermore, in step S224, the steps for calculating the overall corrosion risk index of the pipeline according to the corrosion rate and the corrosion type include:

[0104] S2241: Construct a pipeline corrosion assessment model based on the Bayesian network, take multiple groups of corrosion rates and corrosion types as inputs, and use the Bayesian network for probabilistic inference to calculate the corrosion probability distribution at different positions of the pipeline;

[0105] S2242: Obtain the corrosion risk index according to the corrosion probability distribution.

[0106] Among them, in step S2241, constructing a pipeline corrosion assessment model based on a Bayesian network can be implemented as follows: First, determine multiple factors affecting pipeline corrosion risk, such as corrosion rate and corrosion type. Then, based on the experience of those skilled in the art, historical data, or experimental results, determine the dependency relationships between these factors and construct a Bayesian network structure. Further, multiple sets of corrosion rate and corrosion type data at different positions of the pipeline can be collected as input and input into the Bayesian network model. Thus, using the probability inference function of the Bayesian network, the corrosion probability distribution at different positions of the pipeline can be calculated. For example, the Bayesian network can output the probabilities of slight corrosion, moderate corrosion, and severe corrosion occurring at different positions of the pipeline.

[0107] Specifically, in step S2242, after obtaining the corrosion probability distribution at different positions of the pipeline, the corrosion risk index can be calculated. As a preferred implementation, the corrosion risk index can be obtained by weighted summation of the corrosion probability distribution. For example, weights can be set for different corrosion grades, and the weight of severe corrosion is higher than that of slight corrosion. Then, multiply the probability of each corrosion grade by the corresponding weight and sum the results to obtain the corrosion risk index. The higher the corrosion risk index, the higher the overall corrosion risk of the pipeline. Through the application of the Bayesian network, corrosion data can be analyzed more comprehensively, considering the interactions between various influencing factors, so as to more precisely evaluate the corrosion risk at each location of the pipeline.

[0108] Furthermore, step S3 includes:

[0109] S31: Receive environmental noise parameters, extract multiple peak frequency points from the noise power spectral density according to the environmental noise parameters, and determine multiple candidate signal frequencies based on the multiple peak frequency points;

[0110] S32: Receive pipeline corrosion parameters and calculate the signal attenuation amounts at multiple candidate signal frequencies according to the pipeline corrosion parameters;

[0111] S33: For each candidate signal frequency, calculate the minimum signal voltage required to ensure reliable signal transmission according to the signal attenuation amount;

[0112] S34: Compare the size of the minimum signal voltage with the preset safety limit voltage, select the candidate signal frequency corresponding to the minimum signal voltage less than or equal to the preset safety limit voltage, and use the corresponding candidate signal frequency as the optimized signal frequency and the minimum signal voltage as the optimized model voltage control parameter.

[0113] Among them, in step S31, signal processing methods such as fast Fourier transform can be used to analyze the time-domain signal of environmental noise, obtaining the power distribution of the noise in the frequency domain, that is, the noise power spectral density. The peak frequency points can be determined as the frequency points with higher amplitudes in the noise power spectral density, representing the frequency bands where the noise energy in the environment is concentrated. Multiple candidate signal frequencies will be determined based on these peak frequency points. As an implementation method, it is possible to select frequency bands away from the vicinity of these noise peak frequency points and choose other frequency points as candidate signal frequencies. For example, frequencies between the noise peak frequency points or far from the noise peak frequency points can be selected as candidate signal frequencies to reduce noise interference.

[0114] In step S32, the degree of pipeline corrosion will affect the transmission characteristics of signals in metal pipelines. The higher the degree of corrosion, the greater the signal attenuation usually is. The signal attenuation amount can be calculated by establishing a signal transmission model and substituting the pipeline corrosion parameters. For example, based on parameters such as the material, size, and corrosion degree of the metal pipeline, a lumped parameter transmission line model can be established, and this model can be used to calculate the attenuation amount of the signal during transmission in the pipeline at different candidate signal frequencies.

