Detection method and system for automatic drain valve

Abstract

The invention provides a detection method and system for an automatic drain valve, and relates to the technical field of equipment testing. The method comprises the following steps: collecting working data of a drain valve to be detected; determining a flow peak change trend and a drainage efficiency attenuation degree based on flow data of continuous multiple drainage records, and generating an impurity deposition index; generating an impurity stripping index based on the instantaneous change rate of the flow velocity data and the variable quantity of the flow data, and determining a first impurity deposition degree in combination with an impurity deposition index; determining a vibration anomaly factor and an acoustic anomaly factor based on the vibration data and the acoustic data, and determining an impurity anomaly score in combination with the first impurity deposition degree; determining the working intensity based on the vibration data, the pressure data and the liquid level data, obtaining the drainage frequency of the drainage valve to be detected after last maintenance, and determining the fault probability based on the working intensity, the drainage frequency and the impurity anomaly score; and predicting the fault condition of the to-be-detected drain valve based on the fault probability. The fault detection accuracy is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of device testing, in particular to a detection method and system of an automatic drain valve. BACKGROUND

[0002] The automatic drain valve is a key component in the industrial fluid system, and its running state directly determines the energy efficiency level and running safety of the system. During the long-term operation of the industrial system, condensate water is continuously generated due to temperature fluctuations or medium condensation. The condensate water often contains impurities such as dust in the air, rust slag generated by pipeline corrosion, oil mist left by system lubrication, and scale formed by medium crystallization. If such condensate water containing impurities cannot be discharged in time, it will continue to accumulate in the system, and then cause a series of serious problems: on the one hand, it accelerates the corrosion of the inner wall of the pipeline, shortening the service life of the pipeline; on the other hand, it causes functional failures such as jamming failure of pneumatic elements, significant reduction of heat exchange efficiency of heat exchangers, and vacuum degree reduction of vacuum pumps, and in extreme cases, it can cause the entire industrial system to stop, causing significant economic losses to production and operation.

[0003] The related art usually detects the automatic drain valve by using traditional manual operation, specifically including visual inspection of the drainage state, manual start-stop test of the valve response, and judgment of whether the valve working sound is abnormal by hearing. However, the above detection methods mainly adopt post-maintenance or regular inspection strategies. From the time effectiveness of detection, the post-maintenance strategy only intervenes in maintenance after the drain valve fails or the system has problems due to drainage, lacks early warning capability, and cannot avoid system loss before failure. The regular inspection strategy carries out detection according to a fixed cycle, but if impurities accumulate rapidly during the interval between two inspections, a detection blind area is easily formed, leading to failure to discover the fault in time and expanding the influence range. SUMMARY

[0004] Therefore, the present application provides a detection method and system of an automatic drain valve to solve the problems that the post-maintenance strategy in the related art cannot avoid system loss before failure, and the regular inspection strategy easily forms a detection blind area when impurities accumulate rapidly during the interval between two inspections, leading to failure to discover the fault in time and expanding the influence range.

[0005] According to a first aspect of the present application, a detection method of an automatic drain valve is provided, and the technical solution is as follows: Collect working data of a drain valve to be detected, the working data including flow data, flow rate data, vibration data, acoustic data, pressure data, and liquid level data; Determine a flow peak value change trend and a drainage efficiency attenuation degree based on the flow data of continuous multiple drainage records, and generate an impurity deposition index based on the flow peak value change trend and the drainage efficiency attenuation degree; generate an impurity stripping index based on the instantaneous change rate of the flow rate data and the change amount of the corresponding flow data, and determine a first impurity deposition degree based on the impurity deposition index and the impurity stripping index; determine a vibration anomaly factor and an acoustic anomaly factor based on the vibration data and the acoustic data, and determine an impurity anomaly score of the to-be-detected drain valve based on the vibration anomaly factor, the acoustic anomaly factor, and the first impurity deposition degree; determine a working intensity based on the vibration data, the pressure data, and the liquid level data, obtain a drain frequency of the to-be-detected drain valve since the last maintenance, and determine a failure probability based on the working intensity, the drain frequency, and the impurity anomaly score; predict a failure condition of the to-be-detected drain valve based on the failure probability.

[0006] Exemplarily, the flow data based on the continuous multiple drainage records is used to determine a flow peak change trend and a drainage efficiency attenuation degree, and an impurity deposition index is generated based on the flow peak change trend and the drainage efficiency attenuation degree, including: obtaining a flow peak value in the flow data of the continuous multiple drainage records, and constructing a flow peak change curve with the number of drainages as the independent variable and the flow peak value corresponding to the number of drainages as the dependent variable; performing linear fitting on the flow peak change curve, and determining the slope of the fitted straight line, denoted as the flow peak change trend; obtaining a first drainage amount and a first drainage time of the first drainage of the to-be-detected drain valve since the last maintenance, and determining a first drainage efficiency based on the first drainage amount and the first drainage time; obtaining a current drainage amount and a current drainage time of the current drainage of the to-be-detected drain valve since the last maintenance, and determining a current drainage efficiency based on the current drainage amount and the current drainage time; determining an effective drainage time based on the flow data in the current drainage process; determining the drainage efficiency attenuation degree based on the first drainage efficiency, the current drainage efficiency, and the effective drainage time; and calculating the product of the absolute value of the flow peak change trend and the drainage efficiency attenuation degree to generate the impurity deposition index.

[0007] Exemplarily, the effective drainage time is determined based on the flow data in the current drainage process, including: obtaining a system design maximum flow of the to-be-detected drain valve, calculating the product of the system design maximum flow and a preset proportion to obtain a flow threshold; obtaining target flow data not less than the flow threshold in the current drainage process, and determining the sum of drainage times corresponding to the target flow data, denoted as the effective drainage time.

[0008] Exemplarily, the impurity deposition indicator and the impurity stripping indicator are generated based on the instantaneous change rate of the flow rate data and the change amount of the flow data corresponding to the instantaneous change rate, and the first impurity deposition degree is determined based on the impurity deposition indicator and the impurity stripping indicator, including: for each sampling time in the current drainage, the flow data and the flow rate data at the current sampling time and the previous sampling time are obtained; the instantaneous change rate of the flow rate data at the current sampling time is determined based on the difference between the flow rate data at the current sampling time and the previous sampling time and the sampling interval, and the flow rate turning point is determined based on the instantaneous change rate of the flow rate data; the difference between the instantaneous change rates of the flow rate data at the current sampling time and the previous sampling time corresponding to the flow rate turning point is determined, and is recorded as a first change amount; the difference between the flow data at the current sampling time and the previous sampling time corresponding to the flow rate turning point is determined, and is recorded as a second change amount; the product of the first change amount and the second change amount is determined to obtain the impurity stripping indicator; and the product of the impurity deposition indicator and the impurity stripping indicator is determined to obtain the first impurity deposition degree.

[0009] Exemplarily, the vibration data is valve vibration data in the drainage process collected by a vibration sensor installed on the outer wall of the drainage valve to be detected; the acoustic data is sound data emitted by the valve in the drainage process collected by an acoustic sensor installed on the outer wall of the drainage valve to be detected; and the vibration abnormal factor and the acoustic abnormal factor are determined based on the vibration data and the acoustic data, including: for each sampling time in the current drainage, the actual vibration amplitude and the actual vibration frequency collected by the vibration sensor, and the actual noise intensity and the actual noise frequency collected by the acoustic sensor are obtained; the set upper limit of the vibration amplitude and the set upper limit of the vibration frequency of the drainage valve to be detected are obtained, the difference between the actual vibration amplitude and the set upper limit of the vibration amplitude, and the difference between the actual vibration frequency and the set upper limit of the vibration frequency are calculated; the product of the difference between the vibration amplitude and the difference between the vibration frequency is determined, and is recorded as the vibration abnormal factor; the set upper limit of the noise intensity and the set upper limit of the noise frequency of the drainage valve to be detected are obtained, the difference between the actual noise intensity and the set upper limit of the noise intensity, and the difference between the actual noise frequency and the set upper limit of the noise frequency are calculated; and the product of the difference between the noise intensity and the difference between the noise frequency is determined, and is recorded as the acoustic abnormal factor.

