A method for measuring liquid level of fire water tank

Abstract

The present invention relates to the technical field of water level monitoring of building fire water tanks, and proposes a method for measuring the liquid level of a fire water tank, including: collecting water level data and pressure data, obtaining a water level sequence, a pressure sequence and a first-order difference sequence of the pressure sequence at the current sampling moment, obtaining the change continuity at the current sampling moment, and obtaining the fluctuation factor at the current sampling moment in combination with the change trend of the pressure data in the pressure sequence at the current sampling moment; obtaining the fluctuation difference of the water level data and the local fluctuation sequence at the current sampling moment, obtaining the water level change index at the current sampling moment, and obtaining the potential water level influence factor at the current sampling moment in combination with the fluctuation factor at the current sampling moment; adjusting the water level data at the current collection moment according to the potential water level influence factor at the current sampling moment, and obtaining the liquid level measurement result of the fire water tank. The present invention aims to solve the problem that slight leakage is extremely difficult to detect, making the liquid level measurement of the fire water tank inaccurate.

Description

Technical Field

[0001] The invention relates to the technical field of water level monitoring of building fire water tanks, and in particular to a method for measuring the liquid level of a fire water tank. Background Art

[0002] Fire water pools are an indispensable infrastructure in the modern building safety system. They can store a large amount of water and quickly provide a stable and reliable water source for fire fighting during the fire fighting and rescue process. They play a vital role in ensuring building safety. Due to the tight land restrictions in urban areas and the residents' requirements for environmental beauty, underground closed fire water pools are the most common type of fire water pools. Underground closed fire water pools are underground, which effectively utilizes underground space. Through the closed design, the fire water pool reduces the impact of the surrounding environment and prevents pollutants and impurities from entering the pool.

[0003] However, the closed design of underground closed fire water pools often makes it difficult to detect leakage problems in time. Since the pool is located underground, the leaked water may be directly absorbed by the surrounding soil and will not immediately show obvious signs on the ground. At the same time, the leakage is generally very slow, making the drop in the water level in the underground closed fire water pool extremely difficult to detect. Conventional monitoring methods cannot accurately and quickly detect leakage problems, affecting the reliability of the fire water pool and the safety of water supply. Therefore, a liquid level measurement method for fire water pools is needed to avoid the impact of leakage problems on fire response. Summary of the invention

[0004] The present invention provides a method for measuring the liquid level of a fire water tank to solve the problem that slight leakage is extremely difficult to detect, resulting in inaccurate liquid level measurement in the fire water tank. The technical solution adopted is as follows:

[0005] An embodiment of the present invention provides a method for measuring the liquid level of a fire water tank, the method comprising the following steps:

[0006] Collect water level data and pressure data at the current sampling time and at each sampling time in the previous local time period to obtain the water level sequence and pressure sequence at the current sampling time;

[0007] Obtain the first-order difference sequence of the pressure sequence at the current sampling moment, record the ratio of the number of data not equal to 0 in the first-order difference sequence to the number of all data contained in the first-order difference sequence as the fluctuation data ratio at the current sampling moment; record the data segment consisting of consecutive adjacent data not equal to 0 in the first-order difference sequence as the continuous fluctuation data segment, record the average of the number of data contained in all continuous fluctuation data segments in the first-order difference sequence as the continuous fluctuation length; record the number of all continuous fluctuation data segments in the first-order difference sequence as the continuous fluctuation number; record the product of the fluctuation data ratio, the continuous fluctuation number and the continuous fluctuation length at the current sampling moment as the change continuity at the current sampling moment;

[0008] Perform straight line fitting on the pressure sequence at the current sampling moment, obtain the slope of the fitted straight line, and record the absolute value of the slope of the fitted straight line as the change trend at the current sampling moment; record the product of the change trend at the current sampling moment and the change duration as the fluctuation factor at the current sampling moment;

[0009] Any water level data in the water level sequence at the current sampling moment is recorded as the target water level data, and the range of a preset number of water level data adjacent to the target water level data is recorded as the fluctuation difference of the target water level data; the product of the standard deviation of all fluctuation differences in the local fluctuation sequence at the current sampling moment and the fluctuation difference of the water level data at the current sampling moment is recorded as the water level change index at the current sampling moment; the ratio of the fluctuation factor at the current sampling moment to the water level change index is recorded as the potential water level influencing factor at the current sampling moment;

[0010] The water level data at the current sampling moment is adjusted according to the potential water level influencing factors at the current sampling moment to obtain the liquid level measurement result of the fire water tank.