[0115] In step S33, when the signal is transmitted in the metal pipeline, attenuation will occur. To ensure that the receiving end can reliably receive the signal, the transmitting end needs to provide a sufficiently large signal voltage. The calculation of the minimum signal voltage needs to consider factors such as the signal attenuation amount, the sensitivity of the receiving end, and the signal-to-noise ratio requirement. For example, the minimum signal power required by the receiving end can be preset first, and then based on the calculated signal attenuation amount, the minimum signal power required by the transmitting end can be deduced inversely, and then the corresponding minimum signal voltage can be calculated according to the waveguide impedance.

[0116] In step S34, the calculated minimum signal voltage will be compared with the preset safety limit voltage. The preset safety limit voltage is the upper limit value of the voltage set according to the requirements of intrinsic safety to prevent safety accidents caused by excessive voltage in an explosive environment. If the minimum signal voltage is less than or equal to the preset safety limit voltage, the candidate signal frequency corresponding to this minimum signal voltage will be selected as the optimized signal frequency, and this minimum signal voltage will be selected as the optimized signal voltage control parameter. If there are multiple candidate signal frequencies that meet the conditions, the candidate signal frequency corresponding to the minimum signal voltage can be selected as the final optimized signal frequency to further reduce the safety risk and power consumption.

[0117] Furthermore, step S32 includes:

[0118] S321: For the metal drainage pipe, select multiple characteristic points at a preset interval along the signal propagation direction, and obtain the corrosion degree parameters at the positions of each characteristic point.

[0119] S322: Determine the equivalent resistivity at the locations of each feature point according to the corrosion degree parameter;

[0120] S323: Based on the equivalent resistivity, establish the lumped parameter transmission line equation;

[0121] S324: For each candidate signal frequency, calculate the signal attenuation by solving the lumped parameter transmission line equation.

[0122] Among them, in step S321, the preset spacing can be set according to the pipeline length and corrosion condition in the actual application scenario. For example, in a pipeline with relatively uniform corrosion degree, the spacing can be set larger; on the contrary, in a pipeline with complex corrosion degree distribution, the spacing can be set smaller to more precisely reflect the corrosion distribution. The selection of feature points can be points evenly distributed on the metal drainage pipe, or the density of feature points can be increased in the corrosion-prone areas or areas with higher corrosion degree according to the pre-determined corrosion detection results. The corrosion degree parameter can be obtained through a variety of non-destructive testing methods, such as ultrasonic testing, electromagnetic testing or radiographic testing, etc.

[0123] In step S322, the determination of the equivalent resistivity is based on the relationship model between the corrosion degree parameter and the material resistivity. For example, the mapping relationship between the corrosion depth, corrosion area or corrosion type and the equivalent resistivity can be established and obtained through experimental data or theoretical analysis.

[0124] In step S323, the establishment of the lumped parameter transmission line equation is to discretize the metal drainage pipe into multiple small segments, and each small segment is equivalent to lumped parameter elements such as resistors, inductors and capacitors. The resistance value of the pipe segment is calculated according to the average equivalent resistivity and the geometric size of the pipe segment, and the inductance value and capacitance value are calculated according to the geometric shape of the pipe segment, material parameters and surrounding medium parameters.

[0125] In step S324, the solution of the lumped parameter transmission line equation can adopt the frequency domain analysis method. For example, substitute the candidate signal frequency into the equation, calculate the propagation constant and impedance of the signal on the transmission line, and then calculate the signal attenuation.

