Airtightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas

Abstract

The present application relates to container airtightness detection technical field, specifically to a kind of bottled liquefied petroleum gas's airtightness monitoring and intelligent pressure regulating device.The present application proposes a kind of bottled liquefied petroleum gas's airtightness monitoring and intelligent pressure regulating device.The present application is first by acquisition module historical data;Further in preliminary analysis module, according to the opening and closing state of valve, select monitoring inlet pressure and outlet pressure and outlet flow, or according to the correlation of inlet pressure and temperature data, determine whether to issue early warning;Further depth analysis module analyzes the possibility of leakage, and analyzes the difference of the change trend of inlet pressure, determines whether to issue early warning;Also by intelligent pressure regulating module, monitor outlet flow fluctuation to determine whether to adjust outlet pressure.By analyzing the correlation of pressure and temperature change, the continuity of the change trend of pressure, accurately monitor the airtightness of liquefied petroleum gas container, and monitor gas flow to adjust outlet pressure in time.

Description

Technical Field

[0001] The present invention relates to the technical field of container air tightness detection, and in particular to an air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas. Background Art

[0002] Bottled liquefied petroleum gas is flammable and explosive. Once a leak occurs, it will cause serious accidents such as fire and explosion. During use, it is necessary to ensure the stability of the pressure to avoid the risk of gas leakage or incomplete combustion.

[0003] Because liquefied petroleum gas (LPG) combustion experiences significant temperature fluctuations during use, maintaining a stable outlet pressure does not necessarily mean a stable LPG flow rate. Existing methods for monitoring whether the outlet pressure is within a normal fluctuation range are subject to errors. Severe fluctuations in LPG flow can lead to flameout or flashback during actual combustion. Furthermore, normal LPG consumption during use makes it difficult to monitor existing LPG leaks, leading to misjudgments of LPG leaks and inaccurate pressure regulation, which can easily lead to safety accidents. Regulating the pressure when airtightness issues exist can result in even more severe LPG leaks, causing serious safety accidents. Summary of the Invention

[0004] In order to solve the technical problem that the existing monitoring of the air tightness of bottled liquefied petroleum gas is inaccurate and leads to inaccurate pressure regulation, the purpose of the present invention is to provide an air tightness monitoring and intelligent pressure regulation device for bottled liquefied petroleum gas. The technical solution adopted is as follows:

[0005] A device for monitoring the air tightness and intelligent pressure regulation of bottled liquefied petroleum gas, comprising a pressure regulator, an air tightness monitoring system, and an intelligent pressure regulation module; the air tightness monitoring system comprises:

[0006] Acquisition module: acquiring the inlet and outlet pressure, temperature data and outlet flow of the pressure regulator in a preset historical neighborhood at the same acquisition frequency;

[0007] Preliminary analysis module: when the valve of the pressure regulator is closed, monitoring the inlet pressure and outlet pressure as well as the outlet flow rate to determine whether to issue an early warning; when the valve is open, determining whether to issue an early warning based on the correlation between the inlet pressure and the temperature data;

[0008] Deep Analysis Module: When the valve is open and no warning is issued, the preset historical neighborhood is divided into preset time periods; based on the change trend of the air inlet pressure in each preset time period and the characteristics of the sharp fluctuation of the air inlet pressure, the leakage possibility of each preset time period is obtained; based on the difference in the change trend of the air inlet pressure in the adjacent preset time periods, the difference is combined with all the leakage possibilities to determine whether to issue a warning;

[0009] The intelligent pressure regulating module is used to determine whether to adjust the outlet pressure according to the fluctuation of the outlet flow.

[0010] Furthermore, the method for obtaining the leakage possibility includes:

[0011] With temperature as the horizontal axis and pressure as the vertical axis, a straight line fitting is performed on the temperature data and the air inlet pressure in each preset time period to obtain a sub-segment fitting straight line; within each preset time period, the air inlet pressures above the sub-segment fitting straight line are classified into a first category, and the air inlet pressures below the sub-segment fitting straight line are classified into a second category, and the similar air inlet pressures adjacent in time sequence are classified into one segment to obtain similar pressure segments;

[0012] Obtaining the deviation trend strength of each preset period according to the longest data quantity of the same type of pressure segments within each preset period; the longest data quantity of the same type of pressure segments is positively correlated with the deviation trend strength;

[0013] Obtaining an abnormal fluctuation coefficient for each preset time period based on a difference in quantity between the two types of air inlet pressure data within each preset time period, in combination with a difference in discrete distribution between the two types of air inlet pressure data, and a discrete intensity of each type of air inlet pressure data; the difference in quantity and discrete distribution between the two types of air inlet pressure data, as well as the discrete intensity of each type of air inlet pressure data, are all positively correlated with the abnormal fluctuation coefficient;

[0014] The deviation trend strength and the abnormal fluctuation coefficient are integrated to obtain the leakage possibility of each preset time period; the deviation trend strength and the abnormal fluctuation coefficient are both positively correlated with the leakage possibility.

