Air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas

Abstract

The invention relates to the technical field of container airtightness detection, in particular to an airtightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas. The invention provides an air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas. The method comprises the following steps: acquiring module historical data; further, in the preliminary analysis module, the air inlet pressure, the air outlet pressure and the air outlet flow are selectively monitored according to the opening and closing state of the valve, or whether an early warning is given out or not is judged according to the correlation between the air inlet pressure and the temperature data; further, a deep analysis module analyzes the leakage possibility, analyzes the difference of the change trend of the pressure intensity of the air inlet, and judges whether to give an early warning or not; and the intelligent pressure regulating module monitors the fluctuation of the flow of the air outlet to judge whether to regulate the pressure of the air outlet. The gas tightness of the liquefied petroleum gas container is accurately monitored by analyzing the change correlation between the pressure intensity and the temperature and the continuity of the change trend of the pressure intensity, the gas flow is monitored, and the pressure intensity of a gas outlet is timely adjusted.

Description

Technical Field

[0001] The 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] During the use of liquefied petroleum gas, the combustion of the gas will cause large temperature changes, resulting in the outlet pressure to remain stable, which does not mean that the gas flow rate is stable. The existing method of monitoring whether the outlet pressure is within the normal fluctuation range has errors, and severe fluctuations in the gas flow rate will cause flame separation or flashback during the actual combustion process. In addition, there is normal gas consumption during use, which makes it difficult to monitor the existing gas leakage, and there are misjudgments of the gas leakage, which makes the gas pressure regulation inaccurate and prone to safety accidents. If the pressure is adjusted when there is an airtightness problem, it may cause more serious gas leakage, resulting in 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 a bottled liquefied petroleum gas air tightness monitoring and intelligent pressure regulation device, and the technical solution adopted is as follows:

[0005] A device for monitoring the air tightness and intelligent pressure regulation of bottled liquefied petroleum gas, the device 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 air inlet, air outlet pressure, temperature data and air 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, the air inlet pressure and the air outlet pressure as well as the air outlet flow rate are monitored to determine whether to issue an early warning; when the valve is opened, whether to issue an early warning is determined based on the correlation between the air 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; according to the change trend of the air inlet pressure in each preset time period, combined with the violent fluctuation characteristics of the air inlet pressure, the leakage possibility of each preset time period is obtained; according to the difference in the change trend of the air inlet pressure in the preset time periods adjacent in time sequence, combined with all the leakage possibilities, it is determined 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 rate.

[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 of each preset time period to obtain a sub-segment fitting straight line; within each preset time period, the air inlet pressure located on the upper side of the sub-segment fitting straight line is classified into the first category, and the air inlet pressure located on the lower side of the sub-segment fitting straight line is classified into the second category, and the air inlet pressures of the same type that are adjacent in time sequence are classified into one segment to obtain a pressure segment of the same type;

[0012] According to the longest data quantity of the same type of pressure segments in each of the preset time periods, the deviation trend strength of each of the preset time periods is obtained; the longest data quantity of the same type of pressure segments is positively correlated with the deviation trend strength;

[0013] According to the quantity difference of the two types of the air inlet pressure data in each of the preset time periods, combined with the discrete distribution difference of the two types of the air inlet pressure data, and the discrete intensity of each type of the air inlet pressure data, the abnormal fluctuation coefficient of each of the preset time periods is obtained; the quantity difference and discrete distribution difference of the two types of the air inlet pressure data, and the discrete intensity of each type of the air inlet pressure data are 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 longest pressure segment of the same type in each preset time period is used as the mark type;

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

[0018] According to the difference of the sign type and the sign vector of the preset time periods adjacent in time sequence, combined with the overall characteristics of all the leakage possibilities, a leakage risk coefficient is obtained; the difference of the sign type and the sign vector, 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 according to the leakage risk factor.