[0126] Furthermore, step S323 includes:

[0127] S3231: Divide the metal drainage pipe along the signal propagation direction into multiple pipe segments according to the positions of the selected multiple feature points;

[0128] S3232: Calculate the average equivalent resistivity of each pipe segment for the equivalent resistivity at both ends of each pipe segment, and calculate the resistance of the pipe segment according to the average equivalent resistivity;

[0129] S3233: Obtain the length, permeability, outer diameter, and inner diameter of the pipe segment, and calculate the inductance of the pipe segment;

[0130] S3234: Obtain the permittivity of the medium around the pipe segment, and calculate the capacitance of the pipe segment based on the permittivity, length, outer diameter, and inner diameter of the pipe segment;

[0131] S3235: Based on the resistance, inductance, and capacitance of the pipe segment, establish the lumped parameter transmission line equation.

[0132] Among them, in step S3231, the metal drain pipe is divided into multiple pipe segments along the signal propagation direction, and the division is based on the positions of a plurality of pre-selected characteristic points. These characteristic points are the positions for detecting the corrosion degree parameters on the pipeline. By discretizing the continuous metal drain pipe into multiple pipe segments, the parameters of each pipe segment can be calculated independently, so as to more finely describe the non-uniform characteristics of the pipeline.

[0133] In step S3232, for each divided pipe segment, first calculate the average value of the equivalent resistivity at both ends of the pipe segment, and use this average equivalent resistivity as the representative resistivity of the pipe segment. Then, based on this average equivalent resistivity and the geometric dimensions of the pipe segment, calculate the resistance value of the pipe segment. The resistance calculation of the pipe segment takes into account the influence of the corrosion degree on the resistivity of the metal. The higher the corrosion degree, the greater the resistivity of the metal usually is.

[0134] Steps S3233 and S3234 calculate the inductance and capacitance parameters of each pipe segment respectively. The calculation of the inductance requires obtaining parameters such as the length, permeability, outer diameter, and inner diameter of the pipe segment, and the calculation of the capacitance requires obtaining the permittivity of the medium around the pipe segment and the geometric dimension parameters of the pipe segment.

[0135] In step S3235, after obtaining the resistance, inductance, and capacitance of each pipe segment, these parameters are used to establish the lumped parameter transmission line equation. The lumped parameter model approximates the actual continuous transmission line as a circuit network composed of discrete resistance, inductance, and capacitance elements. With the help of the lumped parameter transmission line equation, the transmission characteristics of signals in the metal drain pipe can be approximately analyzed and calculated, providing a model basis for the accurate calculation of the subsequent signal attenuation amount.

[0136] In some specific implementation manners, the steps for establishing the lumped parameter transmission line equation are as follows:

[0137] Obtain the resistance Rn, inductance Ln, and capacitance Cn of each pipe segment, and the signal angular frequency ω; where, Rn is the resistance of the nth pipe segment, with the unit of ohm (Ω); Ln is the inductance of the nth pipe segment, with the unit of henry (H); Cn is the capacitance of the nth pipe segment, with the unit of farad (F); ω is the signal angular frequency, with the unit of radian per second (rad / s); n is the serial number of the pipe segment;

[0138] For each pipe segment, construct the transmission matrix Tn of the lumped-parameter transmission line equation. The matrix Tn takes the following form:

[0139] , where j is the imaginary unit;

[0140] By cascading and multiplying the transmission matrices Tn of all pipe segments, calculate the lumped-parameter transmission equation T_total, that is ; where T1 is the transmission matrix of the first pipe segment, TN is the transmission matrix of the Nth pipe segment, and N is the total number of pipe segments.

[0141] After obtaining the lumped-parameter transmission equation, the voltage transmission coefficient Av can be calculated. The voltage transmission coefficient Av is approximately expressed as Av = 1 / T_total[1,1], where T_total[1,1] is the element in the first row and first column of the lumped-parameter transmission equation T_total;

[0142] According to the voltage transmission coefficient Av, calculate the signal attenuation. The signal attenuation ; where log10 is the logarithm to the base 10, and |Av| is the absolute value of the voltage transmission coefficient Av.