[0010] Illustratively, the determining the impurity anomaly score of the to-be-detected drain valve based on the vibration anomaly factor, the acoustic anomaly factor and the first impurity deposition degree comprises: determining a mean value of the vibration anomaly factor at each of the sampling time points in the current drainage process, denoted as a vibration anomaly score of the current drainage; determining a mean value of the acoustic anomaly factor at each of the sampling time points in the current drainage process, denoted as an acoustic anomaly score of the current drainage; determining an anomaly correlation factor of the vibration anomaly score and the acoustic anomaly score; determining a second impurity deposition degree based on the anomaly correlation factor, the vibration anomaly score and the acoustic anomaly score; determining a confidence degree of the first impurity deposition degree based on the first impurity deposition degree and the second impurity deposition degree, and taking a product of the first impurity deposition degree and the confidence degree as the impurity anomaly score.

[0011] Illustratively, the determining the anomaly correlation factor of the vibration anomaly score and the acoustic anomaly score comprises: determining a product of the vibration anomaly score and the acoustic anomaly score, denoted as a sensor anomaly score product; determining an absolute value of a difference between the vibration anomaly score and the acoustic anomaly score, denoted as a sensor anomaly score difference absolute value; and determining a ratio of the sensor anomaly score product and the sensor anomaly score difference absolute value to obtain the anomaly correlation factor of the vibration anomaly score and the acoustic anomaly score.

[0012] Exemplarily, the vibration data is valve vibration data in the process of drainage collected by a vibration sensor installed on the outer wall of the drainage valve to be detected; the pressure data is valve inner side pressure data in the process of drainage collected by a pressure sensor installed on the inner side of the drainage valve to be detected; the liquid level data is the liquid surface height of accumulated water in the system to which the drainage valve to be detected belongs, collected by a liquid level sensor internally provided on the inner side of the drainage valve to be detected; and the determination of the working intensity based on the vibration data, the pressure data and the liquid level data comprises: for the current drainage, first pressure data collected by the pressure sensor before the current drainage and second pressure data collected by the pressure sensor after the current drainage are acquired, and a difference between the first pressure data and the second pressure data is calculated and recorded as a pre-post drainage pressure difference; a vibration amplitude average value acquired by the vibration sensor in the current drainage process is acquired, and the equipment operation intensity is determined based on the vibration amplitude average value and the pre-post drainage pressure difference; the maximum liquid level data of a water storage device in the system to which the drainage valve to be detected belongs and the current liquid level data collected by the liquid level sensor are acquired, and the theoretical drainage amount is determined based on the maximum liquid level data, the current liquid level data and the volume of the water storage device; the actual drainage amount of the current drainage is acquired, and a difference between the actual drainage amount and the theoretical drainage amount is recorded as a residual impurity value; and the working intensity is determined based on the effective drainage time, the equipment operation intensity and the residual impurity value.

[0013] Exemplarily, the prediction of the failure condition of the drainage valve to be detected based on the failure probability comprises: acquiring the liquid level data before the next drainage; predicting a failure probability increase amount of the next drainage relative to the current drainage based on the liquid level data before the next drainage and the failure probability of the current drainage; determining the failure probability of the next drainage based on the failure probability of the current drainage and the failure probability increase amount; and if the failure probability of the next drainage is greater than a preset threshold, sending an instruction of stopping working to the drainage valve to be detected, and performing maintenance on the drainage valve to be detected.

[0014] According to a second aspect of the present disclosure, there is provided a detection system of an automatic drainage valve, specifically as follows: a data acquisition module, configured to acquire working data of a drainage valve to be detected, the working data comprising flow data, flow rate data, vibration data, acoustic data, pressure data and liquid level data; a data processing module, configured to determine a flow peak value change trend and a drainage efficiency attenuation degree based on the flow data recorded in continuous multiple drainages, and generate an impurity deposition index based on the flow peak value change trend and the drainage efficiency attenuation degree; The data processing module is further configured to generate an impurity peeling index based on the instantaneous change rate of the flow rate data and the corresponding change amount of the flow data, and determine a first impurity deposition degree based on the impurity deposition index and the impurity peeling index. The data processing module is further configured to determine a vibration anomaly factor and an acoustic anomaly factor based on the vibration data and the acoustic data, and determine an impurity anomaly score of the to-be-detected drain valve based on the vibration anomaly factor, the acoustic anomaly factor, and the first impurity deposition degree. The data processing module is further configured to determine a working intensity based on the vibration data, the pressure data, and the liquid level data, obtain a drain frequency of the to-be-detected drain valve since the last maintenance, and determine a failure probability based on the working intensity, the drain frequency, and the impurity anomaly score. The failure detection module is configured to predict a failure condition of the to-be-detected drain valve based on the failure probability.

[0015] The present application can have the following partial or all beneficial effects: In the detection method of the automatic drain valve provided by the present application, the flow peak change trend and the drain efficiency attenuation degree are determined based on the flow data recorded by multiple continuous drainages, the impurity deposition index is generated based on the flow peak change trend and the drain efficiency attenuation degree, the impurity peeling index is generated based on the instantaneous change rate of the flow rate data and the corresponding change amount of the flow data, and the first impurity deposition degree is determined based on the impurity deposition index and the impurity peeling index, so that the data change of the flow and the flow rate during the working process of the to-be-detected drain valve can be utilized to analyze the impurity deposition degree at the valve of the to-be-detected drain valve, and the prediction accuracy of the blockage degree of the to-be-detected drain valve is improved. In addition, the vibration anomaly factor and the acoustic anomaly factor are determined based on the vibration data and the acoustic data, and the impurity anomaly score of the to-be-detected drain valve is determined based on the vibration anomaly factor, the acoustic anomaly factor, and the first impurity deposition degree, so that the first impurity deposition degree can be verified in combination with the multi-modal data such as the vibration data and the acoustic data, and the reliability of the failure prediction of the to-be-detected drain valve is further improved. Meanwhile, the working intensity is determined based on the vibration data, the pressure data, and the liquid level data, the drain frequency of the to-be-detected drain valve since the last maintenance is obtained, the failure probability is determined based on the working intensity, the drain frequency, and the impurity anomaly score, and the failure condition of the to-be-detected drain valve is predicted based on the failure probability. The working intensity of the to-be-detected drain valve is dynamically evaluated through the changes of the liquid level and the pressure before and after the working of the to-be-detected drain valve, the failure probability is calculated in combination with the drain frequency and the impurity anomaly score, the early prediction of the failure of the to-be-detected drain valve is realized, and the hysteresis of the manual maintenance is effectively solved.

[0016] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart of a detection method for an automatic drain valve according to an exemplary embodiment of the present disclosure is shown; Figure 2 A schematic diagram of the flow peak variation curve in the detection method of the automatic drain valve according to an exemplary embodiment of the present disclosure is shown; Figure 3 A schematic block diagram of a detection system for an automatic drain valve according to an exemplary embodiment of the present disclosure is shown. Detailed Implementation

[0019] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an automatic drain valve detection method and system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] The following description, in conjunction with the accompanying drawings, details the specific scheme of the detection method and system for an automatic drain valve provided by the present invention.

