Method and device for detecting gas leakage of laser cutting air compressor

Abstract

The application provides a gas leakage detection method and device for laser cutting air compressors, relates to the technical field of laser cutting air compressor testing, and comprises the following steps: identifying the gas transmission flow direction of the laser cutting air compressor, analyzing system key pipelines and equipment flow transfer nodes, configuring ultrasonic sensors, and obtaining ultrasonic monitoring signals; collecting gas state data; identifying abnormal points, performing abnormal positioning analysis to determine abnormal flow transfer nodes; positioning node flow transfer influence parameters and leakage risk, configuring ultrasonic monitoring sensitive parameters; adjusting the parameters of the ultrasonic sensors; performing joint leakage analysis to obtain gas leakage detection results. Through the application, the technical problem that gas leakage cannot be discovered and positioned in time due to the difficulty in real-time dynamic monitoring of gas flow abnormalities in the system can be solved, the technical goal of real-time dynamic monitoring of gas flow abnormalities can be achieved, and the technical effect of efficiently and accurately identifying and positioning potential leakage points can be achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laser cutting air compressor testing, in particular to a gas leakage detection method and device for laser cutting air compressor. BACKGROUND

[0002] The working principle of the laser cutting air compressor is to provide the required gas source for the laser cutting machine through compressed air. Due to the complex structure, the gas may encounter various resistances and abnormal conditions during the circulation process, thereby affecting the overall efficiency and stability of the equipment.

[0003] In the traditional technology, when analyzing the gas flow path, only the performance and maintenance of static equipment are usually focused on, and real-time monitoring of dynamic gas flow characteristics is ignored, so that abnormal gas flow cannot be discovered and located in time. In addition, the current monitoring system lacks intelligent adjustment mechanism and cannot dynamically adjust the sensitivity of the sensor according to real-time data. For example, in areas with high risk of leakage, if the sensitivity of the monitoring parameters cannot be improved in time, some potential gas leakage may not be effectively captured, thereby affecting production safety and product quality. Therefore, under this traditional monitoring method, once the system appears abnormal, it often can only rely on manual judgment or post-analysis, and cannot reflect the dynamic changes of the system in real time, resulting in long maintenance period, low production efficiency, and even more serious safety hazards.

[0004] In summary, the existing technology has the technical problem that it is difficult to monitor the abnormality of gas flow in the system in real time and dynamically, most of which lack intelligent and adaptive adjustment mechanism, so that gas leakage is difficult to be discovered and located in time, further affecting the stable operation of the laser cutting air compressor and the cutting quality, increasing the risk of equipment failure, prolonging the maintenance time, and even bringing safety hazards and production downtime, thereby affecting the production efficiency and product quality. SUMMARY

[0005] The purpose of the present application is to provide a gas leakage detection method and device for laser cutting air compressor, to solve the technical problem that in the existing technology, it is difficult to monitor the abnormality of gas flow in the system in real time and dynamically, most of which lack intelligent and adaptive adjustment mechanism, so that gas leakage is difficult to be discovered and located in time, further affecting the stable operation of the laser cutting air compressor and the cutting quality, increasing the risk of equipment failure, prolonging the maintenance time, and even bringing safety hazards and production downtime, thereby affecting the production efficiency and product quality.

[0006] In view of the above problems, the present application provides a gas leakage detection method and device for laser cutting air compressor.

[0007] In a first aspect, the application provides a gas leakage detection method for a laser cutting air compressor, which is implemented by a gas leakage detection device for the laser cutting air compressor, and includes the following steps: identifying a gas transmission flow direction of the laser cutting air compressor, analyzing system key pipelines and equipment flow transfer nodes, configuring an ultrasonic sensor, and obtaining an ultrasonic monitoring signal; collecting gas state data of the laser cutting air compressor system, including temperature, humidity, and pressure; performing abnormal point identification according to the ultrasonic monitoring signal and the gas state data, obtaining abnormal data, and performing abnormal positioning analysis based on the abnormal data to determine an abnormal flow transfer node; positioning a node flow transfer impact parameter and a leakage risk according to the abnormal flow transfer node, configuring an ultrasonic monitoring sensitive parameter by using the abnormal data and the node flow transfer impact parameter and the leakage risk; performing parameter adjustment on the ultrasonic sensor based on the ultrasonic monitoring sensitive parameter to obtain enhanced monitoring data; and performing joint leakage analysis by using the enhanced monitoring data and the abnormal data to obtain a gas leakage detection result.

[0008] In a second aspect, the application further provides a gas leakage detection device for a laser cutting air compressor, which is used to execute the gas leakage detection method for the laser cutting air compressor as described in the first aspect, and includes the following modules: an ultrasonic monitoring signal obtaining module, which is used to identify a gas transmission flow direction of the laser cutting air compressor, analyze system key pipelines and equipment flow transfer nodes, configure an ultrasonic sensor, and obtain an ultrasonic monitoring signal; a gas state data collecting module, which is used to collect gas state data of the laser cutting air compressor system, including temperature, humidity, and pressure; an abnormal flow transfer node determining module, which is used to perform abnormal point identification according to the ultrasonic monitoring signal and the gas state data, obtain abnormal data, and perform abnormal positioning analysis based on the abnormal data to determine an abnormal flow transfer node; an ultrasonic monitoring sensitive parameter configuring module, which is used to position a node flow transfer impact parameter and a leakage risk according to the abnormal flow transfer node, configure an ultrasonic monitoring sensitive parameter by using the abnormal data and the node flow transfer impact parameter and the leakage risk; an enhanced monitoring data obtaining module, which is used to perform parameter adjustment on the ultrasonic sensor based on the ultrasonic monitoring sensitive parameter to obtain enhanced monitoring data; and a gas leakage detection result obtaining module, which is used to perform joint leakage analysis by using the enhanced monitoring data and the abnormal data to obtain a gas leakage detection result.