[0143] Furthermore, step S33 includes:

[0144] S331: Obtain the waveguide coupling efficiency of the guided wave signal injected into the metal drain pipe and the waveguide impedance of the guided wave signal transmitted in the metal drain pipe in the test experiment;

[0145] S332: For each candidate signal frequency, calculate the minimum signal power required to ensure reliable signal transmission according to the signal attenuation and the waveguide coupling efficiency;

[0146] S333: Calculate the minimum signal voltage corresponding to the minimum signal power according to the minimum signal power and the waveguide impedance.

[0147] Among them, in step S331, the waveguide coupling efficiency and the waveguide impedance are obtained through a pre-test experiment. Specifically, the waveguide coupling efficiency can be obtained as the energy conversion efficiency when the guided wave signal is injected from the transducer into the metal drain pipe, and the waveguide impedance can be obtained as the impedance value encountered when the guided wave signal propagates in the metal drain pipe. During the test, a signal generator and a power amplifier are used to generate and amplify the guided wave signal, a coupler is used to inject the guided wave signal into the metal drain pipe, and a sensor is used to receive the guided wave signal propagating in the metal drain pipe. By analyzing the injected and received guided wave signals, the waveguide coupling efficiency and the waveguide impedance can be calculated.

[0148] In step S332, the calculation of the minimum signal power takes into account the waveguide coupling efficiency. Thus, the energy loss during the waveguide coupling process can be compensated, ensuring that the power of the waveguide signal actually injected into the metal drain pipe meets the transmission requirements. For example, if the waveguide coupling efficiency is low, the minimum signal power needs to be increased to ensure that sufficient signal energy is injected into the metal drain pipe.

[0149] In step S333, the calculation of the minimum signal voltage takes into account the waveguide impedance. Thus, it can be ensured that the output minimum signal voltage can overcome the impedance of the metal drain pipe, thereby guaranteeing the effective transmission of the waveguide signal in the metal drain pipe. For example, if the waveguide impedance is high, the minimum signal voltage needs to be increased to drive the waveguide signal to propagate in the metal drain pipe.

[0150] Specifically, for each candidate signal frequency, first, the waveguide coupling efficiency and the waveguide impedance are obtained through experimental measurement. Then, based on the signal attenuation calculated in step S32 and the experimentally measured waveguide coupling efficiency, step S332 is executed to calculate the minimum signal power required to ensure reliable signal transmission. The calculation formula can be: minimum signal power = signal attenuation / waveguide coupling efficiency. After that, according to step S333, based on the minimum signal power calculated in step S332 and the experimentally measured waveguide impedance, the minimum signal voltage is calculated. The calculation formula can be: minimum signal voltage = square root of

[0151] Through the above steps, the minimum signal voltage required to ensure reliable signal transmission can be determined more accurately, providing a more reliable parameter basis for subsequent signal output and transmission.

[0152] Further, after step S333, it includes:

[0153] S334: Construct an adaptive safety margin correction model based on environmental parameters, where the environmental parameters include temperature, humidity, and corrosive gas concentration;

[0154] S335: Real-time collect the temperature, humidity, and corrosive gas concentration of the environment around the intrinsically safe sensor device to obtain the corresponding environmental parameter values;

[0155] S336: Input the environmental parameter values into the adaptive safety margin correction model to calculate the safety margin adjustment coefficient corresponding to the current environmental parameters;

[0156] S337: Adjust the minimum signal voltage according to the safety margin adjustment coefficient to obtain the compensated minimum signal voltage.

[0157] Among them, in view of the problem that the calculation of the minimum signal voltage may not fully consider the influence of environmental parameters, an adaptive safety margin correction mechanism is proposed. First, an adaptive safety margin correction model is constructed, which is pre-established to evaluate the influence degree of environmental parameters such as temperature, humidity and corrosive gas concentration on the safety margin. The mapping relationship between the environmental parameters and the safety margin adjustment coefficient is included in this model.