[0015] Furthermore, the method of determining whether to issue an early warning based on the difference in the change trend of the air inlet pressure in the adjacent preset time periods in time sequence and combining all the leakage possibilities includes:

[0016] The category of the longest pressure segment of the same type within each preset time period is used as the marker category;

[0017] With time as the horizontal axis and pressure as the vertical axis, a linear fit is performed on the inlet pressure in each of the preset time periods to obtain a pressure-time fitting line; and the product of a two-dimensional vector consisting of a slope and an intercept of the pressure-time fitting line and the leakage probability is used as a signature vector corresponding to the preset time period;

[0018] Obtaining a leakage risk coefficient based on the differences in the types of the marks and the differences in the mark vectors of the adjacent preset time periods in time sequence, combined with the overall characteristics of all the leakage possibilities; the differences in the types of the marks, the differences in the mark vectors, and the overall characteristics of all the leakage possibilities are positively correlated with the leakage risk coefficient;

[0019] Whether to issue an early warning is determined based on the leakage risk factor.

[0020] Furthermore, the method for determining whether to issue an early warning based on the leakage risk coefficient includes:

[0021] When the leakage risk coefficient is greater than a second preset threshold, it is determined that an early warning is issued.

[0022] Furthermore, the method for determining whether to issue a warning based on the correlation between the air inlet pressure and the temperature data includes:

[0023] With temperature as the horizontal axis and pressure as the vertical axis, a linear fit is performed on the temperature data of the preset historical neighborhood and the air inlet pressure to obtain a temperature-pressure fitting line; the probability of normal air tightness is obtained based on the slope and determination coefficient of the temperature-pressure fitting line; the slope and determination coefficient of the temperature-pressure fitting line are both positively correlated with the probability of normal air tightness;

[0024] Whether to issue an early warning is determined based on the likelihood that the air tightness is normal.

[0025] Furthermore, the method for determining whether to issue an early warning based on the possibility of normal air tightness includes:

[0026] When the probability of normal airtightness is less than a first preset threshold, it is determined that an early warning is issued.

[0027] Furthermore, the method of monitoring the air inlet pressure, the air outlet pressure and the air outlet flow to determine whether to issue an early warning includes:

[0028] When the valve of the pressure regulator is closed, if the air inlet pressure and the air outlet pressure remain unchanged, and the air outlet flow rate remains at 0, it is determined that no warning is issued, otherwise a warning is issued.

[0029] Furthermore, the method of determining whether to adjust the outlet pressure according to the fluctuation of the outlet flow rate includes:

[0030] A flow rate stability coefficient is obtained based on the difference in the air outlet flow rate between the first and last two preset time periods and the severity of the fluctuation of the air outlet flow rate between the first and last two preset time periods; the difference in the air outlet flow rate between the first and last two preset time periods and the severity of the fluctuation of the air outlet flow rate between the first and last two preset time periods are both negatively correlated with the flow rate stability coefficient;

[0031] Whether to perform pressure regulation is determined according to the flow stability coefficient.

[0032] Furthermore, the method for determining whether to perform pressure regulation according to the flow stability coefficient includes:

[0033] When the flow stability coefficient is less than a third preset threshold, it is determined that pressure regulation is performed.

[0034] Furthermore, the linear fitting adopts the least square method.

[0035] The present invention has the following beneficial effects:

[0036] The present invention first obtains historical data through the acquisition module to provide a basis for data analysis; further in the preliminary analysis module: when the valve of the pressure regulator is closed, the inlet pressure and outlet pressure as well as the outlet flow are monitored to determine whether an early warning is issued, and the air tightness of the container is monitored from a static perspective; when the valve is opened, the air tightness is preliminarily detected and determined by means of the correlation between the inlet pressure and temperature data caused by the combustion of petroleum gas; further in the in-depth analysis module: the preset historical neighborhood is divided into preset time periods to more carefully analyze the local fluctuation changes of the data; according to the inlet pressure in each preset time period, the air tightness is preliminarily detected and determined. The changing trend of the inlet pressure is combined with the characteristics of the dramatic fluctuations in the inlet pressure to obtain the possibility of leakage in each preset time period, characterizing the possibility of airtightness defects in each preset time period and providing a basis for subsequent judgment. The possibility of airtightness defects is further analyzed from the perspective of the change trend, and combined with the perspective of the possibility of leakage, a joint decision is made whether to issue an early warning, thereby more carefully monitoring the airtightness of the container. The intelligent pressure regulation module is also used to determine whether to adjust the outlet pressure based on the fluctuation of the outlet flow rate, and the pressure is adjusted in a timely manner to avoid ineffective pressure regulation caused by airtightness defects and more serious leakage accidents caused by pressure regulation during LPG leaks. By analyzing the correlation between pressure and temperature changes and the continuity of the pressure change trend, the present invention accurately monitors the airtightness of liquefied petroleum gas containers and monitors the gas flow to adjust the outlet pressure in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 A system block diagram of an air tightness monitoring system provided by one embodiment of the present invention;

[0039] Figure 2 The present invention provides a flowchart of a method for obtaining leakage possibility according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a device for monitoring and intelligently regulating the tightness of bottled liquefied petroleum gas. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0041] Unless defined otherwise, 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 belongs.