[0022] Please see Figure 1 It shows a flowchart of a method for detecting an automatic drain valve according to an embodiment of the present invention, as follows. Figure 1 As shown, the testing method for this automatic drain valve specifically includes the following steps: S110: Collects the operating data of the drain valve under test, including flow rate data, velocity data, vibration data, acoustic data, pressure data, and liquid level data; S120: Determine the peak flow rate change trend and the degree of drainage efficiency decay based on the flow rate data from multiple consecutive drainage records, and generate an impurity deposition index based on the peak flow rate change trend and the degree of drainage efficiency decay. S130: generate a foreign matter peeling index based on the instantaneous change rate of the flow rate data and the change amount of the corresponding flow data, and determine a first foreign matter deposition degree based on the foreign matter deposition index and the foreign matter peeling index; S140: determine a vibration anomaly factor and an acoustic anomaly factor based on the vibration data and the acoustic data, and determine a foreign matter anomaly score of the to-be-detected drain valve based on the vibration anomaly factor, the acoustic anomaly factor, and the first foreign matter deposition degree; S150: determine a working intensity based on the vibration data, the pressure data, and the liquid level data, obtain a drain frequency of the to-be-detected drain valve since the last maintenance, and determine a failure probability based on the working intensity, the drain frequency, and the foreign matter anomaly score; S160: predict a failure condition of the to-be-detected drain valve based on the failure probability.

[0023] Next, each step of the above automatic drain valve detection method will be described in detail: In step S110, working data of the to-be-detected drain valve is collected, including flow data, flow rate data, vibration data, acoustic data, pressure data, and liquid level data.

[0024] In the embodiments of the present application, the above to-be-detected drain valve can be any automatic drain valve deployed in a certain industrial system for draining condensate and other liquids in the industrial system. During the drainage process, the liquid discharged may contain particulate matter, oily substances, and crystalline substances, etc. When the liquid passes through the valve, the above-mentioned impurities are adsorbed and deposited on the wall surface or filter screen of the valve. As the liquid continuously flows through the automatic drain valve, the impurity layer gradually thickens until it blocks the entire liquid passage of the to-be-detected drain valve. In addition, due to the periodic opening of the to-be-detected drain valve, the instantaneous increase in water flow will impact the outermost layer of impurities, thereby removing the loose impurities on the outermost layer, and the deep deposits are compressed and reinforced to form a more compact impurity layer, which eventually leads to complete blockage of the drain valve at a certain moment. The automatic drain valve detection method provided in the embodiments of the present application assesses the possibility of the to-be-detected drain valve being blocked and maintains the to-be-detected drain valve.

[0025] In the embodiments of the present application, the above working data is each data generated by the to-be-detected drain valve during the drainage process. For example, the working data can include flow data, flow rate data, vibration data, acoustic data, pressure data, and liquid level data.

[0026] In the embodiments of the present application, the above flow data is the size of the water flow of the to-be-detected drain valve during the drainage process. For example, the flow data can be collected by a flow sensor at the valve of the to-be-detected drain valve, which reflects the degree of unobstructedness of the valve passage and the influence of the deposition of the above-mentioned impurities on the water flow.

[0027] In the embodiments of the present application, the flow rate data is the speed of water flow through the valve of the drainage valve to be detected during the drainage process. Exemplarily, the flow rate data can be converted from the flow data and the cross-sectional area of the valve based on the basic formula of fluid mechanics, or can be directly collected by a flow rate sensor, for analyzing the change of the flow rate to determine the condition of the impurity stripping valve.

[0028] In the embodiments of the present application, the vibration data includes the vibration amplitude and the vibration frequency generated by the drainage valve to be detected during the drainage process. Exemplarily, the vibration data can be collected by a vibration sensor installed on the outer wall of the valve of the drainage valve to be detected.

[0029] In the embodiments of the present application, the acoustic data is the sound intensity and the sound frequency generated by the valve of the drainage valve to be detected due to the impact of water flow during the drainage process. Exemplarily, the acoustic data can be collected by an acoustic sensor installed on the outer wall of the valve of the drainage valve to be detected.

[0030] In the embodiments of the present application, the pressure data is the pressure received by the inner side of the valve of the drainage valve to be detected during the drainage process. Exemplarily, the pressure data can be collected by a pressure sensor installed on the inner side of the valve.

[0031] In the embodiments of the present application, the liquid level data is used to represent the liquid surface height of the water accumulated in the system to which the drainage valve to be detected belongs. Exemplarily, the liquid level data can be monitored and obtained in real time by a liquid level sensor provided in the drainage valve to be detected.

[0032] In the embodiments of the present application, the collection frequency of each sensor is set based on the actual scene requirement. For example, in a specific implementation, the frequency of data collection of each sensor is specified as 10 Hz.

[0033] In the embodiments of the present application, after the real-time working data of the drainage valve to be detected is collected, the obtained real-time working data is standardized to realize the dimension unification of the data, and the real-time working data is temporarily stored in a temporary storage area designated by the system. The longest storage duration of the temporary storage area can be set based on the actual scene requirement, for example, in the specific implementation, the longest storage duration of the temporary storage area can be set as 10 minutes. When the valve of the drainage valve to be detected is opened, all the data in the temporary storage area is transferred to a real-time storage area designated by the system, and the subsequently collected working data is also stored in the real-time storage area until the valve of the drainage valve to be detected is closed. After the valve of the drainage valve to be detected is closed, the working data collected in real time thereafter is stored in the temporary storage area.

[0034] The embodiment of the application realizes the timing management of data acquisition through the dynamic storage mechanism of the above-mentioned sub-regions, which can ensure the complete recording of full working cycle data before and after the opening of the valve, avoid long-term occupation of storage space by invalid data through the temporary storage mechanism, and realize data partition storage with the valve opening and closing state as the trigger point, facilitating the accurate extraction and analysis of subsequent drainage process data, and improving the efficiency and pertinence of data management.

[0035] In addition, for the data in the above-mentioned real-time storage region, the embodiment of the application can also take the time from the single valve opening to closing of the to-be-detected drainage valve as a time window, pre-process the obtained real-time working data, and integrate the pre-processed data into a data set to obtain a working data set corresponding to the drainage event.

[0036] In step S120, the flow peak value change trend and the drainage efficiency decay degree are determined based on the flow data recorded in the continuous multiple drainages, and the impurity deposition index is generated based on the flow peak value change trend and the drainage efficiency decay degree.

[0037] In the embodiment of the application, the above-mentioned flow peak value change trend reflects the change trend of the flow peak value with the number of drainages. Specifically, taking the ith drainage as an example, the flow peak value of the ith drainage is the maximum value of the flow data collected by the flow sensor during the ith drainage.

[0038] During the working process of the to-be-detected drainage valve, impurities in the liquid deposit on the valve wall or filter screen, reducing the valve passage area of the to-be-detected drainage valve. According to the principle of fluid mechanics, if the area of the valve passage of the to-be-detected drainage valve decreases, the flow rate of the water flow through the to-be-detected drainage valve will decrease in the same drainage time. Therefore, the change trend of the flow peak value can be used to measure the valve impurity deposition degree of the to-be-detected drainage valve. Specifically, when the drainage is continuously performed, if there is impurity deposition in the valve of the to-be-detected drainage valve, the flow peak value of each drainage will gradually decrease with the increase of the number of drainages.

[0039] Exemplarily, the above-mentioned flow peak value change trend can be determined by the following method: obtaining the flow peak value in the flow data recorded in the continuous multiple drainages, taking the number of drainages as the independent variable and the flow peak value corresponding to the number of drainages as the dependent variable, and constructing a flow peak value change curve. Specifically, the flow peak value change curve can be as shown in Figure 2 The flow peak value change curve is linearly fitted, and the slope of the fitted straight line is determined, denoted as the flow peak value change trend.