[0158] Furthermore, the temperature, humidity and corrosive gas concentration of the environment around the intrinsically safe sensor device are collected in real time through sensors to obtain the current environmental parameter values. The collected environmental parameter values are then input into the adaptive safety margin correction model, and the model calculates the safety margin adjustment coefficient corresponding to the current environmental parameters according to the preset mapping relationship. Thus, the minimum signal voltage calculated in step S333 is adjusted according to the safety margin adjustment coefficient to obtain the finally compensated minimum signal voltage, and this voltage value can better meet the safety requirements under the current environmental conditions.

[0159] Specifically, the adaptive safety margin correction model can adopt the form of a look-up table, and the safety margin adjustment coefficients under different combinations of environmental parameters are preset. For example, when the temperature rises, the humidity increases or the corrosive gas concentration increases, the safety margin adjustment coefficient can be increased accordingly, and vice versa. In practical applications, the look-up table can be calibrated by experimental or simulation methods according to the specific environmental characteristics and safety requirements. The real-time collection of environmental parameters can be completed by temperature sensors, humidity sensors and gas concentration sensors, which are arranged in the environment around the drainer. The parameter calculation module receives the environmental parameter values from the sensors and inputs them into the pre-constructed adaptive safety margin correction model to find the corresponding safety margin adjustment coefficient. Finally, the signal output module adjusts the minimum signal voltage according to this adjustment coefficient. For example, by multiplying the minimum signal voltage by the safety margin adjustment coefficient, the compensated minimum signal voltage is obtained.

[0160] In some specific embodiments, the adaptive safety margin correction model is constructed as a two-dimensional look-up table. The row index of the table represents the temperature value, the column index represents the humidity value, and each element in the table stores the safety margin adjustment coefficient under a specific temperature and humidity combination. The corrosive gas concentration is divided into three levels: high, medium, and low, and each level corresponds to an independent two-dimensional look-up table. In the model construction stage, through controlled variable experiments, under different combinations of temperature, humidity, and corrosive gas concentration, the minimum safety margin required to ensure the safe operation of the system is tested and determined, and it is converted into a safety margin adjustment coefficient and stored in the look-up table. In the device operation stage, the temperature sensor and the humidity sensor collect the ambient temperature and humidity values in real time, and the gas concentration sensor detects the corrosive gas concentration level. The parameter calculation module looks up the safety margin adjustment coefficient in the corresponding look-up table according to the collected temperature value, humidity value, and gas concentration level. For example, if the current ambient temperature is 25 degrees Celsius, the humidity is 60%, and the corrosive gas concentration is medium, the parameter calculation module looks up the safety margin adjustment coefficient corresponding to a temperature of 25 degrees Celsius and a humidity of 60% in the look-up table corresponding to the medium level of corrosive gas concentration. Assuming the found coefficient is 1.2, then the minimum signal voltage calculated in step S333 is multiplied by 1.2 to obtain the compensated minimum signal voltage. Thus, the signal output module outputs an electrical signal with the compensated minimum signal voltage to ensure the safe and reliable operation of the system under the current environmental conditions.

[0161] Second aspect, a device for intelligent inspection and digital management and control of a gas drainer, which is applied in any one of the above-mentioned methods for intelligent inspection and digital management and control of a gas drainer, is characterized in that the device includes:

[0162] The liquid level detection module 201: is used to detect the liquid level height in the gas drainer in real time and convert the liquid level height into an electrical signal;

[0163] The noise parameter detection module 202: is used to detect the noise intensity of the surrounding environment of the drainer and the corrosion condition of the metal drain pipe in real time, and output the environmental noise parameter and the pipeline corrosion parameter;

[0164] The parameter calculation module 203: is used to receive the environmental noise parameter and the pipeline corrosion parameter, and calculate the optimized signal frequency and voltage control parameter;

[0165] The signal output module 204: is used to output an electrical signal according to the optimized signal frequency and voltage control parameter;

[0166] The guided wave conversion module 205: is used to convert the output electrical signal into a guided wave signal to propagate along the metal drain pipe;

[0167] The signal transmitting module 206: is used to receive the guided wave signal, convert the guided wave signal into a radio frequency signal and transmit it.