[0011] Further, the water level data at the current sampling moment is adjusted according to the potential water level influencing factor at the current sampling moment to obtain the liquid level measurement result of the fire water tank, including the specific method of:

[0012] The water level data at the current acquisition moment is processed using the Kalman filter algorithm to obtain the Kalman gain at the current acquisition moment, and the adjusted Kalman gain at the current sampling moment is obtained according to the potential water level influencing factor and the Kalman gain at the current sampling moment;

[0013] The adjusted Kalman gain at the current sampling moment is used as the value of the Kalman gain, and the Kalman filter algorithm is used to process the water level data at the current collection moment to obtain the optimal estimate, and the value of the optimal estimate is used as the liquid level measurement result of the underground closed fire water tank.

[0014] Furthermore, the specific method for obtaining the adjusted Kalman gain at the current sampling moment is:

[0015] The product of the normalized value of the potential water level influencing factor at the current sampling moment, the Kalman gain at the current acquisition moment, and the number 2 is recorded as the adjusted Kalman gain at the current sampling moment.

[0016] The beneficial effects of the present invention are:

[0017] The present application first evaluates the significance and duration of the unusual fluctuations in the pressure inside the water pool, and obtains the duration of the change at the current sampling moment. The greater the duration of the change at the current sampling moment, the longer the data segment with continuous fluctuations in the pressure sequence at the current sampling moment and the more frequent the occurrence. The greater the volatility of the pressure data contained in the pressure sequence at the current sampling moment, the stronger the persistence of the fluctuating data. Further, in combination with the changing trend of the pressure data in the pressure sequence at the current sampling moment, the fluctuation factor at the current sampling moment is obtained. The greater the fluctuation factor at the current sampling moment, the stronger the volatility of the pressure data within the day before the current sampling moment, and the greater the possibility of leakage in the underground closed fire water pool. Then, considering that other environmental factors near the underground closed fire water pool will also affect the collected data In order to improve the accuracy of underground closed fire water tank leakage judgment and further improve the stability of fire water tank liquid level measurement, the influence of other environmental factors on the collected data is evaluated, and the water level change index at the current sampling moment is obtained. Then, according to the water level change index and fluctuation factor at the current sampling moment, the potential water level influence factor at the current sampling moment is obtained. The potential water level influence factor at the current sampling moment is an evaluation of the degree of influence of all influencing factors on the accuracy of the water level data collected at the current sampling moment. Finally, according to the potential water level influence factor at the current sampling moment, the water level data at the current collection moment is adjusted to obtain the liquid level measurement result of the fire water tank, so as to solve the problem that slight leakage is extremely difficult to detect, resulting in inaccurate liquid level measurement of the fire water tank. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be 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 labor.

[0019] Figure 1 A schematic flow chart of a method for measuring the liquid level of a fire water tank provided by an embodiment of the present invention;

[0020] Figure 2 A flowchart for obtaining potential water level influencing factors provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] See also Figure 1 , which shows a flow chart of a method for measuring the liquid level of a fire water tank provided by an embodiment of the present invention, the method comprising the following steps:

[0023] Step S001: Collect water level data and pressure data at the current sampling time and at each sampling time in the previous local time period to obtain the water level sequence and pressure sequence at the current sampling time.

[0024] Before the underground closed fire water pool is closed, a float type water level sensor and a capacitive pressure sensor are placed in the underground closed fire water pool. After the underground closed fire water pool is closed and used, the float type water level sensor is used to collect the water level data in the underground closed fire water pool, and the capacitive pressure sensor is used to collect the pressure data in the underground closed fire water pool.

[0025] Arrange the water level data at the current sampling time and before in the order of acquisition time to obtain the water level sequence at the current sampling time. Arrange the pressure data at the current sampling time and before in the order of acquisition time to obtain the pressure sequence at the current sampling time.

[0026] Among them, the collection time intervals of water level data and pressure data are the same. The empirical value of the collection time interval in this embodiment is 5 seconds. Both the water level sequence and the pressure sequence contain data within one day. As other implementation methods, the implementer can decide the sampling rate and the number of samples according to the actual situation. This application does not impose any special restrictions.

[0027] It should be noted that, in order to facilitate calculation, all water level data and pressure data involved in the calculation in this embodiment are pre-processed to eliminate the dimension effect. This embodiment uses the Z-Score standard normalization method to remove the dimension of the water level data and pressure data respectively. In actual application, the implementer can use other methods of the prior art to remove the dimension, which is not limited here.

[0028] At this point, the water level sequence and pressure sequence at the current sampling moment are obtained.

[0029] Step S002: Obtain the change continuity at the current sampling moment according to the data distribution and quantity of the numerical differences between adjacent pressure data in the pressure sequence at the current sampling moment, and obtain the fluctuation factor at the current sampling moment according to the change trend of the pressure data in the pressure sequence at the current sampling moment and the change continuity at the current sampling moment.

[0030] The design of underground closed fire water tanks takes the balance of internal pressure into consideration. When the airtightness of the water tank is good, there will be no air or water leakage, so under normal operating conditions, the pressure inside the water tank is kept within the preset safety range. When the pressure inside the water tank fluctuates unusually, it indicates that the airtightness of the water tank may be damaged, which may cause the water level of the water stored inside the underground closed fire water tank to change.