[0009] The one or more technical solutions provided in the application have at least the following technical effects or advantages:

[0010] By identifying the gas transmission direction of the laser cutting air compressor, analyzing the key pipeline and equipment flow node of the system, configuring the ultrasonic sensor, obtaining the ultrasonic monitoring signal, collecting the gas state data of the laser cutting air compressor system, including temperature, humidity, pressure, identifying the abnormal points according to the ultrasonic monitoring signal and the gas state data, obtaining the abnormal data, and based on the abnormal data, performing abnormal positioning analysis to determine the abnormal flow node, according to the abnormal flow node, positioning the node flow influence parameter and leakage risk, using the abnormal data and the node flow influence parameter and leakage risk, configuring the ultrasonic monitoring sensitive parameter, based on the ultrasonic monitoring sensitive parameter, adjusting the parameter of the ultrasonic sensor, obtaining the enhanced monitoring data, using the enhanced monitoring data and the abnormal data for joint leakage analysis, obtaining the gas leakage detection result, that is, by realizing the technical target of real-time dynamic monitoring of gas flow abnormality and intelligent adjustment of sensor sensitivity, achieving efficient and accurate identification and positioning of potential leakage points, thereby ensuring the stable operation of the laser cutting air compressor, improving the safety of the system, reducing equipment failure and maintenance cost, and improving production efficiency and cutting quality.

[0011] The above description is only a summary of the technical solutions of the present application, in order to more clearly understand the technical means of the present application, the specific embodiments of the present application can be implemented according to the content of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the present application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only exemplary, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of the provided drawings.

[0013] Figure 1 Flowchart of the gas leakage detection method for laser cutting air compressor of the present application;

[0014] Figure 2 Structure diagram of the gas leakage detection device for laser cutting air compressor of the present application.

[0015] Explanation of reference signs:

[0016] An ultrasonic monitoring signal obtaining module 11, a gas state data collecting module 12, an abnormal flow transfer node determining module 13, an ultrasonic monitoring sensitive parameter configuring module 14, an enhanced monitoring data obtaining module 15, and a gas leakage detection result obtaining module 16. DETAILED DESCRIPTION

[0017] The present application provides a gas leakage detection method and device for a laser cutting air compressor, which solves the technical problem in the prior art that it is difficult to dynamically monitor the abnormality of gas flow in the system in real time, most of which lack intelligent and adaptive adjustment mechanisms, resulting in difficulty in discovering and locating gas leakage in time, further affecting the stable operation of the laser cutting air compressor and the cutting quality, increasing the risk of equipment failure, prolonging the maintenance time, and even causing safety hazards and production downtime, thereby affecting the production efficiency and product quality. The technical goal of real-time dynamic monitoring of gas flow abnormalities and intelligent adjustment of sensor sensitivity is achieved, achieving the technical effect of efficiently and accurately identifying and locating potential leakage points, thereby ensuring the stable operation of the laser cutting air compressor, improving the safety of the system, reducing equipment failure and maintenance costs, and improving production efficiency and cutting quality.

[0018] Hereinafter, the technical solutions in the present application will be described clearly and completely with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application. In addition, it should be noted that, for the convenience of description, only parts related to the present application are shown in the drawings, not all.

[0019] Embodiment one, please refer to the accompanying Figure 1 The present application provides a gas leakage detection method for a laser cutting air compressor, which is applied to a gas leakage detection device for a laser cutting air compressor, and specifically includes the following steps:

[0020] Step one: identifying the gas transmission flow direction of the laser cutting air compressor, analyzing the system key pipeline and equipment flow transfer node, configuring ultrasonic sensors, and obtaining ultrasonic monitoring signals.

[0021] Specifically, the gas input from the air compressor inlet passes through air filters, freeze dryers, and other devices, and then the flow direction of the gas in the laser cutting air compressor is identified to obtain the gas transmission flow direction. Next, the system key pipeline and device flow transfer nodes, such as air filters, freeze dryers, etc., are analyzed, and are self-defined by those skilled in the art according to actual conditions. The ultrasonic sensor detects whether there is a leak by monitoring the ultrasonic signal generated by the change in gas flow rate. In order to ensure the accuracy and reliability of the detection, the ultrasonic sensor is configured to detect the sound fluctuations in the gas flow. Through the ultrasonic monitoring signal, the tiny leakage points in the pipeline or device are found in time, so as to effectively prevent and repair. If the ultrasonic sensor detects that the flow rate changes more than five meters per second, it may indicate that there is a leak at a certain pipeline connection, which needs to be checked and repaired immediately.

[0022] Step two: Collecting gas state data of the laser cutting air compressor system, including temperature, humidity, and pressure.

[0023] Specifically, since temperature, humidity, and pressure have important influence on the flow characteristics of the gas and the normal operation of the device, affecting the density and flow rate of the gas, and then affecting the performance of the system and the accuracy of the detection, the key state data of the gas, including temperature, humidity, and pressure, are collected during the monitoring of the operation of the laser cutting air compressor system.

[0024] Step three: Identifying abnormal points according to the ultrasonic monitoring signal and the gas state data, obtaining abnormal data, and performing abnormal positioning analysis based on the abnormal data to determine the abnormal flow transfer node.