[0042] The specific scheme of the air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas provided by the present invention is described in detail below with reference to the accompanying drawings.

[0043] An embodiment of the present invention provides a device for monitoring the airtightness of bottled liquefied petroleum gas and for intelligently regulating pressure. The device includes a pressure regulator, wherein the pressure regulator's air inlet is connected to the liquefied petroleum gas cylinder, the air outlet is connected to the outside world, and the pressure regulator and the liquefied petroleum gas cylinder are tightly connected via an inlet connector; an airtightness monitoring system for monitoring the airtightness of the liquefied petroleum gas cylinder for defects; and an intelligent pressure regulating module for timely regulating the pressure. The structure and operating principle of the pressure regulator are well known to those skilled in the art and will not be further described here.

[0044] See also Figure 1 , which shows a system block diagram of an air tightness monitoring system provided by an embodiment of the present invention, specifically including: an acquisition module 101, a preliminary analysis module 102 and a deep analysis module 103.

[0045] Acquisition module 101: acquires the inlet and outlet pressure, temperature data and outlet flow of the pressure regulator in a preset historical neighborhood at the same acquisition frequency.

[0046] Pressure sensors are installed at the air inlet and outlet of the pressure regulator to obtain the air inlet and outlet pressures of the pressure regulator, and the air inlet pressure also represents the pressure inside the bottle; a flow sensor is installed at the outlet of the pressure regulator to monitor the gas flow and obtain the air outlet flow; a temperature sensor is installed on the outside of the bottle body near the air inlet of the pressure regulator to obtain temperature data, which represents the temperature data inside the bottle; in one embodiment of the present invention, various data are collected at a frequency of 10 seconds each time, and each Internet of Things sensor transmits the collected data to the air tightness monitoring system for real-time analysis. The preset time domain length of the historical neighborhood is 3 minutes, the same as the data collection frequency. Air tightness monitoring and intelligent pressure regulation are performed every 10 seconds, and the data of the last 3 minutes at the current moment are used as analysis objects to obtain analysis results.

[0047] Preliminary analysis module 102: When the valve of the pressure regulator is closed, the inlet pressure, outlet pressure and outlet flow are monitored to determine whether to issue an early warning; when the valve is open, the inlet pressure and temperature data are correlated to determine whether to issue an early warning.

[0048] When the valve of the pressure regulator is closed, the bottled liquefied petroleum gas is in an unused state. At this time, by directly monitoring the inlet pressure, outlet pressure and outlet flow, the air tightness of the bottled liquefied petroleum gas can be monitored intuitively, and it can be determined whether to issue an early warning and monitor from a static perspective.

[0049] Preferably, in one embodiment of the present invention, when the valve of the pressure regulator is closed, if the air tightness is good, no gas passes through the pressure regulator, and the pressures at the air inlet and the air outlet should remain unchanged. Therefore, if the air inlet pressure and the air outlet pressure remain unchanged, and the air outlet flow rate remains at 0, it is determined that no warning is issued, otherwise a warning is issued.

[0050] Among them, the valve is a component that controls the activation, deactivation, pressure and gas flow of bottled liquefied petroleum gas. It may be composed of multiple small components, such as valve seat, valve gasket, valve stem, spring, lever and other components. These components work together to play the role of a valve, so the word valve is used here to summarize it.

[0051] It should be noted that, taking into account the situation where the time interval from valve closing to opening is less than the preset historical neighborhood (3 minutes in one embodiment), and the valve has just been closed, when the time between the moment the valve is closed and the current moment is less than 3 minutes, only the historical data from the moment the valve is closed to the current moment is intercepted for analysis.

[0052] When the valve is opened, the bottled liquefied petroleum gas is in use. The heat released during the combustion of the gas will cause the temperature of the gas in the bottle to rise, resulting in changes in the pressure of the gas in the bottle and the pressure at the air inlet to change. There is a certain correlation between the pressure and temperature of the air inlet. Therefore, based on the correlation between the pressure and temperature data of the air inlet, it is analyzed whether the pressure and temperature of the gas in the bottle belong to normal related changes, so as to determine whether to issue an early warning.

[0053] Preferably, in one embodiment of the present invention, considering that the LPG consumed in the bottle is limited in a short period of time and that liquid LPG will replenish the consumed LPG, the total amount of LPG in the bottle can be considered unchanged. According to the ideal gas state equation, gas pressure and temperature are linearly positively correlated. Therefore, with temperature as the horizontal axis and pressure as the vertical axis, a linear fit is performed on the temperature data of a preset historical neighborhood and the air inlet pressure to obtain a temperature-pressure fitting line.