[0040] In the embodiments of the present application, the above-mentioned drainage efficiency attenuation degree is a quantitative index of the degree of decrease in drainage efficiency of the to-be-detected drainage valve caused by impurity deposition; wherein the drainage efficiency is a quantitative index of the drainage amount of the to-be-detected drainage valve per unit time, which can reflect the drainage capacity of the to-be-detected drainage valve. When the valve passage of the to-be-detected drainage valve is reduced in cross-sectional area due to impurity deposition, the total drainage amount in the same drainage time is reduced, and the drainage efficiency is also reduced, so the degree of impurity deposition of the to-be-detected drainage valve can be measured by the attenuation degree of the drainage efficiency at different drainage times in time sequence.

[0041] Exemplarily, the above-mentioned drainage efficiency attenuation degree can be realized by the following manner: obtaining the initial drainage amount and the initial drainage time of the to-be-detected drainage valve at the first time of drainage after the last maintenance, and calculating the ratio of the initial drainage amount and the initial drainage time, denoted as the initial drainage efficiency; obtaining the current drainage amount and the current drainage time of the to-be-detected drainage valve at the current time of drainage after the last maintenance, and calculating the ratio of the current drainage amount and the current drainage time, denoted as the current drainage efficiency; determining the effective drainage time based on the flow data in the current drainage process; determining the drainage efficiency attenuation degree based on the initial drainage efficiency, the current drainage efficiency and the effective drainage time.

[0042] Specifically, taking the i-th drainage after the last maintenance of the to-be-detected drainage valve as an example, the drainage efficiency of the i-th drainage can be calculated by the following formula: wherein, is the drainage efficiency of the i-th drainage; is the drainage amount of the i-th drainage; is the drainage time of the i-th drainage.

[0043] In the embodiments of the present application, the above-mentioned effective drainage time is the sum of the time periods in which the to-be-detected drainage valve is in a high-flow state during the removal process, wherein the above-mentioned high-flow state refers to a drainage state in which the real-time flow of the to-be-detected drainage valve is not less than a flow threshold value, and the above-mentioned flow threshold value can be determined based on the maximum flow designed for the system to which the to-be-detected drainage valve belongs.

[0044] Exemplarily, the above-mentioned determination of the effective drainage time based on the flow data in the current drainage process can be realized by the following method: obtaining the system design maximum flow of the to-be-detected drainage valve, calculating the product of the system design maximum flow and a preset proportion to obtain a flow threshold value; obtaining target flow data not less than the flow threshold value in the current drainage process, determining the sum of the drainage times corresponding to the target flow data, denoted as the effective drainage time.

[0045] Specifically, taking the i-th drainage after the last maintenance of the to-be-detected drainage valve as an example, assuming that the maximum flow designed for the system to which the to-be-detected drainage valve belongs is , preset ratio is 0.8, real-time flow at t time is , if , mark the time as high-efficiency working time; count all high-efficiency working times in the i-th drainage process, and record the sum of all high-efficiency working times as effective drainage time of the i-th drainage .

[0046] In the embodiment of the present application, the initial drainage efficiency can also be determined based on the initial drainage amount and the initial drainage duration corresponding to the first drainage since the last maintenance of the drainage valve to be detected according to the formula for calculating the drainage efficiency of the i-th drainage. Taking the i-th drainage since the last maintenance of the drainage valve to be detected as an example, the drainage efficiency attenuation degree of the i-th drainage since the last maintenance of the drainage valve to be detected can be calculated by the following formula: , wherein is the drainage efficiency attenuation degree of the i-th drainage; is the initial drainage efficiency of the first drainage; is the drainage efficiency of the i-th drainage; is the effective drainage time of the i-th drainage; it can be obtained from the above formula that: if the drainage efficiency of the i-th drainage decreases greatly compared with the initial drainage efficiency, and the effective drainage time of the i-th drainage is long, it can be determined that the decrease of the drainage efficiency is less likely caused by impurity accumulation, and the judgment combined with the effective drainage time can avoid misjudgment of the impurity accumulation degree of the drainage valve to be detected.

[0047] In the embodiment of the present application, the impurity deposition index is an index for measuring the impurity deposition degree of the drainage valve to be detected. The impurity deposition index can be determined by the following method: calculating the product of the absolute value of the flow peak value change trend and the drainage efficiency attenuation degree, and generating the impurity deposition index.

[0048] Specifically, taking the i-th drainage since the last maintenance of the drainage valve to be detected as an example, the impurity deposition index can be calculated by the following formula: , wherein is the impurity deposition index of the i-th drainage; is the flow peak value change trend of continuous multiple drainages; is the drainage efficiency attenuation degree of the i-th drainage; is a normalization function, and the linear normalization function is selected in the embodiment of the present application, and other normalization functions can also be selected in other embodiments of the present application, which will not be described and limited here.

[0049] In step S130, the impurity peeling indicator is generated based on the instantaneous change rate of the flow rate data and the change amount of the corresponding flow data, and the first impurity deposition degree is determined based on the impurity deposition indicator and the impurity peeling indicator.

[0050] In the embodiments of the present application, the instantaneous change rate of the flow rate data is the change rate of the flow rate data collected at adjacent sampling time points, which can be used to measure the degree of impurity peeling at the initial stage of opening of the to-be-detected drain valve.

[0051] The embodiments of the present application can determine the flow rate turning point based on the instantaneous change rate of the flow rate data. Before the flow rate turning point, the flow rate data increases due to the decrease of the cross-sectional area of the to-be-detected drain valve, and along with the water flow washing away the loose deposits on the outermost side of the impurity layer, after reaching the flow rate turning point, the cross-sectional area of the to-be-detected drain valve increases, and the flow rate data gradually decreases. By analyzing the flow rate change at the initial stage of opening of the to-be-detected drain valve, the amount of impurities peeled off can be judged according to the decrease amplitude of the flow rate.

[0052] Exemplarily, the instantaneous change rate of the flow rate data can be determined by the following method: for each sampling time point in the current drainage, the flow rate data at the current sampling time point and the previous sampling time point is obtained; the ratio of the difference between the flow rate data at the current sampling time point and the previous sampling time point to the sampling interval is determined, denoted as the instantaneous change rate of the flow rate data at the current sampling time point.

[0053] Taking the t-th time point in the i-th drainage process after the last maintenance of the to-be-detected drain valve as an example, the instantaneous change rate of the flow rate data at the t-th time point can be calculated by the following formula: Wherein, is the instantaneous change rate of the flow rate data at the t-th time point in the i-th drainage process; is the flow rate data at the t-th time point in the i-th drainage process; is the flow rate data at the t-th time point in the i-th drainage process; is the flow rate data at the t-th time point in the i-th drainage process; is the sampling interval between adjacent sampling time points.

[0054] In the embodiments of the present application, after determining the instantaneous change rate of the flow rate data corresponding to each sampling time point by the above method, further, the flow rate turning point can be determined based on the instantaneous change rate of the flow rate data.

[0055] Specifically, taking the i-th drainage after the last maintenance of the to-be-detected drain valve as an example, if and , the t-th time point in the i-th drainage process is defined as the flow rate turning point; wherein, a first change amount of flow rate data at the flow rate turning point, and a second change amount of flow rate data at the flow rate turning point. a first change amount of flow rate data at the flow rate turning point, and a second change amount of flow rate data at the flow rate turning point.

[0056] In the embodiments of the present application, the impurity stripping index is used to quantify the degree of dispersion of the loose impurities by water flow at the initial stage of opening of the drainage valve to be detected.