[0168] Among them, the liquid level detection module 201 is configured to perform real-time detection of the liquid level height. The detection result is then converted into an electrical signal, laying the foundation for subsequent processing.

[0169] The noise parameter detection module 202 is responsible for synchronously monitoring the noise intensity of the environment around the drainer and the corrosion state of the metal drain pipe. The environmental noise parameters and the pipe corrosion parameters are then output, providing environmental information for signal transmission optimization.

[0170] The parameter calculation module 203 receives the environmental noise parameters and the pipe corrosion parameters. The optimized signal frequency and voltage control parameters are calculated based on the received parameters, realizing the adaptive adjustment of signal transmission.

[0171] The signal output module 204 generates and outputs the corresponding electrical signal according to the optimized parameters determined by the parameter calculation module.

[0172] The guided wave conversion module 205 receives the electrical signal from the signal output module and converts the electrical signal into a guided wave signal so that the signal can effectively propagate along the metal drain pipe.

[0173] The signal transmitting module 206 receives the guided wave signal and further converts the guided wave signal into a radio frequency signal, finally realizing the wireless transmission of data.

[0174] The liquid level detection module 201 can be an intrinsically safe liquid level sensor, such as a magnetostrictive liquid level sensor or a float liquid level sensor, ensuring safe operation in an explosive environment. The noise parameter detection module 202 can integrate a noise sensor and a corrosion sensor. The noise sensor is, for example, a microphone, and the corrosion sensor is, for example, an electrochemical sensor, realizing the synchronous detection of environmental noise and pipe corrosion. The parameter calculation module 203 can be composed of a microprocessor and a memory. The microprocessor runs a preset algorithm program, and the memory stores the algorithm program and parameter data, realizing the calculation of optimized parameters. The guided wave conversion module 205 can adopt a piezoelectric ceramic transducer or a magnetostrictive transducer to realize the conversion of an electrical signal into a guided wave signal. The signal transmitting module 206 can adopt a low-power radio frequency chip, such as a Bluetooth, Zigbee or LoRa module, to realize the wireless transmission of data.

[0175] Specifically, when the device is operating, the liquid level detection module 201 first collects the liquid level height data inside the gas drainage device in real time and converts the liquid level height information into an electrical signal. At the same time, the noise parameter detection module 202 works to collect the noise intensity of the surrounding environment of the drainage device and the corrosion condition information of the metal drainage pipe in real time, and processes and converts this information into environmental noise parameters and pipeline corrosion parameters. The parameter calculation module 203 receives the environmental noise parameters and pipeline corrosion parameters from the noise parameter detection module, and uses a preset optimization algorithm to calculate the optimal signal frequency and voltage control parameters suitable for the current environmental conditions. The signal output module 204 accurately outputs an electrical signal according to the optimized parameters calculated by the parameter calculation module. The guided wave conversion module 205 receives the electrical signal output by the signal output module and converts the electrical signal into a guided wave signal that can propagate in the metal drainage pipe. The guided wave signal propagates along the metal drainage pipe, carrying the liquid level and environmental monitoring data. Finally, the signal transmission module 206 receives the guided wave signal and converts the guided wave signal into a radio frequency signal for external transmission, realizing the remote wireless transmission of the monitoring data. Through the collaborative work of each module, the device realizes the intelligent inspection and digital management and control of the liquid level of the gas drainage device.

[0176] The liquid level detection module 201 is installed inside the gas drainage device and is used to monitor the liquid level height in real time. The environmental noise sensor and corrosion sensor of the noise parameter detection module 202 are installed around the drainage device and are used to collect environmental noise and pipeline corrosion data. The parameter calculation module 203, the signal output module 204, the guided wave conversion module 205, and the signal transmission module 206 are integrated in an intrinsically safe circuit box, and the circuit box is installed on the ground near the drainage device or on the pipeline support.