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

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

[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 straight line fitting is performed on the temperature data of the preset historical neighborhood and the air inlet pressure to obtain a temperature-pressure fitting straight line; according to the slope and determination coefficient of the temperature-pressure fitting straight line, the possibility of normal air tightness is obtained; the slope and determination coefficient of the temperature-pressure fitting straight line are both positively correlated with the possibility of normal air tightness;

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

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

[0026] When the airtightness normal possibility 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 and the air outlet pressure as well as the air outlet flow rate 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 for determining whether to adjust the outlet pressure according to the fluctuation of the outlet flow rate includes:

[0030] According to the difference of the outlet flow rate between the first and last two preset time periods, combined with the fluctuation intensity of the outlet flow rate between the first and last two preset time periods, the flow rate stability coefficient is obtained; the difference of the outlet flow rate between the first and last two preset time periods and the fluctuation intensity of the 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 to issue an early warning, 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 deep analysis module: the preset historical neighborhood is equally 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 of the container is monitored from a static perspective; The changing trend of the inlet pressure is combined with the drastic fluctuation characteristics to obtain the possibility of leakage in each preset period, characterize the possibility of airtightness defects in each preset period, and provide a basis for subsequent judgment; further analyze the possibility of airtightness defects from the perspective of the change trend, and jointly determine whether to issue an early warning from the perspective of the possibility of leakage, and monitor the airtightness of the container more carefully; through the intelligent pressure regulating module, determine whether to adjust the outlet pressure according to the fluctuation of the outlet flow, and adjust the pressure in time to avoid ineffective pressure regulation caused by airtightness defects and more serious leakage accidents caused by pressure regulation when the petroleum gas leaks. The present invention accurately monitors the airtightness of the liquefied petroleum gas container by analyzing the correlation between pressure and temperature changes and the continuity of the pressure change trend, and monitors the gas flow to adjust the outlet pressure in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. 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 creative work.

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

[0039] Figure 2 A flowchart of a method for obtaining leakage possibility provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a bottled liquefied petroleum gas airtightness monitoring and intelligent pressure regulating device proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[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] The embodiment of the present invention provides a gas tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas, the device comprising a pressure regulator, wherein the gas inlet of the pressure regulator is connected to the liquefied petroleum gas cylinder, the gas outlet is connected to the outside, and the pressure regulator and the liquefied petroleum gas cylinder are tightly connected through an inlet connection joint; it also comprises a gas tightness monitoring system for monitoring whether there are defects in the gas tightness of the liquefied petroleum gas cylinder, and comprises an intelligent pressure regulating module for timely pressure regulation. The structure and working principle of the pressure regulator are technical means well known to those skilled in the art, and will not be described in detail 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 comprising: a collection module 101, a preliminary analysis module 102 and a deep analysis module 103.

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

[0046] A pressure sensor is 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, and the temperature data 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, 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, which is 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 is used as the analysis object to obtain the analysis result.

[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 opened, whether to issue an early warning is determined based on the correlation between the inlet pressure and temperature data.

[0048] When the valve of the pressure regulator is closed, the bottled liquefied petroleum gas is not in use. 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 inlet and outlet should remain unchanged. Therefore, if the inlet pressure and the outlet pressure remain unchanged, and the 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 pad, valve stem, spring, lever and other components. These components work together to act as a valve, so they are summarized as valves here.

[0051] It should be noted that, taking into account the situation that the time interval from valve closing to valve opening is less than the preset historical neighborhood (3 minutes in one embodiment), and the valve has just been closed, when the time from the moment the valve is closed to the current moment is less than 3 minutes, only the historical data from the moment the valve is closed to the current moment is captured 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 at the air inlet. Therefore, based on the correlation between the pressure and temperature data at 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 in a short period of time is limited, and the liquid LPG will replenish the consumed LPG, the total amount of LPG in the bottle can be regarded as unchanged. According to the ideal gas state equation, the gas pressure and temperature are linearly positively correlated. Therefore, with the temperature as the horizontal axis and the pressure as the vertical axis, the temperature data of the preset historical neighborhood and the air inlet pressure are linearly fitted to obtain the temperature-pressure fitting line;