[0025] Specifically, the ultrasonic monitoring signal and the gas state data (such as temperature, humidity, and pressure) are combined to identify possible abnormal points. When the ultrasonic signal appears abnormal fluctuation, it can be suspected that there is a leak or blockage in a certain area. By comparing this abnormal signal with the gas state data at that time, the abnormal phenomenon is further confirmed. Then, according to the abnormal data, the positioning analysis is performed to track the gas flow path and identify the abnormal flow transfer node, and the specific position of the abnormal source is determined, then the position is locked as the abnormal flow transfer node, and then the potential fault area in the system is accurately identified and located.

[0026] Step four: According to the abnormal flow transfer node, positioning the node flow transfer influence parameter and the leakage risk, using the abnormal data and the node flow transfer influence parameter and the leakage risk, configuring the ultrasonic monitoring sensitive parameter.

[0027] Specifically, by identifying the abnormal flow transfer node, the impact parameter of the system operation is determined, that is, the node flow transfer impact parameter. The degree of influence of the node anomaly on the overall system through the node flow transfer impact parameter, for example, if the leakage risk is high, it may directly lead to the decline of the cutting effect of the laser cutting machine. Then, the abnormal data, the node flow transfer impact parameter and the leakage risk are combined to configure the sensitive parameters of the ultrasonic sensor. For example, the higher the risk, the higher the sensitivity of the sensor may be set to ensure that subtle leaks can be detected faster and more accurately.

[0028] Step five: parameter adjustment of the ultrasonic sensor based on the ultrasonic monitoring sensitive parameters, to obtain enhanced monitoring data.

[0029] Specifically, the settings of the ultrasonic sensor are adjusted according to the ultrasonic monitoring sensitive parameters, making it more suitable for the current leakage risk state. The ultrasonic monitoring sensitive parameters determine the detection sensitivity and reaction speed of the sensor, and parameter adjustment includes adjustment of sensitivity and sampling frequency, for example, in a high-risk state, the higher the sensitivity and the higher the sampling frequency, so as to more sensitively capture the leakage signal. By adjusting the ultrasonic sensor, more accurate and clear monitoring data can be collected, which helps to discover and analyze gas leakage in a timely manner.

[0030] Step six: joint leakage analysis using the enhanced monitoring data and the abnormal data to obtain a gas leakage detection result.

[0031] Specifically, by analyzing the enhanced monitoring data, combined with the sensitivity and sampling frequency of the ultrasonic sensor after adjustment, more accurate gas flow information and potential leakage signals can be obtained. For example, when the sensitivity of the sensor changes, it can more sensitively capture abnormal fluctuations in gas flow rate or pressure. At the same time, by comparing and combining the enhanced data with the previously identified abnormal data, the specific location of the gas leakage can be determined. Through joint analysis, the location and severity of the gas leakage can be accurately identified, so as to generate a reliable gas leakage detection result.

[0032] The gas leakage detection method for laser cutting air compressor is applied to a gas leakage detection device for laser cutting air compressor, which can achieve the technical goal of real-time dynamic monitoring of gas flow anomalies and intelligent adjustment of sensor sensitivity, and achieve the technical effect of efficiently and accurately identifying and locating potential leakage points, thereby ensuring the stable operation of the laser cutting air compressor, improving the safety of the system, reducing equipment failure and maintenance costs, and improving production efficiency and cutting quality.

[0033] Further, the present application also includes:

[0034] According to the ultrasonic monitoring signal, ultrasonic wave features are extracted, including frequency, intensity, and arrival time; according to the gas state data, propagation influence features and propagation influence coefficients are analyzed; the ultrasonic wave features are corrected using the propagation influence features and propagation influence coefficients, to obtain corrected ultrasonic wave features; based on the gas transmission flow path, the corrected ultrasonic wave features are compared and aligned, to obtain the abnormal data.

[0035] Specifically, when the ultrasonic sensor detects gas flow, the sound wave signal in the transmission process, i.e., the ultrasonic monitoring signal, is captured, and different features of the ultrasonic monitoring signal are extracted, including frequency, intensity, and arrival time. Among them, the frequency represents the vibration speed of the sound wave, the intensity represents the energy size of the sound wave, and the arrival time is the time interval from emission to reception of the sound wave. The ultrasonic wave features help to analyze the gas flow state and whether there is an abnormality, for example, if the frequency and intensity of the ultrasonic wave are significantly abnormal, it may indicate that there is a gas leak or other problems.

[0036] Next, the gas state data includes parameters such as pressure, temperature, and density of the gas, which affect the propagation characteristics of the sound wave in the gas, so the influence features of the sound wave propagation are analyzed according to the actual state of the gas. For example, high-temperature or high-pressure gas may cause changes in the speed of sound wave propagation, thereby affecting the intensity and arrival time of the signal. By analyzing the gas state data, the degree of influence on the sound wave propagation is calculated, and the propagation influence coefficient is obtained.

[0037] Then, since different states of the gas affect the propagation of the sound wave, the features of the ultrasonic wave signal are corrected according to the influence coefficient. For example, if the temperature of the gas is high, the frequency and intensity are adjusted according to the propagation influence coefficient to ensure that the ultrasonic wave signal can truly reflect the gas flow state, so as to more accurately determine whether there is a leak.

[0038] Finally, the transmission path of the gas is fixed in the air compressor system, and whether the ultrasonic wave signal of a certain area is normal is determined by the flow path of the gas. Among them, the corrected ultrasonic wave features are compared with the expected signal pattern, if there is a significant difference, it means that there may be an abnormality, such as a leak or a pipe breakage, thereby generating abnormal data.

[0039] By extracting the sound wave features in the gas flow through the ultrasonic sensor, and correcting these features in combination with the gas state data and the propagation influence coefficient, the abnormal conditions in the system can be more accurately detected, and potential leak points or other problems can be effectively identified, thereby ensuring the stable operation of the laser cutting air compressor system.