[0054] Considering that when gas pressure and temperature are linearly positively correlated, the slope is positive and the coefficient of determination is large, the slope and coefficient of determination of the temperature-pressure fitting line reflect the correlation between the inlet pressure and temperature data and the probability of normal air tightness. The slope and coefficient of determination of the temperature-pressure fitting line are both positively correlated with the probability of normal air tightness.

[0055] As an example, a judgment function is set. When the slope of the temperature-pressure fitting line is positive, it conforms to the normal change of the pressure inside the bottle due to the increase in temperature. The slope mapping value is set to 1. When the slope is less than or equal to 0, it means that the inlet pressure does not conform to the actual temperature change. In other words, as the temperature increases, the pressure inside the bottle remains basically stable or shows a downward trend. This indicates that there is a high possibility of a sealing problem in the bottle, leading to a gas leak. The slope mapping value is set to the slope itself.

[0056] After linear normalization of the slope mapping value, the product of the normalized result and the coefficient of determination is taken as the probability of airtightness being normal.

[0057] Whether to issue an early warning is determined based on the possibility of normal air tightness.

[0058] Considering that the greater the possibility of normal air tightness, the more linear positive correlation between gas pressure and temperature is, which is consistent with normal air tightness, when the possibility of normal air tightness is less than the first preset threshold, it is determined to issue an early warning.

[0059] As an example, the first preset threshold is 0.8.

[0060] It should be noted that, when performing straight-line fitting, the existing least squares algorithm is used; in other embodiments of the present invention, the implementer may also fuse the slope and determination coefficient of the temperature-pressure fitting line through positive correlation methods such as addition and weighted summation, such as weighted summation with weights of 0.5 and 0.5, and use the weighted summation result as the possibility of normal airtightness; use other straight-line fitting methods such as gradient descent method, and set other first preset thresholds; the method for obtaining the determination coefficient and the straight-line fitting method are both existing technologies and will not be repeated here.

[0061] Deep analysis module 103: When the valve is open and no warning is issued, the preset historical neighborhood is divided into preset time periods; based on the changing trend of the air inlet pressure in each preset time period and the characteristics of the violent fluctuation of the air inlet pressure, the leakage possibility of each preset time period is obtained; based on the difference in the changing trend of the air inlet pressure in the adjacent preset time periods in time sequence and combined with all leakage possibilities, it is determined whether to issue a warning.

[0062] Considering that the LPG leak may not be enough to change the current monitored pressure data, resulting in the temperature and pressure in the bottle showing a normal correlation, even though there is a real LPG leak. Therefore, the correlation between temperature and inlet pressure alone is not an accurate indicator of true airtightness and requires further evaluation.

[0063] In order to analyze the local fluctuation changes of the data in more detail, when the valve is opened and no warning is issued, the preset historical neighborhood is divided into preset time periods.

[0064] As an example, the time domain length of the preset period is 1 minute, that is, 3 minutes of historical data is divided into 3 1-minute historical data sub-segments, and the data time sequence of each historical data sub-segment is continuous. In other embodiments of the present invention, the implementer can set other division methods.

[0065] Considering that when the air tightness of the liquefied petroleum gas cylinder is good, the pressure inside the bottle is relatively stable and the air inlet pressure will only fluctuate slightly; when there is an air tightness defect, the change trend of the pressure data will deviate significantly, and when an air tightness defect occurs, the original equilibrium state will be broken, causing the pressure data to fluctuate violently. Therefore, according to the change trend of the air inlet pressure in each preset time period and the violent fluctuation characteristics of the air inlet pressure, the leakage possibility of each preset time period is obtained, and the possibility of air tightness defects in each preset time period is characterized, providing a basis for subsequent judgment.

[0066] See also Figure 2 , which shows a flow chart of a method for obtaining leakage possibility provided by an embodiment of the present invention, specifically comprising:

[0067] Step S301: With temperature as the horizontal axis and pressure as the vertical axis, perform linear fitting on the temperature data and the air inlet pressure of each preset time period to obtain a sub-segment fitting straight line; within each preset time period, classify the air inlet pressure above the sub-segment fitting straight line into the first category, and classify the air inlet pressure below the sub-segment fitting straight line into the second category, and classify the similar air inlet pressures adjacent in time sequence into one segment to obtain similar pressure segments.

[0068] Since the preliminary analysis module 102 did not issue an early warning, the air inlet pressure and temperature data showed a normal linear positive correlation, so a straight line fitting was performed, and the air inlet pressure was classified with the help of the sub-segment fitting straight line; the air inlet pressure on the sub-segment fitting straight line was ideal data, the air inlet pressure on the upper side of the sub-segment fitting straight line was too high and was classified into the first category; the air inlet pressure on the lower side was too low and was classified into the second category; then the similar air inlet pressures adjacent in time series were divided into one section to obtain similar pressure segments, which facilitated the analysis of the situation where the air inlet pressure continued to deviate from the ideal data.