[0031] The first-order difference sequence of the pressure sequence at the current sampling moment is obtained. The calculation of the first-order difference sequence of the sequence is a well-known technology and will not be described in detail.

[0032] According to the data distribution and quantity of the data not equal to 0 in the first-order difference sequence of the pressure sequence at the current sampling moment, the fluctuation data proportion, continuous fluctuation length and continuous fluctuation quantity at the current sampling moment are obtained.

[0033] Preferably, as an embodiment of the present application, the ratio of the number of data not equal to 0 in the first-order difference sequence to the number of all data contained in the first-order difference sequence is recorded as the fluctuation data ratio at the current sampling moment. The data segment composed of continuous adjacent data not equal to 0 in the first-order difference sequence is recorded as the continuous fluctuation data segment, the mean of the number of data contained in all continuous fluctuation data segments in the first-order difference sequence is recorded as the continuous fluctuation length at the current sampling moment, and the number of all continuous fluctuation data segments in the first-order difference sequence is recorded as the continuous fluctuation number at the current sampling moment.

[0034] Data that is not equal to 0 in the first-order difference sequence corresponds to data that is not equal to the adjacent data in the pressure sequence at the current sampling moment, that is, data that is not equal to 0 in the first-order difference sequence corresponds to data that fluctuates in the pressure sequence at the current sampling moment. The more fluctuating data there are in the pressure sequence at the current sampling moment, the more unstable the pressure data at the current sampling moment and the previous day. Continuous fluctuation data segments correspond to data segments that continuously fluctuate in the pressure sequence at the current sampling moment. When the length of continuous fluctuations and the number of continuous fluctuations are larger, the data segments that continuously fluctuate in the pressure sequence at the current sampling moment are longer and appear more frequently, the greater the volatility of the pressure data contained in the pressure sequence at the current sampling moment, and the stronger the persistence of the fluctuating data.

[0035] According to the fluctuation data ratio, continuous fluctuation number and continuous fluctuation length at the current sampling moment, the change continuity at the current sampling moment is obtained. Among them, the change continuity at the current sampling moment is positively correlated with the fluctuation data ratio, continuous fluctuation number and continuous fluctuation length at the current sampling moment.

[0036] Preferably, as an embodiment of the present application, the product of the fluctuation data ratio, the number of continuous fluctuations and the length of continuous fluctuations at the current sampling moment is recorded as the change continuity at the current sampling moment.

[0037] Among them, the calculation formula for the change continuity at the current sampling time is:

[0038]

[0039] in, Indicates the duration of change at the current sampling moment; Indicates the continuous fluctuation length at the current sampling moment; Indicates the number of continuous fluctuations at the current sampling moment; Indicates the proportion of fluctuation data at the current sampling moment.

[0040] The greater the proportion of fluctuation data, the number of continuous fluctuations and the length of continuous fluctuations at the current sampling moment, the greater the continuity of the change at the current sampling moment. At this time, the longer the data segment in which fluctuations appear continuously in the pressure sequence at the current sampling moment and the more frequently they appear, the greater the volatility of the pressure data contained in the pressure sequence at the current sampling moment, and the stronger the continuity of the fluctuating data.

[0041] According to the change trend of the pressure data in the pressure sequence at the current sampling moment and the change continuity at the current sampling moment, the fluctuation factor at the current sampling moment is obtained.

[0042] A straight line fitting is performed on the pressure sequence at the current sampling moment to obtain the slope of the fitting line, and the absolute value of the slope of the fitting line is recorded as the change trend at the current sampling moment.

[0043] This embodiment uses the least square method to perform straight line fitting. Using the least square method to perform straight line fitting is a well-known technology and will not be described in detail.

[0044] When the absolute value of the slope of the fitting straight line is larger, the change trend at the current sampling time is larger. At this time, the change trend of the pressure data at the current sampling time and the previous day is more obvious, the pressure data changes more dramatically with time, and the volatility of the pressure data at the current sampling time and the previous day is stronger.

[0045] According to the change trend and change duration of the current sampling moment, the fluctuation factor of the current sampling moment is obtained.

[0046] Preferably, as an embodiment of the present application, the fluctuation factor at the current sampling moment is the product of the change trend and the change duration at the current sampling moment.

[0047] Among them, the calculation formula of the fluctuation factor at the current sampling time is:

[0048]

[0049] in, Indicates the fluctuation factor at the current sampling moment; Indicates the changing trend at the current sampling time; Indicates the duration of change at the current sampling moment.