[0057] Exemplarily, the impurity stripping index can be determined by the following method: determining the difference between the instantaneous change rates of the flow rate data at the current sampling time and the previous sampling time corresponding to the flow rate turning point, denoted as a first change amount; determining the difference between the flow rate data at the current sampling time and the previous sampling time corresponding to the flow rate turning point, denoted as a second change amount; and determining the product of the first change amount and the second change amount to obtain the impurity stripping index.

[0058] Specifically, taking the t-th time point in the i-th drainage process after the last maintenance of the drainage valve to be detected as the flow rate turning point, the impurity stripping index can be calculated by the following method: wherein, is the impurity stripping index at the flow rate turning point; is the flow rate data at the t-th time point in the i-th drainage process, is the flow rate data at the t-1-th time point in the i-th drainage process, is the second change amount; is the instantaneous change rate of flow rate data at the t-1-th time point in the i-th drainage process, is the instantaneous change rate of flow rate data at the t-th time point in the i-th drainage process, is the first change amount; is a normalization function, and the value range is [0, 1].

[0059] In the embodiments of the present application, the first impurity deposition degree is used to quantify the degree of blockage of the drainage valve to be detected caused by impurity deposition. Exemplarily, the determination of the first impurity deposition degree based on the impurity deposition index and the impurity stripping index can be realized by the following method: determining the product of the impurity deposition index and the impurity stripping index to obtain the first impurity deposition degree.

[0060] Specifically, taking the i-th drainage after the last maintenance of the drainage valve to be detected as an example, the first impurity deposition degree can be calculated by the following formula: wherein, is the first impurity deposition degree of the i-th drainage. is the impurity deposition index of the i th drainage; is the impurity peeling index at the flow rate turning point in the i th drainage process; is a normalization function, and in the embodiments of the present application, a linear normalization function is selected as the normalization function, and in other embodiments of the present application, other normalization functions can also be selected, which will not be described and limited herein.

[0061] In step S140, the vibration anomaly factor and the acoustic anomaly factor are determined based on the vibration data and the acoustic data, and the impurity anomaly score of the to-be-detected drainage valve is determined based on the vibration anomaly factor, the acoustic anomaly factor and the first impurity deposition degree.

[0062] In the embodiments of the present application, the vibration anomaly factor is used to quantify the abnormal degree of mechanical vibration in the working process of the to-be-detected drainage valve.

[0063] For example, the vibration anomaly factor can be realized by the following method: for each sampling time in the current drainage, the actual vibration amplitude and the actual vibration frequency collected by the vibration sensor are obtained; the set upper limit of the vibration amplitude and the set upper limit of the vibration frequency of the to-be-detected drainage valve are obtained, the vibration amplitude difference between the actual vibration amplitude and the set upper limit of the vibration amplitude, and the vibration frequency difference between the actual vibration frequency and the set upper limit of the vibration frequency are calculated; the product of the vibration amplitude difference and the vibration frequency difference is determined, and is recorded as the vibration anomaly factor.

[0064] Specifically, taking the i th drainage process after the last maintenance of the to-be-detected drainage valve as an example, the vibration anomaly factor at the t th time can be calculated by the following formula: , wherein, is the vibration anomaly factor at the t th time in the i th drainage process; is the vibration amplitude collected by the vibration sensor at the t th time in the i th drainage process; is the upper limit of the normal vibration amplitude when the to-be-detected drainage valve is working (i.e., the set upper limit of the vibration amplitude); is the vibration frequency collected by the vibration sensor at the t th time in the i th drainage process; is the upper limit of the normal vibration frequency when the to-be-detected drainage valve is working (i.e., the set upper limit of the vibration frequency); is a normalization function, and in the embodiments of the present application, a linear normalization function is selected as the normalization function, and in other embodiments of the present application, other normalization functions can also be selected, which will not be described and limited herein.

[0065] In the embodiments of the present application, the acoustic anomaly factor is used to quantify the abnormal degree of noise in the working process of the to-be-detected drainage valve.

[0066] Exemplarily, the acoustic anomaly factor can be determined by the following method: for each sampling time in the current drainage, the actual noise intensity and the actual noise frequency collected by the acoustic sensor are obtained; the set upper limit of the noise intensity and the set upper limit of the noise frequency of the drainage valve to be detected are obtained, the noise intensity difference between the actual noise intensity and the set upper limit of the noise intensity, and the noise frequency difference between the actual noise frequency and the set upper limit of the noise frequency are calculated; the product of the noise intensity difference and the noise frequency difference is determined, denoted as the acoustic anomaly factor.

[0067] Specifically, taking the t time in the i drainage process after the last maintenance of the drainage valve to be detected as an example, the acoustic anomaly factor at this time can be calculated by the following formula: Wherein, is the acoustic anomaly factor at the t time in the i drainage process; is the noise intensity collected by the acoustic sensor at the t time in the i drainage process; is the upper limit of the normal noise intensity when the drainage valve to be detected works (i.e. the set upper limit of the noise intensity described above); is the noise frequency collected by the acoustic sensor at the t time in the i drainage process; is the upper limit of the normal noise frequency when the drainage valve to be detected works (i.e. the set upper limit of the noise frequency described above); is a normalization function, and the linear normalization function is selected in the embodiment of the present application, and other normalization functions can also be selected in other embodiments of the present application, which will not be described and limited here.

[0068] It should be noted that in the process of calculating the vibration anomaly factor or the acoustic anomaly factor, if the real-time value of the vibration data or the acoustic data collected by the vibration sensor or the acoustic sensor does not exceed the corresponding set upper limit value, the difference between the real-time value of the corresponding vibration data or acoustic data and the set value is marked as 1. Taking the vibration amplitude collected by the vibration sensor at the t time in the i drainage process as an example, If , then .

[0069] In the embodiment of the present application, the impurity anomaly score is an index for comprehensively evaluating the abnormal degree of the working state of the drainage valve to be detected.

[0070] Exemplarily, the determination of the impurity anomaly score of the to-be-detected drain valve based on the vibration anomaly factor, the acoustic anomaly factor, and the first impurity deposition degree can be implemented as follows: determining the average value of the vibration anomaly factor at each sampling time in the current drainage process, denoted as the vibration anomaly score of the current drainage; determining the average value of the acoustic anomaly factor at each sampling time in the current drainage process, denoted as the acoustic anomaly score of the current drainage; determining an anomaly correlation factor of the vibration anomaly score and the acoustic anomaly score; determining the second impurity deposition degree based on the anomaly correlation factor, the vibration anomaly score, and the acoustic anomaly score; determining the confidence of the first impurity deposition degree based on the first impurity deposition degree and the second impurity deposition degree, and recording the product of the first impurity deposition degree and the confidence as the impurity anomaly score.

[0071] Specifically, taking the i th drainage after the last maintenance of the to-be-detected drain valve as an example, after the vibration anomaly factor and the acoustic anomaly factor at each sampling time in the i th drainage are calculated by the above process, the average value of the vibration anomaly factor at each sampling time can be calculated to obtain the vibration anomaly score of the i th drainage , and the average value of the acoustic anomaly factor at each sampling time can be calculated to obtain the acoustic anomaly score of the i th drainage ; wherein the vibration anomaly score is used to measure the vibration anomaly degree of the to-be-detected drain valve in the i th drainage; and the acoustic anomaly score is used to measure the noise anomaly degree of the to-be-detected drain valve in the i th drainage.

[0072] In the embodiments of the present application, the anomaly correlation factor is a parameter used to measure the anomaly correlation degree of the vibration anomaly factor and the acoustic anomaly factor. The higher the value of the anomaly correlation factor, the higher the possibility that the vibration data and the acoustic data appear abnormal at the same time, for example, impurity deposition reduces the cross-sectional area of the valve, and the change in liquid flow rate will simultaneously cause the vibration to intensify and the noise to be abnormal.