[0069] In another embodiment of the present invention, the air inlet pressure can be directly classified using the temperature-pressure fitting line: the air inlet pressure above the temperature-pressure fitting line is classified into the first category, and the air inlet pressure below the temperature-pressure fitting line is classified into the second category.

[0070] Step S302: Obtain the deviation trend intensity of each preset time period according to the data quantity of the longest pressure segment of the same type in each preset time period.

[0071] Considering that the more data of the longest similar pressure segment within the preset period, the longer the duration of deviation from the normal ideal inlet pressure within the preset period, the more significant the deviation trend of the inlet pressure, and the number of data of the longest similar pressure segment are positively correlated with the intensity of the deviation trend.

[0072] As an example, the ratio of the number of data of the longest pressure segment of the same type in each preset time period to the total amount of data of all inlet pressure data in the preset time period is used as the deviation trend intensity of the corresponding preset time period, and the deviation trend intensity is used to express the changing trend of the inlet pressure in the preset time period.

[0073] Step S303: Obtain the abnormal fluctuation coefficient for each preset period based on the difference in quantity of the two types of air inlet pressure data in each preset period, combined with the difference in discrete distribution of the two types of air inlet pressure data and the discrete intensity of each type of air inlet pressure data.

[0074] Considering that when the liquefied petroleum gas cylinder has no airtightness defects, the pressure inside the bottle will fluctuate on both sides of the fitted pressure (sub-segment fitting straight line), and the quantity distribution and discrete distribution on both sides are relatively similar; at the same time, since the temperature and inlet pressure have a strong linear positive correlation feature, the inlet pressure data on each side are closer to the sub-segment fitting straight line and the discrete intensity is smaller. Therefore, the quantity difference and discrete distribution difference between the two types of inlet pressure data, as well as the discrete intensity of each type of inlet pressure data are positively correlated with the abnormal fluctuation coefficient.

[0075] As an example, any current preset period is selected as the target period. The calculation formula for the abnormal fluctuation coefficient of the target period includes:

[0076] h=norm((|cv1+cv2|+|cv1-cv2|)×|N1-N2|);

[0077] Among them, h represents the abnormal fluctuation coefficient of the target period; norm() represents the linear normalization function; cv1 represents the coefficient of variation of the first type of air inlet pressure data within the target period; cv2 represents the coefficient of variation of the second type of air inlet pressure data within the target period; N1 represents the number of first type of air inlet pressure data within the target period; N2 represents the number of second type of air inlet pressure data within the target period; || represents taking the absolute value.

[0078] In the calculation formula of the abnormal fluctuation coefficient, the discrete characteristics of each type of inlet pressure data are expressed by the coefficient of variation. The larger the coefficient of variation, the greater the discrete intensity of the data, the larger the |cv1+cv2|, the more severe the inlet pressure fluctuation, and the more likely it is that the abnormal fluctuation is caused by airtightness defects, and the larger h is; the difference in the coefficient of variation is expressed in the form of the absolute value of the difference. The larger the |cv1-cv2|, the greater the difference in the discrete distribution of the two inlet pressures, and the more likely it is that the abnormal fluctuation is caused by airtightness defects, and the larger h is; the larger the |N1-N2|, the greater the difference in the number of the two inlet pressures, indicating that there are more inlet pressure data higher or lower than the fitting pressure, and the more likely it is that the abnormal fluctuation is caused by airtightness defects, and the larger h is; from the perspective of the discrete intensity of each type of inlet pressure data and the number and discrete distribution of different types of inlet pressure data, the violent fluctuation characteristics of the inlet pressure are expressed.

[0079] The preset time periods are taken as target time periods one by one, and the abnormal fluctuation coefficient of each preset time period is obtained.

[0080] In other embodiments of the present invention, the implementer may also fuse the quantity differences and discrete distribution differences of the two types of air inlet pressure data, as well as the discrete intensity of each type of air inlet pressure data, through positive correlation methods such as addition or weighted summation; for example, norm(|cv1+cv2|), norm(|cv1-cv2|) and norm(|N1-N2|) are all weightedly summed with a weight of 1 / 3, and the weighted summation result is used as the abnormal fluctuation coefficient.

[0081] Step S304: The deviation trend strength and the abnormal fluctuation coefficient are integrated to obtain the leakage possibility of each preset time period.

[0082] Considering that the greater the deviation trend intensity, the longer the duration of deviation from the normal ideal inlet pressure within the preset period, the more likely it is that the abnormal deviation is caused by leakage; at the same time, the larger the abnormal fluctuation coefficient, the more likely it is that the abnormal fluctuation of the inlet pressure is caused by airtightness defects, so the deviation trend intensity and the abnormal fluctuation coefficient are both positively correlated with the possibility of leakage.

[0083] As an example, the product of the deviation trend strength and the abnormal volatility coefficient in each preset period is used as the leakage possibility.