[0040] Further, the present application also includes:

[0041] According to the system key pipeline and equipment flow node, the geometric layout of the pipeline and equipment is identified, including pipeline layout and equipment position and the length, diameter, elbow, joint position of the pipeline; according to the historical abnormal case, the potential leakage position is located; according to the gas transmission flow path, a gas flow model is constructed, the geometric layout of the pipeline and equipment and the potential leakage position are fitted into the gas flow model, a space-time correlation model is established, which is used to describe the flow path of gas in the pipeline and equipment and the space-time characteristics of each node on the flow path; the corrected ultrasonic wave feature is fitted into the space-time correlation model, the gas flow signal deviation is identified, and the abnormal data is obtained.

[0042] Specifically, according to the system key pipeline and equipment flow node, the geometric layout of the pipeline and equipment is identified by measurement and other methods, including pipeline layout and equipment position and the length, diameter, elbow, joint position of the pipeline, the direction of the pipeline, the position of each equipment and detailed size parameters are obtained, so as to analyze the flow characteristics of gas in different regions subsequently.

[0043] By analyzing the leakage cases that have occurred in the system, the area where the leakage is most likely to occur is inferred, which helps to identify the part of the system that is most prone to problems, for example, if the historical data shows that the elbow or joint position is more prone to leakage, then these positions become the key detection area, so as to improve the detection efficiency and accuracy.

[0044] Using the geometric layout of the pipeline and equipment and the potential leakage position, a gas flow model is constructed, the geometric layout of the pipeline and equipment and the potential leakage position are parameterized into the gas flow model, thereby generating a space-time correlation model, which not only describes the overall path of gas flow, but also reflects the flow characteristics of gas at a specific position and time point, facilitating the prediction and monitoring of abnormal signals. For example, the space-time correlation model shows that the gas flow rate decreases at the elbow, or the flow rate increases at the long straight pipe.

[0045] Applying the corrected ultrasonic wave feature to the space-time correlation model can accurately analyze the deviation of the gas flow signal, and further identify whether there is abnormal data. If the signal characteristics of some nodes deviate significantly from the standard flow characteristics predicted by the model, it is judged that there may be leakage or equipment failure at this place.

[0046] By identifying the geometric layout of the pipeline of the system, positioning the high-risk area combined with the historical leakage cases, establishing the gas flow and space-time correlation model, and comparing with the corrected ultrasonic signal, the abnormal signal in the gas flow can be accurately identified, and the effective prediction and detection of the leakage position of the system are realized.

[0047] Further, the present application also includes:

[0048] aligning data of all laid ultrasonic sensors according to collection time to determine arrival time of abnormal data; obtaining arrival time difference according to arrival time of all ultrasonic sensors; performing abnormal distance positioning analysis according to the arrival time difference to obtain first abnormal positioning; performing reverse engineering analysis through the space-time correlation model based on the abnormal data to perform spatial abnormal positioning analysis to obtain second abnormal positioning; and performing overlapping positioning using the first abnormal positioning and the second abnormal positioning to obtain the abnormal flow transfer node.

[0049] Specifically, the collection data of all ultrasonic sensors installed in the system are aligned in time sequence to ensure synchronization of time information of signals, so as to more clearly determine the arrival time of abnormal data. For example, if a sensor collects an abnormal intensity signal within two seconds, and other sensors do not appear abnormal within the same time, it may indicate that the abnormal signal first appears at a position near the sensor.

[0050] Then, the arrival time of abnormal data recorded by each sensor is compared to calculate the arrival time difference between different sensors. The time difference reflects the propagation speed and path of the abnormal signal at different positions.

[0051] Through the arrival time difference, the distance of the abnormal signal can be calculated, combined with the signal propagation speed for positioning analysis, to preliminarily determine the position of the abnormal region and obtain the approximate abnormal range. For example, it is calculated that the abnormal signal may appear at a position two meters away from sensor A, thereby forming the first abnormal positioning.

[0052] Using the space-time correlation model, the spatial position of the abnormal data is further analyzed by reverse calculation according to the path of the abnormal data. The reverse engineering analysis method can more accurately locate the abnormal signal source. For example, it is found through reverse analysis that the abnormal signal may be located at a specific elbow of the pipeline, thereby obtaining the second abnormal positioning.

[0053] Finally, the first abnormal positioning and the second abnormal positioning are overlapped and analyzed to determine the intersection point thereof as the final abnormal flow transfer node, thereby accurately identifying the specific position of the leakage or fault. For example, if the results of the two positioning point to the same node, it can be determined that the node is the abnormal flow transfer node.

[0054] By time aligning the data of ultrasonic sensors, calculating the arrival time difference, using the arrival time difference for preliminary abnormal positioning, and then using the space-time correlation model for reverse analysis, and finally overlapping the two positioning results, the abnormal node of gas flow in the system can be accurately positioned, the detection accuracy of the position of gas leakage or fault is improved, and timely measures can be taken.

[0055] Further, the present application also includes:

[0056] The influence relationship between temperature, humidity, pressure and ultrasonic signal propagation is fitted by experimental data, and the influence relationship interval and corresponding influence coefficient are obtained; the influence threshold of temperature, humidity and pressure is obtained by data clustering of the influence relationship interval according to the influence coefficient; the propagation influence feature is obtained by data matching of the gas state data using the influence threshold of temperature, humidity and pressure, the propagation influence feature is the gas state data satisfying the influence threshold, including one or more of temperature, humidity and pressure; the propagation influence coefficient is obtained by mapping matching of the propagation influence feature and the influence coefficient.