[0054] Considering that when gas pressure and temperature are linearly positively correlated, the slope is positive and the determination coefficient is large, the slope and determination coefficient of the temperature-pressure fitting line reflect the correlation between the inlet pressure and temperature data, and obtain the possibility of normal air tightness; the slope and determination coefficient of the temperature-pressure fitting line are positively correlated with the possibility 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 is consistent with the normal change of the pressure increase in 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, that is, as the temperature increases, the pressure in the bottle basically remains stable or shows a trend of decreasing pressure, which means that there is a high possibility of sealing problems in the bottle leading to LPG leakage. The slope mapping value is set to the slope itself.

[0056] After the slope mapping value is linearly normalized, the product of the normalized result and the determination coefficient is taken as the possibility of airtightness normality.

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

[0058] Considering that the greater the possibility of normal air tightness, the more the gas pressure and temperature show a linear positive correlation, which is consistent with the normal air tightness situation, so 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 by 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; according to the changing trend of the air inlet pressure in each preset time period, combined with the violent fluctuation characteristics of the air inlet pressure, the leakage possibility of each preset time period is obtained; according to the difference in the changing trend of the air inlet pressure of the adjacent preset time periods in time sequence, combined with all leakage possibilities, it is determined whether to issue a warning.

[0062] Considering that the leakage of LPG may not be enough to change the current monitoring pressure data, the temperature and pressure in the bottle also show a normal correlation, but there is a real LPG leakage. Therefore, it is not accurate to judge the real air tightness only by the correlation between temperature and inlet pressure, and further judgment is needed.

[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 equally 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 airtightness 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 airtightness defect, the change trend of the pressure data will deviate significantly, and when an airtightness 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, combined with the violent fluctuation characteristics of the air inlet pressure, the possibility of leakage in each preset time period is obtained, and the possibility of airtightness 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 on the upper side of the sub-segment fitting straight line into the first category, classify the air inlet pressure on the lower side of the sub-segment fitting straight line into the second category, and classify the similar air inlet pressures adjacent in time sequence into one section to obtain similar pressure segmentation.

[0068] Since the preliminary analysis module 102 did not issue a 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 relatively high, and was classified into the first category; the air inlet pressure on the lower side was relatively low, and was classified into the second category; then the similar air inlet pressures adjacent in time series were divided into one section, and the similar pressure segmentation was obtained, which was convenient for analyzing the situation where the air inlet pressure continued to deviate from the ideal data.

[0069] In another embodiment of the present invention, the inlet pressure can be directly classified using the temperature-pressure fitting line: the inlet pressure on the upper side of the temperature-pressure fitting line is classified into the first category, and the inlet pressure on the lower side of 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 the 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 is 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 data of all air 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 air inlet pressure in the preset time period.

[0073] Step S303: according to the quantity difference of the two types of air inlet pressure data in each preset time period, combined with the discrete distribution difference of the two types of air inlet pressure data, and the discrete intensity of each type of air inlet pressure data, the abnormal fluctuation coefficient of each preset time period is obtained.

[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 fitting 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 the inlet pressure have a strong linear positive correlation, the inlet pressure data on each side fits the sub-segment fitting straight line more closely and the discrete intensity is small, so the quantity difference and discrete distribution difference of 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, and the calculation formula of 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 in the target period; cv2 represents the coefficient of variation of the second type of air inlet pressure data in the target period; N1 represents the number of the first type of air inlet pressure data in the target period; N2 represents the number of the second type of air inlet pressure data in 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 strength of the data, the larger the |cv1+cv2|, the more drastic 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, which means 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 strength 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 strength of each type of air inlet pressure data, by means of 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: Fusion the deviation trend strength and the abnormal fluctuation coefficient to obtain the leakage possibility of each preset time period.