[0084] In other embodiments of the present invention, the deviation from the mean of the trend strength and the abnormal fluctuation coefficient may also be used as the possibility of leakage.

[0085] Considering that when there is no airtightness defect, the change of the air inlet pressure caused by the consumption of petroleum gas during use is relatively stable. Therefore, based on the difference in the changing trend of the air inlet pressure in the adjacent preset time periods, the possibility of the existence of airtightness defects is analyzed from the perspective of the change trend. At the same time, all leakage possibilities are combined to jointly determine whether to issue an early warning from the perspective of leakage possibility.

[0086] Preferably, in one embodiment of the present invention, considering that the longest pressure segment of the same type represents the main deviation feature of the inlet pressure from the fitting straight line in the corresponding period, the category of the longest pressure segment of the same type in each preset period is used as the marker category;

[0087] To analyze the changing trend of the inlet pressure, a linear fit was performed on the inlet pressure in each preset period, with time as the horizontal axis and pressure as the vertical axis, to obtain a pressure-time fitting line. Considering that the slope and intercept represent the position and shape of the fitting line, they reflect the main changing trend of the inlet pressure and can be used as trend parameters.

[0088] At the same time, the corresponding leakage possibility is obtained by analyzing the changing trend and violent fluctuation characteristics of the inlet pressure, which also reflects the main trend of the inlet pressure. Therefore, the product of the two-dimensional vector composed of the slope and intercept of the pressure-time fitting line and the leakage possibility is used as the signature vector corresponding to the preset time period. The two-dimensional vector is weighted by the slope possibility, and the two are combined to obtain the signature vector, which is convenient for subsequent comparison of the difference in changing trends.

[0089] Further, according to the difference in the sign type and the sign vector of the adjacent preset time periods in time sequence, combined with the overall characteristics of all leakage possibilities, a leakage risk coefficient is obtained;

[0090] Considering that the overall leakage possibility of all time periods is greater, it means that the possibility of LPG leakage is more likely to occur in the preset historical neighborhood, and the leakage risk is greater; at the same time, the greater the difference in the sign vectors of adjacent time periods, the greater the difference in the changing trend of the air inlet pressure data of adjacent time periods; the greater the difference in the sign type, the greater the difference in the deviation direction of the air inlet pressure data of adjacent time periods, so the difference in the sign type and the difference in the sign vector, as well as the overall characteristics of all leakage possibilities, are positively correlated with the leakage risk coefficient.

[0091] As an example, the calculation formula for the leakage risk factor includes:

[0092]

[0093] Where p represents the leakage risk coefficient; E(b) represents the mean value of the leakage probability of all preset time periods in the current preset historical neighborhood; XOR() represents the exclusive OR function; i represents the sequence number of the preset time period in the current preset historical neighborhood; I represents the number of preset time periods in the current preset historical neighborhood; label i Indicates the type of sign for the i-th preset period; label i+1 Indicates the type of sign for the i+1th preset period; bc i+1 bc represents the flag vector of the i-th preset period; i represents the flag vector of the i+1th preset time period; ‖‖ represents the modulo operation.

[0094] In the calculation formula of the leakage risk coefficient, the average value of the leakage possibility represents the overall characteristics of all leakage possibilities. The greater the overall leakage possibility, the greater the leakage risk coefficient. When the mark type is set to the first category, label = 0, and when the mark type is set to the second category, label = 1. The label is compared by the XOR function. i and label i+1, when they are the same, it means that the deviation direction of the inlet pressure in adjacent preset time periods is consistent, the change of the inlet pressure is relatively consistent, the feedback value is 0, and the leakage risk coefficient is smaller; on the contrary, when they are different, they are 1, and the leakage risk coefficient is larger; the difference of the sign vector of adjacent preset time periods is shown by modulo operation, ‖bc i+1 -bc i The larger the value is, the greater the difference in the inlet pressure change trend is, and the greater the leakage risk coefficient is.

[0095] Determine whether to issue an early warning based on the leakage risk factor.

[0096] Considering that the greater the slope risk coefficient is, the more likely it is that there is an airtightness defect, when the leakage risk coefficient is greater than the second preset threshold, it is determined that an early warning is issued.

[0097] As an example, the second preset threshold is 0.8.

[0098] In another embodiment of the present invention, considering that the probability of normal airtightness also reflects the probability of airtightness defects, the smaller the probability of normal airtightness, the greater the probability of airtightness defects, the leakage risk coefficient can be further corrected: after linearly normalizing the ratio of the leakage risk coefficient to the probability of normal airtightness, the normalized result is used as the corrected leakage risk. When the corrected leakage risk is greater than a fourth preset threshold, it is determined to issue an early warning; wherein the fourth preset threshold is 0.8, and the probability of normal airtightness is in the denominator;

[0099] It should be noted that, since the preliminary analysis module 102 has issued an early warning when the probability of normal air tightness is zero, the denominator is not zero when calculating the corrected leakage risk.