[0177] The liquid level detection module 201 and the noise parameter detection module 202 are connected to the circuit box through intrinsically safe cables to achieve signal and power supply transmission. The radio frequency signal is transmitted to the monitoring center or cloud platform through the antenna to realize remote monitoring and management of the data. The overall device adopts a low-power design and is powered by a battery to achieve long-term independent operation.

[0178] Thus, the present application provides an intelligent inspection and digital management and control device that can achieve intrinsic safety, wireless reliable transmission, and low-power operation in the explosive environment around the gas drainage device in the old urban area.

[0179] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0180] The above are only embodiments of the present application and are not intended to limit the protection scope of the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. An intelligent inspection and digital control method for gas drainers, characterized in that, The method includes the steps of: S1: Detect the liquid level height in the gas drainage device in real time and convert the liquid level height into an electrical signal; S2: Detect the noise intensity of the surrounding environment of the drainage device and the corrosion condition of the metal drainage pipe in real time, and output the environmental noise parameter and the pipeline corrosion parameter; S3: Receive the environmental noise parameter and the pipeline corrosion parameter, and calculate the optimized signal frequency and voltage control parameter; Step S3 includes: S31: Receive the environmental noise parameter, extract multiple peak frequency points in the noise power spectral density according to the environmental noise parameter, and determine multiple candidate signal frequencies according to the multiple peak frequency points; S32: Receive the pipeline corrosion parameter, and calculate the signal attenuation amount at the multiple candidate signal frequencies according to the pipeline corrosion parameter; S33: For each candidate signal frequency, calculate the minimum signal voltage required to ensure reliable signal transmission according to the signal attenuation amount; S34: Compare the minimum signal voltage with the preset safety limit voltage, select the candidate signal frequency corresponding to the minimum signal voltage less than or equal to the preset safety limit voltage, and use the corresponding candidate signal frequency as the optimized signal frequency and the minimum signal voltage as the optimized signal voltage control parameter; S4: Output the electrical signal according to the optimized signal frequency and voltage control parameter; S5: Convert the output electrical signal into a guided wave signal to propagate along the metal drainage pipe; S6: Receive the guided wave signal, convert the guided wave signal into a radio frequency signal and transmit it.

2. The intelligent inspection and digital control method for a gas drainer according to claim 1, characterized in that, Step S2 includes: S21: Collect the noise intensity of the surrounding environment of the gas drainage device in real time, perform a fast Fourier transform on the noise intensity to obtain the noise power spectral density, and output the noise power spectral density as the environmental noise parameter; S22: Detect the corrosion potential and corrosion current at different positions of the metal drainage pipe in real time, calculate the corrosion rate according to the corrosion potential and the corrosion current, obtain the corrosion degree level according to the corrosion rate, and output the corrosion degree level as the pipeline corrosion parameter.

3. The intelligent inspection and digital control method of a gas drainer according to claim 2, wherein, Step S22 includes: S221: Synchronously detect the corrosion potential and corrosion current of multiple monitoring points at different positions of the metal drainage pipe at a preset time interval to obtain corresponding multiple groups of the corrosion potential and the corrosion current; S222: Substitute each group of the corrosion potential and the corrosion current into the Tafel formula and perform polarization curve fitting to obtain the corresponding corrosion rate; S223: Identify the corrosion type at different positions of the detected metal drainage pipe; S224: Calculate the overall corrosion risk index of the pipeline according to the corrosion rate and the corrosion type, and determine the corrosion degree level of the metal pipeline according to the mapping relationship between the preset corrosion risk index and the corrosion degree level, and output the corrosion degree level as the pipeline corrosion parameter.

4. A method for intelligent inspection and digital control of a gas drainer according to claim 3, characterized in that, In step S224, the step of calculating the overall corrosion risk index of the pipeline according to the corrosion rate and the corrosion type includes: S2241: Construct a pipeline corrosion assessment model based on a Bayesian network. Take multiple groups of the corrosion rate and the corrosion type as inputs, perform probabilistic inference using the Bayesian network, and calculate the corrosion probability distribution at different positions of the pipeline. S2242: Obtain the corrosion risk index according to the corrosion probability distribution.