[0082] Considering that the greater the deviation trend intensity, the longer the duration of the deviation from the normal ideal air 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 that the air inlet pressure is an abnormal fluctuation caused by airtightness defects, so the deviation trend intensity and the abnormal fluctuation coefficient are 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 time period is taken as the leakage possibility.

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

[0085] Considering that when there is no airtightness defect, the change of the air inlet pressure caused by the consumption of LPG during use is relatively stable. Therefore, according to the difference in the changing trend of the air inlet pressure in 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, combined with all leakage possibilities, it is jointly determined whether to issue an early warning based on the leakage possibility angle.

[0086] Preferably, in one embodiment of the present invention, considering that the longest pressure segment of the same type represents the main deviation characteristics of the air inlet pressure relative to the fitting straight line in the corresponding period, the category to which the longest pressure segment of the same type belongs in each preset period is used as the mark category;

[0087] In order to analyze the changing trend of the inlet pressure, a straight line fitting is performed on the inlet pressure of 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 sign vector corresponding to the preset time period; the two-dimensional vector is weighted by the slope possibility, and the two are fused to obtain the sign vector, which is convenient for subsequent comparison of the difference in changing trends.

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

[0090] Considering that the overall greater the possibility of leakage in all time periods, it means that the more likely it is that there will be a petroleum gas leakage in the preset historical neighborhood, and the greater the leakage risk; 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 type of signs, the greater the difference in the deviation direction of the air inlet pressure data of adjacent time periods, so the difference in the type of signs, the difference in the sign vector, and 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, the same means that the deviation direction of the inlet pressure in the 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, if they are not 1 at the same time, the leakage risk coefficient is larger; the difference of the sign vector of the adjacent preset time periods is shown by the modulus operation, ‖bc i+1 -bc i The larger the value is, the greater the difference in the change trend of the inlet pressure 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 larger 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 to issue an early warning.

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

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

[0099] It should be noted that, since the preliminary analysis module 102 has issued an early warning when the possibility of normal airtightness 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 the corresponding type as the flag type, and set other second preset thresholds.

[0101] During the use of bottled liquefied petroleum gas, if the gas flow rate is too large, the gas flow rate is greater than the combustion speed of the petroleum gas, causing the flame to move away from the fire hole, resulting in flame separation; the burning flame is very easy to extinguish, causing the gas to leak directly, causing safety accidents. If the gas flow rate is too small, the gas flow rate is less than the combustion speed of the petroleum gas, flashback occurs, the flame is not completely burned, and toxic gases are generated, which will also cause safety accidents; therefore, it is necessary to use a pressure regulator to dynamically adjust the pressure to keep the gas flow rate stable.

[0102] Therefore, in the embodiment of the present invention, an intelligent pressure regulating module is also 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, considering that the smaller the difference in the gas outlet flow rate between the first and last two 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 rate 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 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 between the outlet flow rates of 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 fluctuation intensity 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 and the reciprocal of the sum of the first difference parameter and the second fluctuation intensity parameter are 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 are the results of time sequence sorting, the first preset time period is the preset time period with the smallest time sequence; the last preset time period is the preset time 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 the pressure regulator regulates the pressure so that the outlet pressure meets the preset usage standards of bottled liquefied petroleum gas, which is already an existing technology and will not be described in detail here. The preset usage standards are related to the usage scenarios of bottled liquefied petroleum gas. For example, the rated outlet pressures of household and commercial pressure regulators are 2.8kPa and 5.0kPa respectively. In other usage scenarios, implementers can set them by themselves.

[0110] In summary, 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 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 rate of the pressure regulator through the acquisition module; further, in the preliminary analysis module, according to the opening and closing state of the valve, the inlet pressure and outlet pressure and outlet flow rate are selected for monitoring, or according to the correlation between the inlet pressure and temperature data, it is determined whether to issue an early warning; further, the deep analysis module analyzes the possibility of leakage, and analyzes the difference in the changing trend of the inlet pressure to determine whether to issue an early warning; and the intelligent pressure regulating module is used to monitor the fluctuation of the outlet flow rate to determine whether to adjust the outlet pressure.