[0100] In other embodiments of the present invention, the implementer may also select a type of air inlet pressure with the largest amount of data, and use the corresponding type as the flag type to set other second preset thresholds.

[0101] When using bottled liquefied petroleum gas (LPG), if the outlet flow rate is too high, the outlet velocity will be greater than the combustion rate of the LPG, causing the flame to move away from the fire hole, resulting in flame lift. The burning flame will easily go out, causing gas to leak directly and causing safety accidents. If the outlet flow rate is too low, the outlet velocity will be less than the combustion rate of the LPG, causing flashback, incomplete combustion of the flame, and the generation of toxic gases, which can also cause safety accidents. Therefore, a pressure regulator is needed to dynamically adjust the pressure to maintain a stable outlet flow rate.

[0102] Therefore, in the embodiment of the present invention, an intelligent pressure regulating module is further included, and the intelligent pressure regulating module is used to determine whether to adjust the outlet pressure according to the fluctuation of the outlet flow rate.

[0103] Preferably, in one embodiment of the present invention, the smaller the difference in the gas outlet flow rate between the first and last preset time periods of the current preset historical neighborhood is, the more stable the fluctuation is, indicating that the LPG outlet flow rate is stable in the local time period and the flow stability coefficient is greater;

[0104] Based on this, the flow stability coefficient is obtained according to the difference in the outlet flow rate between the first and last preset time periods and the severity of the fluctuation of the outlet flow rate between the first and last preset time periods; the difference in the outlet flow rate between the first and last preset time periods and the severity of the fluctuation of the outlet flow rate between the first and last preset time periods are both negatively correlated with the flow stability coefficient.

[0105] Determine whether to perform pressure regulation based on the flow stability coefficient.

[0106] As an example, the absolute value of the difference between the mean of the outlet flow rate in the first preset period and the mean of the outlet flow rate in the last preset period is used as the first difference parameter, representing the difference in the outlet flow rate between the first and last preset periods; the sum of the variance of the outlet flow rate in the first preset period and the variance of the outlet flow rate in the last preset period is used as the second fluctuation intensity parameter, representing the degree of fluctuation of the outlet flow rate in the first and last preset periods; the reciprocal of the sum of the first difference parameter and the preset zero-dividing positive parameter 0.01 is taken, and the sum of the reciprocal of the second fluctuation intensity parameter is linearly normalized to obtain the flow stability coefficient;

[0107] When the flow stability coefficient is less than the third preset threshold value of 0.8, it is determined that pressure regulation is to be performed to avoid ineffective pressure regulation due to air tightness defects and more serious leakage accidents caused by pressure regulation during LPG leakage.

[0108] It should be noted that the first and last periods are the results of time sequence sorting, the first preset period is the preset period with the smallest time sequence; the last preset period is the preset period with the largest time sequence; when there is a warning signal, the pressure adjustment operation will not be performed, and the valve must be closed immediately to avoid more serious leakage accidents.

[0109] It should be noted that regulating the outlet pressure of a pressure regulator to ensure that the outlet pressure meets the preset usage standards for bottled LPG is a well-known technology and will not be further elaborated here. The preset usage standards are related to the usage scenarios of bottled LPG. For example, the rated outlet pressures of household and commercial pressure regulators are 2.8kPa and 5.0kPa, respectively. For other usage scenarios, implementers can set their own settings.

[0110] In summary, in response to the technical problem that the existing monitoring of the air tightness of bottled liquefied petroleum gas is inaccurate and leads to inaccurate pressure regulation, the present invention proposes an air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas. The present invention first obtains the data of the inlet and outlet pressure, temperature data and outlet flow of the pressure regulator through the acquisition module; further, in the preliminary analysis module, according to the opening and closing status of the valve, the inlet pressure and outlet pressure and outlet flow are selected for monitoring, or according to the correlation between the inlet pressure and temperature data, a warning is determined; further, the in-depth analysis module analyzes the possibility of leakage and the difference in the changing trend of the inlet pressure to determine whether to issue a warning; and the intelligent pressure regulating module monitors the fluctuation of the outlet flow to determine whether to adjust the outlet pressure.