[0073] Exemplarily, the process of determining the anomaly correlation factor based on the vibration anomaly score and the acoustic anomaly score can be implemented by the following method: determining the product of the vibration anomaly score and the acoustic anomaly score, denoted as the sensor anomaly score product; determining the absolute value of the difference between the vibration anomaly score and the acoustic anomaly score, denoted as the sensor anomaly score difference absolute value; and determining the anomaly correlation factor of the vibration anomaly score and the acoustic anomaly score based on the sensor anomaly score product and the sensor anomaly score difference absolute value.

[0074] Specifically, taking the i th drainage after the last maintenance of the to-be-detected drain valve as an example, the anomaly correlation factor can be calculated by the following formula: wherein, is an abnormal correlation factor of the i-th drainage; is a vibration abnormality score of the i-th drainage; is an acoustic abnormality score of the i-th drainage.

[0075] In the embodiments of the present application, the second impurity deposition degree is the impurity deposition degree of the valve to be detected determined based on the abnormal data of the vibration sensor and the acoustic sensor. By comparing the consistency of the second impurity deposition degree and the first impurity deposition degree, the confidence of the first impurity deposition degree can be determined. Specifically, the higher the consistency of the second impurity deposition degree and the first impurity deposition degree, the higher the confidence of the first impurity deposition degree.

[0076] Specifically, taking the i-th drainage after the last maintenance of the drainage valve to be detected as an example, the confidence of the first impurity deposition degree can be calculated by the following formula: wherein, is the confidence of the first impurity deposition degree in the i-th drainage; is the first impurity deposition degree in the i-th drainage; is a vibration abnormality score of the i-th drainage; is an acoustic abnormality score of the i-th drainage; is an abnormal correlation factor of the vibration abnormality score and the acoustic abnormality score in the i-th drainage; is used to represent the consistency of the first impurity deposition degree and the second impurity deposition degree; is a normalization function. In the embodiments of the present application, the linear normalization function is selected as the normalization function. In other embodiments of the present application, other normalization functions can also be selected, which are not described and limited herein.

[0077] In the embodiments of the present application, after determining the confidence of the first impurity deposition degree, the impurity abnormality score can be determined by calculating the product of the first impurity deposition degree and the confidence.

[0078] Specifically, taking the i-th drainage after the last maintenance of the drainage valve to be detected as an example, the impurity abnormality score can be calculated by the following formula: wherein, is the impurity abnormality score of the i-th drainage; is the confidence of the first impurity deposition degree in the i-th drainage; is the first impurity deposition degree of the i-th drainage.

[0079] In step S150, the working intensity is determined based on the vibration data, the pressure data and the liquid level data, the drainage frequency of the to-be-detected drainage valve since the last maintenance is obtained, and the fault probability is determined based on the working intensity, the drainage frequency and the impurity abnormality score.

[0080] In the embodiments of the present application, the working intensity is used to quantify the working pressure related to impurity deposition that the to-be-detected drainage valve bears in the drainage process. Specifically, the more the total amount of liquid that needs to be drained by the system, the longer the effective drainage time of the to-be-detected drainage valve in the drainage process, and the higher the working intensity of the to-be-detected drainage valve; the larger the total amount of impurities in the liquid, the higher the working intensity of the to-be-detected drainage valve, because the impurity deposition will reduce the cross-sectional area of the valve passage, so that the water flow resistance increases when the liquid passes through the to-be-detected valve, and the to-be-detected valve needs to provide a larger pressure difference to push the liquid flow.

[0081] For example, the determination of the working intensity based on the vibration data, the pressure data and the liquid level data can be realized by the following method: for the current drainage, the first pressure data collected by the pressure sensor before the current drainage and the second pressure data collected by the pressure sensor after the current drainage are obtained, and the difference between the first pressure data and the second pressure data is calculated, which is denoted as the pressure difference before and after drainage; the average vibration amplitude obtained by the vibration sensor during the current drainage is obtained, and the equipment running intensity is determined based on the average vibration amplitude and the pressure difference before and after drainage; the maximum liquid level data of the water storage device in the system to which the to-be-detected drainage valve belongs and the current liquid level data collected by the liquid level sensor are obtained, and the theoretical drainage amount is determined based on the maximum liquid level data, the current liquid level data and the volume of the water storage device; the actual drainage amount of the current drainage is obtained, and the difference between the actual drainage amount and the theoretical drainage amount is denoted as the impurity residual value; and the working intensity is determined based on the effective drainage time, the equipment running intensity and the impurity residual value.

[0082] In the embodiments of the present application, the equipment running intensity is an index for reflecting the running load of the to-be-detected drainage valve in the drainage process due to pressure changes and vibrations.

[0083] Specifically, taking the current drainage as the i-th drainage since the last maintenance of the to-be-detected drainage valve as an example, the equipment running intensity can be calculated by the following formula: wherein, is the equipment running intensity of the to-be-detected drainage valve in the i-th drainage; is the difference between the pressure data collected by the pressure sensor before and after the i-th drainage (i.e., the pressure difference before and after the above drainage); is the average value of the vibration amplitude collected by the vibration sensor during the i-th drainage; As the normalization function, a linear normalization function is selected in the embodiment of the present application, and other normalization functions can also be selected in other embodiments of the present application, which will not be described and limited herein.

[0084] In the embodiment of the present application, the maximum liquid level data is the maximum value of the liquid level data of the water storage device arranged in the system to which the drainage valve belongs (the liquid to be drained in the system is drained through the drainage valve to be detected), and exemplarily, the maximum liquid level data can be the height of the water storage device.

[0085] In the embodiment of the present application, the theoretical drainage volume is the volume of the liquid to be drained corresponding to the drainage process determined according to the liquid level of the water storage device. Exemplarily, the volume can be determined by the proportion of the current liquid level data collected by the liquid level sensor in the maximum liquid level data and the volume of the water storage device, wherein the current liquid level data refers to the height of the liquid to be drained in the current drainage in the water storage device.

[0086] In the embodiment of the present application, the actual drainage volume is the volume of the liquid to be drained actually drained corresponding to the drainage process. Exemplarily, the actual drainage volume can be obtained by integrating or accumulating the drainage flow data collected by the flow sensor.

[0087] In the embodiment of the present application, the impurity residual value is an index for reflecting the impurity content in water and the valve deposition risk in the drainage process. Exemplarily, the impurity residual value can be determined by the difference between the actual drainage volume and the theoretical drainage volume in the corresponding drainage process.

[0088] Specifically, taking the i th drainage after the last maintenance of the drainage valve to be detected as an example, the impurity residual value can be calculated by the following formula: wherein, is the impurity residual value in the i th drainage process; is the actual drainage volume of the i th drainage; is the volume of the water storage device; is the liquid level data of the i th drainage collected by the liquid level sensor; is the height of the water storage device; is the theoretical drainage volume of the i th drainage; is a normalization function, and a linear normalization function is selected in the embodiment of the present application, and other normalization functions can also be selected in other embodiments of the present application, which will not be described and limited herein.

[0089] In the embodiment of the present application, the equipment operation intensity of the drainage valve to be detected in the i th drainage process is determined by the above process and the impurity residual value Further, the working strength of the valve to be detected in the i th drainage process can be calculated by the following formula: wherein, is the working strength of the valve to be detected in the i th drainage process; is the effective drainage time in the i th drainage process; is the impurity residual value in the i th drainage process; is the equipment running strength of the drainage valve to be detected in the i th drainage process.