[0111] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some 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 referenced to each other, and 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 intelligent pressure regulation, the device 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 air inlet, air outlet pressure, temperature data and air 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, the air inlet pressure and the air outlet pressure as well as the air outlet flow rate are monitored to determine whether to issue an early warning; when the valve is opened, whether to issue an early warning is determined based on the correlation between the air 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; according to the change trend of the air inlet pressure in each preset time period, combined with the violent fluctuation characteristics of the air inlet pressure, the leakage possibility of each preset time period is obtained; according to the difference in the change trend of the air inlet pressure in the preset time periods adjacent in time sequence, combined with all the leakage possibilities, it is determined 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.

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 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 of each preset time period to obtain a sub-segment fitting straight line; within each preset time period, the air inlet pressure located on the upper side of the sub-segment fitting straight line is classified into the first category, and the air inlet pressure located on the lower side of the sub-segment fitting straight line is classified into the second category, and the air inlet pressures of the same type that are adjacent in time sequence are classified into one segment to obtain a pressure segment of the same type; According to the longest data quantity of the same type of pressure segments in each of the preset time periods, the deviation trend strength of each of the preset time periods is obtained; the longest data quantity of the same type of pressure segments is positively correlated with the deviation trend strength; According to the quantity difference of the two types of the air inlet pressure data in each of the preset time periods, combined with the discrete distribution difference of the two types of the air inlet pressure data, and the discrete intensity of each type of the air inlet pressure data, the abnormal fluctuation coefficient of each of the preset time periods is obtained; the quantity difference and discrete distribution difference of the two types of the air inlet pressure data, and the discrete intensity of each type of the air inlet pressure data are 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.

3. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 2, characterized in that: 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 longest pressure segment of the same type in each preset time period is used as the mark type; With time as the horizontal axis and pressure as the vertical axis, a straight line fitting is performed on the air inlet pressure in each of the preset time periods to obtain a pressure-time fitting straight line; the product of a two-dimensional vector consisting of a slope and an intercept of the pressure-time fitting straight line and the leakage possibility is used as a sign vector corresponding to the preset time period; According to the difference of the sign type and the sign vector of the preset time periods adjacent in time sequence, combined with the overall characteristics of all the leakage possibilities, a leakage risk coefficient is obtained; the difference of the sign type and the sign vector, 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 according to the leakage risk factor.

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 according to the leakage risk coefficient includes: When the leakage risk coefficient is greater than a second preset threshold, it is determined to issue an early warning.

5. 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 a 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 straight line fitting is performed on the temperature data of the preset historical neighborhood and the air inlet pressure to obtain a temperature-pressure fitting straight line; according to the slope and determination coefficient of the temperature-pressure fitting straight line, the possibility of normal air tightness is obtained; the slope and determination coefficient of the temperature-pressure fitting straight line are both positively correlated with the possibility of normal air tightness; Whether to issue an early warning is determined based on the likelihood that the airtightness is normal.

6. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 5, characterized in that: The method for determining whether to issue an early warning according to the normal possibility of air tightness includes: When the airtightness normal possibility is less than a first preset threshold, it is determined that an early warning is issued.

7. 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 and the air outlet pressure as well as the air outlet flow rate 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.

8. 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: According to the difference of the outlet flow rate between the first and last two preset time periods, combined with the fluctuation intensity of the outlet flow rate between the first and last two preset time periods, the flow rate stability coefficient is obtained; the difference of the outlet flow rate between the first and last two preset time periods and the fluctuation intensity of the 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.

9. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 8, 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.

10. The air tightness monitoring and intelligent pressure regulating device for bottled liquefied petroleum gas according to claim 2, 3 or 5, characterized in that: The linear fitting adopts the least square method.

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