[0057] Specifically, the influence relationship between temperature, humidity, pressure and ultrasonic signal propagation is fitted by experimental data, the influence of environmental factors such as temperature, humidity and pressure on ultrasonic signal propagation is determined, and the influence relationship interval and corresponding influence coefficient are obtained. The influence relationship interval indicates that temperature, humidity and pressure will significantly affect the propagation of ultrasonic signals within the influence relationship interval. For example, when the temperature exceeds thirty degrees Celsius, the propagation speed of ultrasonic signals increases, thereby affecting the arrival time and intensity of the signals. In addition, each factor in temperature, humidity and pressure has a corresponding influence coefficient, indicating the specific influence degree of the factor on ultrasonic propagation.

[0058] The ultrasonic signal propagation changes under different environmental conditions are analyzed, and the influence threshold of temperature, humidity and pressure is obtained by data clustering of different values of temperature, humidity and pressure, i.e. data clustering of the influence relationship interval, thereby dividing the interval with significant influence on signal propagation and the interval with less influence on signal propagation.

[0059] The influence threshold of temperature, humidity and pressure is used for data matching of the gas state data, i.e. the actual state data in the gas system is compared with the influence threshold, and the gas state data that will affect the propagation of ultrasonic signals within a specific range is screened out, and the propagation influence feature is obtained. The propagation influence feature is the gas state data satisfying the influence threshold, including one or more of temperature, humidity and pressure.

[0060] By combining the propagation influence feature and the influence coefficient, a corrected propagation influence coefficient is assigned to each specific gas state data by mapping matching method. According to the mapping relationship, the influence coefficient under the combined conditions is calculated, and the propagation characteristics of the ultrasonic signal are corrected.

[0061] By fitting the experimental data to the relationship between temperature, humidity and pressure affecting the propagation of ultrasonic signals, and obtaining the influence coefficient, the environmental conditions that significantly affect the signal propagation are found through data clustering. The actual gas state data is matched using the influence threshold, and the characteristics that meet the influence standard are selected. Based on the characteristics and influence coefficients, the corrected propagation influence coefficient is obtained, and the propagation prediction of the ultrasonic signal is adjusted and optimized, thereby improving the accuracy of gas leakage detection.

[0062] Further, the present application also includes:

[0063] According to the abnormal flow node, a collaborative influence node is identified; according to the abnormal flow node, an influence analysis is performed through historical abnormal cases, and a node flow influence parameter and a leakage risk are located, the node flow influence parameter is an operating parameter of a laser cutting air compressor affected by gas leakage of an abnormal flow node, and the leakage risk describes an influence degree of the node flow influence parameter on a cutting target of the laser cutting air compressor; according to the collaborative influence node, a cumulative influence analysis of gas flow is performed to obtain a collaborative leakage risk; according to the leakage risk and the collaborative leakage risk, a leakage risk trend is obtained; and according to the leakage risk and the leakage risk trend, the ultrasonic monitoring sensitive parameter is configured, and the ultrasonic monitoring sensitive parameter is positively correlated with the leakage risk and the leakage risk trend.

[0064] Specifically, after determining the abnormal flow node, further nodes affected by the abnormal flow node are identified, which are referred to as collaborative influence nodes. The collaborative influence nodes are associated with the abnormal flow node due to connected pipelines, joints or equipment, thereby indirectly affecting gas flow or system operation. For example, if an abnormal flow occurs at a pipeline joint, nodes near the joint may also be affected.

[0065] Using historical abnormal cases, the influence of the identified abnormal flow node is analyzed in detail, and the specific influence of gas leakage of the node on the operating parameters of the air compressor is evaluated, such as how much the gas pressure or flow rate of the system is reduced, thereby affecting the cutting effect. The leakage risk measures the direct influence of these parameter changes on the cutting target, for example, if the gas flow rate decreases by fifty percent, it may result in insufficient or uneven cutting depth.

[0066] Subsequently, cumulative analysis of gas flow of all collaborative influence nodes is performed, and the superimposed risk caused by leakage of multiple nodes is calculated to obtain a collaborative leakage risk. The collaborative leakage risk reflects the comprehensive influence of multiple associated nodes, for example, if the flow rate is reduced by more than one hundred kilopascals due to the cumulative leakage of multiple adjacent nodes, it may significantly affect the quality and accuracy of the entire cutting process.

[0067] The dynamic trend analysis of the leakage risk and the collaborative leakage risk obtains the risk change trend in the future period of time, and obtains the leakage risk trend. For example, if the risk continues to increase, it may indicate that the system leakage problem is getting worse, and timely measures need to be taken for adjustment.

[0068] Finally, according to the leakage risk and the leakage risk trend, the sensitive parameters of the ultrasonic monitoring are adjusted. The sensitivity of the parameter setting should be positively correlated with the leakage risk. Among them, the greater the risk trend is, the higher the sensitivity is, at the same time, the greater the risk is, the higher the sensitivity is, on the contrary, the lower the sensitivity is, but when the risk is greater and the risk trend is getting smaller, the sensitivity is lower. For example, in the high risk trend, the sensitivity of the ultrasonic sensor is improved to detect small leaks earlier.

[0069] Through the risk analysis result, the change trend of the leakage risk is further obtained, and the ultrasonic monitoring parameters are configured accordingly to detect the system risk in time and ensure the stable operation of the laser cutting air compressor.

[0070] Further, the present application also includes:

[0071] The collection sensitive parameters of the ultrasonic sensor and the adjustment range are obtained; the sensitive parameter configuration relationship between the ultrasonic monitoring sensitive parameters and the collection data timeliness and the collection data accuracy is established; the adjustment range is taken as a constraint, the adaptive fuzzy list is set according to the sensitive parameter configuration relationship, which includes the leakage risk, the leakage risk trend and the corresponding ultrasonic monitoring sensitive parameters; the leakage risk and the leakage risk trend are used as input quantities, and the adaptive matching is performed through the adaptive fuzzy list to obtain the ultrasonic monitoring sensitive parameters.