[0090] In the embodiments of the present application, the above failure probability is used to quantify the possibility of the valve to be detected to appear the blockage failure in the drainage process. Exemplarily, the failure probability can be determined based on the working strength, the drainage frequency of the drainage valve to be detected since the last maintenance, and the impurity abnormality score. Wherein, the drainage frequency of the drainage valve to be detected since the last maintenance can be determined by the ratio of the number of drainages of the drainage valve to be detected since the last maintenance to the time interval from the last maintenance to the current time.

[0091] Specifically, taking the i th drainage since the last maintenance of the drainage valve to be detected as an example, the above failure probability can be calculated by the following formula: wherein, is the failure probability of the drainage valve to be detected in the i th drainage process; is the drainage frequency of the drainage valve to be detected from the last maintenance to the i th drainage; is the working strength of the valve to be detected in the i th drainage process; is the impurity abnormality score in the i th drainage; is a normalization function, and in the embodiments of the present application, a linear normalization function is selected. In other embodiments of the present application, other normalization functions can also be selected, which will not be described and limited herein.

[0092] In step S160, the failure condition of the drainage valve to be detected is predicted based on the failure probability.

[0093] In the embodiments of the present application, after the failure probability of the current drainage is determined through the above process, the probability of the drainage valve to be detected to appear the blockage failure in the next drainage process can be predicted based on the failure probability, so that timely processing measures can be taken to avoid the lag of manual maintenance.

[0094] For example, the above-mentioned prediction of the failure status of the drain valve under test based on the failure probability can be achieved as follows: acquiring the liquid level data collected by the liquid level sensor before the next drainage; predicting the increase in the failure probability of the next drainage relative to the current drainage based on the liquid level data before the next drainage and the failure probability of the current drainage; determining the failure probability of the next drainage based on the failure probability of the current drainage and the increase in the failure probability; if the failure probability of the next drainage is greater than a preset threshold, sending a stop operation command to the drain valve under test and performing maintenance on the drain valve under test.

[0095] Specifically, artificial intelligence algorithms (such as convolutional neural networks) can be used to predict the increase in the failure probability based on the failure probability of the current drainage and the liquid level data before the next drainage of the valve under test. The sum of the failure probability of the current drainage and the predicted increase in the failure probability is then recorded as the predicted failure probability value for the next drainage. Taking the current drainage as the i-th drainage since the last maintenance of the valve under test as an example, if the predicted failure probability of the next drainage... (The preset threshold is set to 0.6 here.) If it is believed that the continued operation of the drain valve under test will cause equipment damage, a stop operation command is sent to control the equipment or system to stop running and to perform maintenance on the drain valve under test. It should be noted that if the failure probability of the current drainage is greater than the preset threshold, a stop operation command should also be sent to the drain valve under test.

[0096] The foregoing primarily describes the solutions provided by the embodiments of the present invention from a methodological perspective. To achieve the aforementioned functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, the present invention can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0097] Correspondingly, embodiments of this disclosure also provide a detection system for an automatic drain valve, referencing... Figure 3 As shown, the detection system 300 for the automatic drain valve may include a data acquisition module 310, a data processing module 320, and a fault detection module 330, wherein: The data acquisition module is used to collect the working data of the drain valve under test. The working data includes flow rate data, flow velocity data, vibration data, acoustic data, pressure data, and liquid level data. The data processing module is configured to determine a flow peak value change trend and a drainage efficiency attenuation degree based on flow data recorded in continuous multiple times of drainage, and generate an impurity deposition index based on the flow peak value change trend and the drainage efficiency attenuation degree. The data processing module is further configured to generate an impurity stripping index based on an instantaneous change rate of the flow rate data and a change amount of the corresponding flow data, and determine a first impurity deposition degree based on the impurity deposition index and the impurity stripping index. The data processing module is further configured to determine a vibration abnormal factor and an acoustic abnormal factor based on the vibration data and the acoustic data, and determine an impurity abnormal score of the to-be-detected drainage valve based on the vibration abnormal factor, the acoustic abnormal factor, and the first impurity deposition degree. The data processing module is further configured to determine a working intensity based on the vibration data, the pressure data, and the liquid level data, obtain a drainage frequency of the to-be-detected drainage valve since the last maintenance, and determine a failure probability based on the working intensity, the drainage frequency, and the impurity abnormal score. The failure detection module is configured to predict a failure condition of the to-be-detected drainage valve based on the failure probability.

[0098] The specific implementation details of the above-described detection system of the automatic drainage valve have been described in detail in the corresponding positions of the detection method of the automatic drainage valve, and thus will not be described here again.

[0099] The above description is merely preferred embodiments of the present disclosure and a description of the principles of the applied technology. Those skilled in the art should understand that the disclosed range of the present disclosure is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or equivalent features without departing from the above disclosed concept. For example, the above-described features are replaced with each other to form technical solutions with similar functions disclosed in the present disclosure (but not limited to).

[0100] In addition, although each operation is described in a specific order, this should not be understood as requiring the operations to be performed in the specific order shown or in a sequential order. In certain circumstances, multitasking and parallel processing can be advantageous. Similarly, although several implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Certain features described in the context of separate embodiments can also be combined in a single embodiment. Conversely, various features described in the context of a single embodiment can also be separated and implemented in multiple embodiments.

Claims

1. A method for detecting an automatic drain valve, characterized in that, The method includes: Collect the operating data of the drain valve to be tested, including flow rate data, flow velocity data, vibration data, acoustic data, pressure data, and liquid level data; Based on the flow data from multiple consecutive drainage records, the peak flow rate variation trend and the degree of drainage efficiency decay are determined, and an impurity deposition index is generated based on the peak flow rate variation trend and the degree of drainage efficiency decay. An impurity stripping index is generated based on the instantaneous rate of change of the flow velocity data and the corresponding change in the flow rate data, and the degree of first impurity deposition is determined based on the impurity deposition index and the impurity stripping index. Based on the vibration data and the acoustic data, a vibration anomaly factor and an acoustic anomaly factor are determined, and based on the vibration anomaly factor, the acoustic anomaly factor, and the first impurity deposition degree, the impurity anomaly score of the drain valve to be tested is determined. The working intensity is determined based on the vibration data, the pressure data, and the liquid level data. The drainage frequency of the drain valve to be tested since the last maintenance is obtained. The failure probability is determined based on the working intensity, the drainage frequency, and the impurity anomaly score. The failure status of the drain valve to be tested is predicted based on the failure probability.

2. The detection method for the automatic drain valve according to claim 1, characterized in that, The process of determining the peak flow rate variation trend and the degree of drainage efficiency decay based on the flow rate data from multiple consecutive drainage records, and generating an impurity deposition index based on the peak flow rate variation trend and the degree of drainage efficiency decay, includes: Obtain the peak flow rate from the flow rate data of multiple consecutive drainage records, and construct a flow rate peak change curve with the number of drainages as the independent variable and the peak flow rate corresponding to the number of drainages as the dependent variable. The flow peak change curve is fitted with a straight line, and the slope of the fitted straight line is determined and denoted as the flow peak change trend. The initial drainage volume and duration of the first drainage of the drain valve under test since the last maintenance are obtained, and the initial drainage efficiency is determined based on the initial drainage volume and the initial drainage duration. Obtain the current drainage volume and current drainage duration of the drain valve under test since the last maintenance, and determine the current drainage efficiency based on the current drainage volume and current drainage duration. The effective drainage time is determined based on the flow data during the current drainage process; The degree of drainage efficiency decay is determined based on the initial drainage efficiency, the current drainage efficiency, and the effective drainage time. The impurity deposition index is generated by multiplying the absolute value of the peak flow rate change trend with the degree of drainage efficiency decline.