5. The intelligent inspection and digital control method of a gas drainer according to claim 1, characterized in that, Step S32 includes: S321: For a metal drain pipe, select multiple feature points at a preset spacing along the signal propagation direction, and obtain the corrosion degree parameters at the positions of each of the feature points. S322: Determine the equivalent resistivity at the positions of each of the feature points according to the corrosion degree parameters. S323: Based on the equivalent resistivity, establish a lumped parameter transmission line equation. S324: For each of the candidate signal frequencies, calculate the signal attenuation amount by solving the lumped parameter transmission line equation.

6. The intelligent inspection and digital control method for a gas drainer according to claim 5, characterized in that, Step S323 includes: S3231: Divide the metal drain pipe along the signal propagation direction into multiple pipe segments according to the positions of the multiple selected feature points. S3232: Calculate the average equivalent resistivity of each pipe segment for the equivalent resistivities at both ends of each pipe segment, and calculate the resistance of the pipe segment according to the average equivalent resistivity. S3233: Obtain the length, magnetic permeability, outer diameter of the pipe segment, and inner diameter of the pipe segment, and calculate the inductance of the pipe segment. S3234: Obtain the dielectric constant of the medium around the pipe segment, and calculate the capacitance of the pipe segment according to the dielectric constant, the length of the pipe segment, the outer diameter of the pipe segment, and the inner diameter of the pipe segment. S3235: Based on the resistance, inductance, and capacitance of the pipe segment, establish a lumped parameter transmission line equation.

7. A method for intelligent inspection and digital management and control of a gas drainer according to claim 6, characterized in that, Step S33 includes: S331: Obtain the wave guide coupling efficiency when a wave guide signal is injected into the metal drain pipe and the wave guide impedance when the wave guide signal is transmitted in the metal drain pipe in the test experiment. S332: For each of the candidate signal frequencies, calculate the minimum signal power required to ensure reliable signal transmission according to the signal attenuation amount and the wave guide coupling efficiency. S333: Calculate the minimum signal voltage corresponding to the minimum signal power according to the minimum signal power and the wave guide impedance.

8. A method for intelligent inspection and digital control of a gas drainer according to claim 7, characterized in that After step S333 includes: S334: Construct an adaptive safety margin correction model based on environmental parameters, where the environmental parameters include temperature, humidity, and corrosive gas concentration. S335: Real-time collect the temperature, humidity, and corrosive gas concentration of the environment around the intrinsically safe sensor device to obtain corresponding environmental parameter values. S336: Input the environmental parameter values into the adaptive safety margin correction model, and calculate the safety margin adjustment coefficient corresponding to the current environmental parameters. S337: Adjust the minimum signal voltage according to the safety margin adjustment coefficient to obtain the compensated minimum signal voltage.

9. An intelligent inspection and digital control device for a gas drainer, which is applied to the intelligent inspection and digital control method for a gas drainer according to any one of claims 1-8 above, is characterized in that, The device includes: Liquid level detection module: used to detect the liquid level height in the gas drainer in real time and convert the liquid level height into an electrical signal. Noise parameter detection module: used to detect the noise intensity of the environment around the drainer and the corrosion condition of the metal drain pipe in real time, and output environmental noise parameters and pipeline corrosion parameters. Parameter calculation module: configured to receive the environmental noise parameter and the pipeline corrosion parameter, and calculate an optimized signal frequency and voltage control parameter; Signal output module: configured to output the electrical signal according to the optimized signal frequency and voltage control parameter; Guided wave conversion module: configured to convert the output electrical signal into a guided wave signal for propagation along the metal drain pipe; Signal transmission module: configured to receive the guided wave signal, convert the guided wave signal into a radio frequency signal and transmit it.

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