[0111] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0112] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A device for monitoring the air tightness of bottled liquefied petroleum gas and for intelligently regulating pressure, comprising a pressure regulator, characterized in that: It also includes an air tightness monitoring system and an intelligent pressure regulating module; the air tightness monitoring system includes: Acquisition module: acquiring the inlet and outlet pressure, temperature data and outlet flow of the pressure regulator in a preset historical neighborhood at the same acquisition frequency; Preliminary analysis module: when the valve of the pressure regulator is closed, monitoring the inlet pressure and outlet pressure as well as the outlet flow rate to determine whether to issue an early warning; when the valve is open, determining whether to issue an early warning based on the correlation between the inlet pressure and the temperature data; Deep Analysis Module: When the valve is open and no warning is issued, the preset historical neighborhood is divided into preset time periods; based on the change trend of the air inlet pressure in each preset time period and the characteristics of the sharp fluctuation of the air inlet pressure, the leakage possibility of each preset time period is obtained; based on the difference in the change trend of the air inlet pressure in the adjacent preset time periods, the difference is combined with all the leakage possibilities to determine whether to issue a warning; The intelligent pressure regulating module is used to determine whether to adjust the outlet pressure according to the fluctuation of the outlet flow rate; The method for obtaining the leakage possibility includes: With temperature as the horizontal axis and pressure as the vertical axis, a straight line fitting is performed on the temperature data and the air inlet pressure in each preset time period to obtain a sub-segment fitting straight line; within each preset time period, the air inlet pressures above the sub-segment fitting straight line are classified into a first category, and the air inlet pressures below the sub-segment fitting straight line are classified into a second category, and the similar air inlet pressures adjacent in time sequence are classified into one segment to obtain similar pressure segments; Obtaining the deviation trend strength of each preset period according to the longest data quantity of the same type of pressure segments within each preset period; the longest data quantity of the same type of pressure segments is positively correlated with the deviation trend strength; Obtaining an abnormal fluctuation coefficient for each preset time period based on a difference in quantity between the two types of air inlet pressure data within each preset time period, in combination with a difference in discrete distribution between the two types of air inlet pressure data, and a discrete intensity of each type of air inlet pressure data; the difference in quantity and discrete distribution between the two types of air inlet pressure data, as well as the discrete intensity of each type of air inlet pressure data, are all positively correlated with the abnormal fluctuation coefficient; The deviation trend strength and the abnormal fluctuation coefficient are integrated to obtain the leakage possibility of each preset time period; the deviation trend strength and the abnormal fluctuation coefficient are both positively correlated with the leakage possibility; The method of determining whether to issue an early warning based on the difference in the change trend of the air inlet pressure in the adjacent preset time periods in time sequence and combining all the leakage possibilities includes: The category of the longest pressure segment of the same type within each preset time period is used as the marker category; With time as the horizontal axis and pressure as the vertical axis, a linear fit is performed on the inlet pressure in each of the preset time periods to obtain a pressure-time fitting line; and the product of a two-dimensional vector consisting of a slope and an intercept of the pressure-time fitting line and the leakage probability is used as a signature vector corresponding to the preset time period; Obtaining a leakage risk coefficient based on the differences in the types of the marks and the differences in the mark vectors of the adjacent preset time periods in time sequence, combined with the overall characteristics of all the leakage possibilities; the differences in the types of the marks, the differences in the mark vectors, and the overall characteristics of all the leakage possibilities are positively correlated with the leakage risk coefficient; Whether to issue an early warning is determined based on the leakage risk factor.

2. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 1, characterized in that: The method for determining whether to issue an early warning according to the leakage risk coefficient includes: When the leakage risk coefficient is greater than a second preset threshold, it is determined that an early warning is issued.

3. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 1, characterized in that: The method for determining whether to issue an early warning based on the correlation between the air inlet pressure and the temperature data includes: With temperature as the horizontal axis and pressure as the vertical axis, a linear fit is performed on the temperature data of the preset historical neighborhood and the air inlet pressure to obtain a temperature-pressure fitting line; the probability of normal air tightness is obtained based on the slope and determination coefficient of the temperature-pressure fitting line; the slope and determination coefficient of the temperature-pressure fitting line are both positively correlated with the probability of normal air tightness; Whether to issue an early warning is determined based on the likelihood that the air tightness is normal.

4. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 3, characterized in that: The method for determining whether to issue an early warning based on the normal possibility of air tightness includes: When the probability of normal airtightness is less than a first preset threshold, it is determined that an early warning is issued.

5. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 1, characterized in that: The method of monitoring the air inlet pressure, the air outlet pressure and the air outlet flow to determine whether to issue an early warning includes: When the valve of the pressure regulator is closed, if the air inlet pressure and the air outlet pressure remain unchanged, and the air outlet flow rate remains at 0, it is determined that no warning is issued, otherwise a warning is issued.

6. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 1, characterized in that: The method for determining whether to adjust the outlet pressure according to the fluctuation of the outlet flow rate includes: A flow rate stability coefficient is obtained based on the difference in the air outlet flow rate between the first and last two preset time periods and the severity of the fluctuation of the air outlet flow rate between the first and last two preset time periods; the difference in the air outlet flow rate between the first and last two preset time periods and the severity of the fluctuation of the air outlet flow rate between the first and last two preset time periods are both negatively correlated with the flow rate stability coefficient; Whether to perform pressure regulation is determined according to the flow stability coefficient.

7. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 6, characterized in that: The method for determining whether to perform pressure regulation according to the flow stability coefficient includes: When the flow stability coefficient is less than a third preset threshold, it is determined that pressure regulation is performed.

8. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 5, characterized in that: The linear fitting adopts the least square method.

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