3. The detection method for the automatic drain valve according to claim 2, characterized in that, Determining the effective drainage time based on the flow data during the current drainage process includes: Obtain the system design maximum flow rate of the drain valve to be tested, calculate the product of the system design maximum flow rate and a preset ratio, and obtain the flow rate threshold. Obtain the target flow rate data that is not less than the flow rate threshold during the current drainage process, determine the sum of the drainage times corresponding to the target flow rate data, and record it as the effective drainage time.

4. The detection method for the automatic drain valve according to claim 1, characterized in that, The process of generating an impurity stripping index based on the instantaneous change rate of the flow velocity data and the corresponding change in the flow rate data, and determining the first impurity deposition degree based on the impurity deposition index and the impurity stripping index, includes: For each sampling time in the current drainage, acquire the flow rate data and the flow velocity data at the current sampling time and the previous sampling time; Based on the flow velocity data and sampling interval at the current sampling time and the previous sampling time, the instantaneous rate of change of the flow velocity data at the current sampling time is determined, and the flow velocity inflection point is determined based on the instantaneous rate of change of the flow velocity data. The difference between the instantaneous rate of change of the flow velocity data at the current sampling time and the previous sampling time corresponding to the flow velocity inflection point is determined and denoted as the first change amount; The difference between the flow rate data at the current sampling time and the previous sampling time corresponding to the flow rate inflection point is determined and denoted as the second change. The impurity stripping index is obtained by determining the product of the first change and the second change. The product of the impurity deposition index and the impurity stripping index is determined to obtain the first impurity deposition degree.

5. The detection method for the automatic drain valve according to claim 1, characterized in that, The vibration data refers to the valve vibration data collected by a vibration sensor installed on the outer wall of the drain valve under test during the drainage process; the acoustic data refers to the sound data emitted by the valve during the drainage process collected by an acoustic sensor installed on the outer wall of the drain valve under test; the determination of vibration anomaly factors and acoustic anomaly factors based on the vibration data and the acoustic data includes: For each sampling moment in the current drainage, the actual vibration amplitude and actual vibration frequency collected by the vibration sensor, and the actual noise intensity and actual noise frequency collected by the acoustic sensor are obtained; Obtain the upper limit of the set vibration amplitude and the upper limit of the set vibration frequency of the drain valve to be tested, and calculate the difference between the actual vibration amplitude and the upper limit of the set vibration amplitude, as well as the difference between the actual vibration frequency and the upper limit of the set vibration frequency. The product of the difference in vibration amplitude and the difference in vibration frequency is defined as the vibration anomaly factor. Obtain the upper limit of the set noise intensity and the upper limit of the set noise frequency of the drain valve to be tested, and calculate the difference between the actual noise intensity and the upper limit of the set noise intensity, as well as the difference between the actual noise frequency and the upper limit of the set noise frequency. The product of the difference in noise intensity and the difference in noise frequency is determined and denoted as the acoustic anomaly factor.

6. The detection method for the automatic drain valve according to claim 5, characterized in that, The determination of the impurity anomaly score of the drain valve to be tested based on the vibration anomaly factor, the acoustic anomaly factor, and the degree of the first impurity deposition includes: The mean value of the vibration anomaly factor at each sampling time during the current drainage process is determined and denoted as the vibration anomaly score of the current drainage. The mean value of the acoustic anomaly factor at each sampling time during the current drainage process is determined and denoted as the acoustic anomaly score of the current drainage. Determine the vibration anomaly score and the anomaly correlation factor of the acoustic anomaly score; The degree of second impurity deposition is determined based on the abnormal correlation factor, the vibration anomaly score, and the acoustic anomaly score. The confidence level of the first impurity deposition degree is determined based on the first impurity deposition degree and the second impurity deposition degree, and the product of the first impurity deposition degree and the confidence level is recorded as the impurity anomaly score.

7. The method for detecting an automatic drain valve according to claim 6, characterized in that, The abnormal correlation factors for determining the vibration anomaly score and the acoustic anomaly score include: The product of the vibration anomaly score and the acoustic anomaly score is determined and denoted as the sensor anomaly score product. The absolute value of the difference between the vibration anomaly score and the acoustic anomaly score is determined and denoted as the absolute value of the sensor anomaly score difference; The abnormal correlation factor of the vibration abnormality score and the acoustic abnormality score is determined based on the product of the abnormality scores of the sensors and the absolute value of the difference between the abnormality scores of the sensors.

8. The method for detecting an automatic drain valve according to claim 2, characterized in that, The vibration data is valve vibration data collected by a vibration sensor installed on the outer wall of the drain valve under test during the drainage process; the pressure data is pressure data inside the valve under test collected by a pressure sensor installed inside the drain valve under test during the drainage process; the liquid level data is the liquid level height of the water accumulated inside the system to which the drain valve under test belongs, collected by a liquid level sensor built into the inside of the drain valve under test; determining the working intensity based on the vibration data, the pressure data, and the liquid level data includes: For the current drainage, the pressure sensor acquires the first pressure data collected before the current drainage and the second pressure data collected after the current drainage, and calculates the difference between the first pressure data and the second pressure data, which is recorded as the pressure difference before and after drainage. The average vibration amplitude obtained by the vibration sensor during the current drainage process is acquired, and the operating intensity of the equipment is determined based on the average vibration amplitude and the pressure difference before and after drainage. The maximum liquid level data of the water storage device in the system to which the drain valve to be tested belongs and the current liquid level data collected by the liquid level sensor are obtained. The theoretical drainage volume is determined based on the maximum liquid level data, the current liquid level data and the volume of the water storage device. Obtain the actual drainage volume of the current drainage, and record the difference between the actual drainage volume and the theoretical drainage volume as the impurity residue value; The workload is determined based on the effective drainage time, the equipment operating intensity, and the residual impurity value.

9. The method for detecting an automatic drain valve according to claim 8, characterized in that, The method of predicting the failure status of the drain valve under test based on the failure probability includes: Obtain the liquid level data before the next drainage; Based on the liquid level data before the next drainage and the failure probability of the current drainage, the increase in the failure probability of the next drainage relative to the current drainage is predicted. The failure probability of the next drainage is determined based on the failure probability of the current drainage and the increase in the failure probability. If the probability of failure in the next drainage is greater than a preset threshold, a stop operation command is sent to the drain valve to be tested, and the drain valve to be tested is maintained.

10. A detection system for an automatic drain valve, characterized in that, The system includes: The data acquisition module is used to collect the working data of the drain valve to be tested. The working data includes flow rate data, flow velocity data, vibration data, acoustic data, pressure data, and liquid level data. The data processing module is used to determine the flow peak change trend and the degree of drainage efficiency decay based on the flow data from multiple consecutive drainage records, and to generate an impurity deposition index based on the flow peak change trend and the degree of drainage efficiency decay. The data processing module is further configured to generate an impurity stripping index based on the instantaneous change rate of the flow velocity data and the corresponding change in the flow rate data, and to determine the first impurity deposition degree based on the impurity deposition index and the impurity stripping index. The data processing module is further configured to determine vibration anomaly factor and acoustic anomaly factor based on the vibration data and the acoustic data, and to determine the impurity anomaly score of the drain valve to be tested based on the vibration anomaly factor, the acoustic anomaly factor and the first impurity deposition degree. The data processing module is also used to determine the working intensity based on the vibration data, the pressure data and the liquid level data, obtain the drainage frequency of the drain valve to be tested since the last maintenance, and determine the failure probability based on the working intensity, the drainage frequency and the impurity abnormality score. The fault detection module is used to predict the fault condition of the drain valve to be detected based on the fault probability.

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