[0072] Specifically, the collection sensitive parameters of the ultrasonic sensor and the adjustable range are obtained. The collection sensitive parameters include the signal strength of the sensor, the collection frequency, etc., which directly affect the detection accuracy and response speed of the data. The adjustment range is the range of adjustment of the collection sensitive parameters. For example, the signal strength range of a certain sensor is one to ten units, the collection frequency is five to ten times per second, and the adjustment range is the upper and lower limits of these parameters.

[0073] Then, the collection data timeliness reflects the real-time of data collection, and the collection data accuracy represents the accuracy of the collected data. The configuration relationship between the ultrasonic monitoring sensitive parameters and the collection data timeliness, and the configuration relationship between the ultrasonic monitoring sensitive parameters and the collection data accuracy are established, which illustrates the influence of sensitive parameters on data collection effect under different configuration conditions. For example, when the signal strength is set to eight units and the collection frequency is ten times per second, the data timeliness may reach zero point one second and the accuracy reaches 95%.

[0074] Then, using the adjustment range as a limiting condition, an adaptive fuzzy list is generated based on the sensitive parameter configuration relationship. The adaptive fuzzy list contains leakage risk, leakage risk trend, and corresponding ultrasonic monitoring sensitive parameters. For example, when the leakage risk is high and the trend is increasing, the adaptive fuzzy list recommends a high-sensitivity monitoring parameter configuration.

[0075] Finally, the leakage risk and risk trend are input into the adaptive fuzzy list for matching, thereby obtaining the ultrasonic monitoring sensitive parameters suitable for the current risk situation. For example, when the leakage risk reaches eighty and the risk trend increases, the adaptive fuzzy list automatically matches a high-frequency, high-intensity acquisition configuration to ensure rapid and accurate monitoring of the leakage situation.

[0076] By obtaining the sensitive parameters and adjustment range of the ultrasonic sensor and establishing the relationship between the parameters and the data acquisition timeliness and accuracy, an adaptive fuzzy list is generated based thereon, and the leakage risk and trend are used as inputs for adaptive matching, thereby achieving automatic adjustment of the sensitive parameters of the ultrasonic sensor to adapt to the detection requirements under different risk conditions.

[0077] In summary, the gas leakage detection method for laser cutting air compressors provided in the present application has the following technical effects:

[0078] By identifying the gas transmission flow direction of the laser cutting air compressor, analyzing the key pipeline and equipment flow nodes of the system, configuring the ultrasonic sensor, obtaining the ultrasonic monitoring signal, collecting the gas state data of the laser cutting air compressor system, including temperature, humidity, and pressure, identifying abnormal points based on the ultrasonic monitoring signal and the gas state data, obtaining abnormal data, and performing abnormal positioning analysis based on the abnormal data to determine the abnormal flow nodes, positioning the node flow influence parameters and leakage risk based on the abnormal flow nodes, configuring the ultrasonic monitoring sensitive parameters using the abnormal data and the node flow influence parameters and leakage risk, adjusting the parameters of the ultrasonic sensor based on the ultrasonic monitoring sensitive parameters to obtain enhanced monitoring data, and performing joint leakage analysis using the enhanced monitoring data and the abnormal data to obtain the gas leakage detection result, that is, by achieving the technical goals of real-time dynamic monitoring of gas flow abnormalities and intelligent adjustment of sensor sensitivity, the potential leakage points are efficiently and accurately identified and located, thereby ensuring the stable operation of the laser cutting air compressor, improving the safety of the system, reducing equipment failure and maintenance costs, and improving production efficiency and cutting quality.

[0079] Embodiment two, based on the gas leakage detection method for laser cutting air compressors in the preceding embodiments, the same inventive concept is provided, and the present application also provides a gas leakage detection device for laser cutting air compressors, please refer to the attached Figure 2 , including:

[0080] An ultrasonic monitoring signal obtaining module 11 is configured to identify the gas transmission flow direction of the laser cutting air compressor, analyze the system key pipeline and equipment flow transfer node, configure the ultrasonic sensor, and obtain the ultrasonic monitoring signal; a gas state data acquisition module 12 is configured to acquire the gas state data of the laser cutting air compressor system, including temperature, humidity, and pressure; an abnormal flow transfer node determination module 13 is configured to identify abnormal points according to the ultrasonic monitoring signal and the gas state data, obtain abnormal data, and determine abnormal flow transfer nodes based on abnormal positioning analysis of the abnormal data; an ultrasonic monitoring sensitive parameter configuration module 14 is configured to locate node flow transfer impact parameters and leakage risk according to the abnormal flow transfer nodes, and configure ultrasonic monitoring sensitive parameters using the abnormal data and the node flow transfer impact parameters and leakage risk; an enhanced monitoring data obtaining module 15 is configured to adjust the parameters of the ultrasonic sensor based on the ultrasonic monitoring sensitive parameters to obtain enhanced monitoring data; and a gas leakage detection result obtaining module 16 is configured to perform joint leakage analysis using the enhanced monitoring data and the abnormal data to obtain a gas leakage detection result.

[0081] Further, the gas leakage detection device for the laser cutting air compressor is also used for:

[0082] According to the ultrasonic monitoring signal, ultrasonic wave features are extracted, including frequency, intensity, and arrival time; according to the gas state data, propagation impact features and propagation impact coefficients are analyzed; the ultrasonic wave features are corrected using the propagation impact features and propagation impact coefficients to obtain corrected ultrasonic wave features; and based on the gas transmission flow transfer path, the corrected ultrasonic wave features are compared for feature alignment to obtain the abnormal data.

[0083] Further, the gas leakage detection device for the laser cutting air compressor is also used for:

[0084] According to the system key pipeline and equipment flow node, the geometric layout of the pipeline and equipment is identified, including pipeline layout and equipment position and pipeline length, diameter, elbow, joint position; according to the historical abnormal case, the potential leakage position is located; according to the gas transmission flow path, a gas flow model is constructed, the geometric layout of the pipeline and equipment and the potential leakage position are fitted into the gas flow model, a space-time correlation model is established, which is used to describe the flow path of gas in the pipeline and equipment and the space-time characteristics of each node on the flow path; the corrected ultrasonic wave feature is fitted into the space-time correlation model, the gas flow signal deviation is identified, and the abnormal data is obtained.

[0085] Further, the gas leakage detection device for laser cutting air compressor is also used for:

[0086] All laid ultrasonic sensors are aligned according to the collection time to determine the arrival time of abnormal data; the arrival time difference is obtained according to the arrival time of all ultrasonic sensors; the abnormal distance positioning analysis is performed according to the arrival time difference to obtain the first abnormal positioning; based on the abnormal data, the reverse engineering analysis is performed through the space-time correlation model to perform the spatial abnormal positioning analysis to obtain the second abnormal positioning; the first abnormal positioning and the second abnormal positioning are used for overlapping positioning to obtain the abnormal flow node.

[0087] Further, the gas leakage detection device for laser cutting air compressor is also used for:

[0088] The influence relationship of temperature, humidity, pressure on ultrasonic signal propagation is fitted through test data to obtain the influence relationship interval and the corresponding influence coefficient; according to the influence coefficient, the influence relationship interval is data clustered to obtain the influence threshold of temperature, humidity and pressure respectively; the influence threshold of temperature, humidity and pressure is used for data matching of the gas state data to obtain the propagation influence feature, the propagation influence feature is the gas state data satisfying the influence threshold, including one or more of temperature, humidity and pressure; the propagation influence feature is mapped and matched with the influence coefficient to obtain the propagation influence coefficient.

[0089] Further, the gas leakage detection device for laser cutting air compressor is also used for:

[0090] According to the abnormal flow transfer node, a synergistic influence node is identified; according to the abnormal flow transfer node, an influence analysis is performed through a historical abnormal case, a node flow transfer influence parameter and a leakage risk are located, the node flow transfer influence parameter is an operation parameter of a laser cutting air compressor affected by gas leakage of an abnormal flow transfer node, and the leakage risk describes an influence degree of the node flow transfer influence parameter on a completed cutting target of the laser cutting air compressor; according to the synergistic influence node, a gas flow transfer cumulative influence analysis is performed to obtain a synergistic leakage risk; according to the leakage risk and the synergistic leakage risk, a leakage risk trend is obtained; and according to the leakage risk and the leakage risk trend, the ultrasonic monitoring sensitive parameter is configured, and the ultrasonic monitoring sensitive parameter is positively correlated with the leakage risk and the leakage risk trend.

[0091] Further, the gas leakage detection device for the laser cutting air compressor is also used for:

[0092] The acquisition sensitive parameter and the adjustment range of the ultrasonic sensor are obtained; an ultrasonic monitoring sensitive parameter and a sensitive parameter configuration relationship of acquisition data timeliness and acquisition data accuracy are established; the adjustment range is taken as a constraint, the adaptive fuzzy list is set according to the sensitive parameter configuration relationship, and the adaptive fuzzy list includes the leakage risk, the leakage risk trend and the corresponding ultrasonic monitoring sensitive parameter; the leakage risk and the leakage risk trend are used as input quantities, adaptive matching is performed through the adaptive fuzzy list, and the ultrasonic monitoring sensitive parameter is obtained.

[0093] Each embodiment in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The gas leakage detection method for the laser cutting air compressor in the first embodiment and the specific examples are also applicable to the gas leakage detection device for the laser cutting air compressor in the present embodiment. Through the foregoing detailed description of the gas leakage detection method for the laser cutting air compressor, those skilled in the art can clearly know the gas leakage detection device for the laser cutting air compressor in the present embodiment. Therefore, for the sake of brevity of the specification, the gas leakage detection device for the laser cutting air compressor in the present embodiment is not described in detail.

[0094] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0095] Obviously, many modifications and variations of the present application are possible in light of the above teachings. It is, therefore, to be understood that within the scope of the application and its equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method for detecting gas leakage of a laser-cut air compressor, characterized by, The method comprises the following steps: Identify the gas transmission flow direction of the laser cutting air compressor, analyze the system key pipeline and equipment flow node, configure the ultrasonic sensor, and obtain the ultrasonic monitoring signal; Collect the gas state data of the laser cutting air compressor system, including temperature, humidity, and pressure; According to the ultrasonic monitoring signal and the gas state data, identify the abnormal points, obtain the abnormal data, and based on the abnormal data, perform abnormal positioning analysis to determine the abnormal flow node, including: According to the ultrasonic monitoring signal, extract the ultrasonic wave features, including frequency, intensity, and arrival time; According to the gas state data, analyze the propagation influence features and propagation influence coefficients; Using the propagation influence features and propagation influence coefficients, correct the ultrasonic wave features to obtain the corrected ultrasonic wave features; Based on the gas transmission flow path, align and compare the corrected ultrasonic wave features to obtain the abnormal data, including: According to the system key pipeline and equipment flow node, identify the geometric layout of the pipeline and equipment, including pipeline layout, equipment position, pipeline length, diameter, elbow, and joint position; According to historical abnormal cases, locate the potential leakage position; According to the gas transmission flow path, construct a gas flow model, fit the geometric layout of the pipeline and equipment and the potential leakage position into the gas flow model to establish a space-time correlation model, which is used to describe the flow path of gas in the pipeline and equipment and the space-time features of each node on the flow path; Fit the corrected ultrasonic wave features into the space-time correlation model to identify the deviation of the gas flow signal and obtain the abnormal data; According to the abnormal flow node, locate the node flow influence parameters and leakage risk, configure the ultrasonic monitoring sensitive parameters using the abnormal data and the node flow influence parameters and leakage risk; Based on the ultrasonic monitoring sensitive parameters, adjust the parameters of the ultrasonic sensor to obtain enhanced monitoring data; Use the enhanced monitoring data and the abnormal data for joint leakage analysis to obtain the gas leakage detection result.

2. The method for detecting a gas leakage of a laser-cut air compressor according to claim 1, wherein, Based on the abnormal data, perform abnormal positioning analysis to determine the abnormal flow node, including: Align all the ultrasonic sensors according to the collection time to determine the arrival time of the abnormal data; According to the arrival time of all ultrasonic sensors, obtain the arrival time difference; According to the arrival time difference, perform abnormal distance positioning analysis to obtain the first abnormal positioning; Based on the abnormal data, perform reverse engineering analysis through the space-time correlation model to perform spatial abnormal positioning analysis and obtain the second abnormal positioning; Use the first abnormal positioning and the second abnormal positioning for overlapping positioning to obtain the abnormal flow node.

3. The method for detecting gas leakage of a laser-cut air compressor according to claim 1, wherein, According to the gas state data, analyze the propagation influence features and propagation influence coefficients, including: Fit the influence relationship between temperature, humidity, pressure and ultrasonic signal propagation through experimental data to obtain the influence relationship interval and the corresponding influence coefficient; According to the influence coefficient, perform data clustering on the influence relationship interval to obtain the influence threshold of temperature, humidity, and pressure respectively; The gas state data is matched by using the influence threshold of the temperature, humidity, and pressure, and the propagation influence feature is obtained, the propagation influence feature being the gas state data satisfying the influence threshold, including one or more of temperature, humidity, and pressure; The propagation influence coefficient is obtained by mapping matching the propagation influence feature and the influence coefficient.

4. The method for detecting gas leakage of a laser-cut air compressor according to claim 1, wherein, According to the abnormal flow transfer node, the node flow transfer influence parameter and the leakage risk are located, and the ultrasonic monitoring sensitive parameter is configured by using the abnormal data and the node flow transfer influence parameter and the leakage risk, including: According to the abnormal flow transfer node, the collaborative influence node is identified; According to the abnormal flow transfer node, the influence analysis is performed through the historical abnormal cases, the node flow transfer influence parameter and the leakage risk are located, the node flow transfer influence parameter being the operation parameter of the laser cutting air compressor affected by the abnormal flow transfer node gas leakage, and the leakage risk describing the influence degree of the node flow transfer influence parameter on the completion of the cutting target of the laser cutting air compressor; According to the collaborative influence node, the gas flow transfer cumulative influence analysis is performed to obtain the collaborative leakage risk; According to the leakage risk and the collaborative leakage risk, the leakage risk trend is obtained; According to the leakage risk and the leakage risk trend, the ultrasonic monitoring sensitive parameter is configured, and the ultrasonic monitoring sensitive parameter is positively correlated with the leakage risk and the leakage risk trend.

5. The method for detecting a gas leakage of a laser-cut air compressor according to claim 4, wherein, According to the leakage risk and the leakage risk trend, the ultrasonic monitoring sensitive parameter is configured, including: The acquisition sensitive parameter and the adjustment range of the ultrasonic sensor are obtained; An ultrasonic monitoring sensitive parameter and sensitive parameter configuration relationship of acquisition data timeliness and acquisition data accuracy are established; The adjustment range is taken as a constraint, the adaptive fuzzy list including the leakage risk, the leakage risk trend, and the corresponding ultrasonic monitoring sensitive parameter is set according to the sensitive parameter configuration relationship; The leakage risk and the leakage risk trend are used as input quantities, and the ultrasonic monitoring sensitive parameter is obtained by adaptive matching through the adaptive fuzzy list.

6. A gas leakage detection device for a laser cutting air compressor, characterized by, Steps for implementing the gas leakage detection method for the laser cutting air compressor in any one of claims 1 to 5, including: An ultrasonic monitoring signal obtaining module is configured to identify the gas transmission direction of the laser cutting air compressor, analyze the system key pipeline and device flow transfer node, and configure the ultrasonic sensor to obtain the ultrasonic monitoring signal; A gas state data acquisition module is configured to acquire the gas state data of the laser cutting air compressor system, including temperature, humidity, and pressure; An abnormal flow transfer node determination module is configured to identify abnormal points according to the ultrasonic monitoring signal and the gas state data, obtain abnormal data, and determine abnormal flow transfer nodes based on abnormal positioning analysis of the abnormal data; An ultrasonic monitoring sensitive parameter configuration module is configured to locate a node flow transfer influence parameter and a leakage risk according to the abnormal flow transfer node, and configure an ultrasonic monitoring sensitive parameter by using the abnormal data and the node flow transfer influence parameter and the leakage risk. An enhanced monitoring data obtaining module is configured to perform parameter adjustment on the ultrasonic sensor based on the ultrasonic monitoring sensitive parameter, and obtain enhanced monitoring data. A gas leakage detection result obtaining module is configured to perform joint leakage analysis by using the enhanced monitoring data and the abnormal data, and obtain a gas leakage detection result.

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