[0050] The greater the change trend and duration of the current sampling time, the greater the fluctuation factor of the current sampling time. At this time, the longer and more frequent the data segment with continuous fluctuations at the current sampling time and the previous day, the more drastic the change of pressure data over time. The stronger the volatility of pressure data at the current sampling time and the previous day, the greater the possibility of leakage in the underground closed fire water tank.

[0051] At this point, the fluctuation factor at the current sampling moment is obtained.

[0052] Step S003, according to the difference between different water level data within a preset range of water level data in the water level sequence, obtain the fluctuation difference of water level data, arrange the fluctuation difference of water level data according to the collection order of water level data, obtain the local fluctuation sequence at the current sampling moment, and obtain the potential water level influencing factor at the current sampling moment according to the difference between the fluctuation factor at the current sampling moment and the fluctuation difference in the local fluctuation sequence at the current sampling moment.

[0053] When a slight underground closed fire water tank leaks, the water level in the underground closed fire water tank changes slowly, and the data collected at different collection times show continuous slight changes. However, other environmental factors near the underground closed fire water tank will also affect the collected data, resulting in continuous slight changes in the data. Other environmental factors include construction near the underground closed fire water tank, vehicle passing, and groundwater flow. Therefore, it is necessary to evaluate the impact of other environmental factors on the collected data, improve the accuracy of the judgment of underground closed fire water tank leakage, and then improve the stability of the liquid level measurement of the fire water tank.

[0054] Any water level data in the water level sequence at the current sampling moment is recorded as the target water level data. This embodiment is described by taking any water level data as an example.

[0055] The extreme differences of the preset number of water level data adjacent to the target water level data are recorded as the fluctuation difference of the target water level data.

[0056] The same method can be used to obtain the fluctuation difference of any water level data in the water level sequence at the current sampling moment, that is, each water level data in the water level sequence at the current sampling moment has a corresponding fluctuation difference. In this embodiment, the value of the preset number is 15.

[0057] The fluctuation difference of the water level data evaluates the fluctuation degree of the water level data in a local area of ​​the water level data. When the fluctuation degree of the water level data in the local area of ​​the water level data is greater, the fluctuation difference of the water level data is greater.

[0058] The fluctuation difference of the water level data is arranged according to the arrangement order of the water level data in the water level sequence at the current sampling moment, so as to obtain the local fluctuation sequence at the current sampling moment.

[0059] The water level variation index at the current sampling moment is obtained according to the difference between the fluctuation differences of the water level data in the local fluctuation sequence at the current sampling moment.

[0060] Preferably, as an embodiment of the present application, the product of the standard deviation of all fluctuation differences in the local fluctuation sequence at the current sampling moment and the fluctuation difference of the water level data at the current sampling moment is recorded as the water level change index at the current sampling moment.

[0061] Among them, the calculation formula of the water level change index at the current sampling time is:

[0062]

[0063] In the formula, Indicates the water level change index at the current sampling moment; Represents the standard deviation of all fluctuation differences in the local fluctuation sequence at the current sampling moment; Indicates the fluctuation difference of water level data at the current sampling moment.

[0064] The larger the standard deviation of all fluctuation differences in the local fluctuation sequence at the current sampling moment, and the larger the fluctuation difference of the water level data at the current sampling moment, the larger the fluctuation factor at the current sampling moment. At this time, the greater the fluctuation degree of the water level data at the current sampling moment and the previous day, the greater the possibility that the water level data collected in the underground closed fire water tank is affected by other environmental factors.

[0065] According to the water level change index and the fluctuation factor at the current sampling moment, the potential water level impact factor at the current sampling moment is obtained. The potential water level impact factor at the current sampling moment is negatively correlated with the water level change index at the current sampling moment and positively correlated with the fluctuation factor at the current sampling moment.

[0066] Preferably, as an embodiment of the present application, the ratio of the fluctuation factor at the current sampling moment to the water level change index is recorded as the potential water level influencing factor at the current sampling moment.

[0067] Among them, the calculation formula of the potential water level influencing factor at the current sampling time is:

[0068]

[0069] In the formula, Indicates the potential water level influencing factor at the current sampling time; Indicates the fluctuation factor at the current sampling moment; Indicates the water level change index at the current sampling moment.

[0070] The potential water level impact factor at the current sampling moment comprehensively analyzes the degree of change in the pressure data and water level data of the underground closed fire water pool, reflecting the possibility of leakage in the underground closed fire water pool at the current sampling moment. The potential water level impact factor at the current sampling moment is an evaluation of the degree of influence of all influencing factors on the accuracy of the water level data collected at the current sampling moment. The larger the fluctuation factor at the current sampling moment and the smaller the water level change index at the current sampling moment, the greater the potential water level impact factor at the current sampling moment. At this time, the greater the volatility of the pressure data at the current sampling moment and the previous day, and the less likely the collected water level data is to be affected by other environmental factors, the greater the possibility of leakage in the underground closed fire water pool.

[0071] At this point, the potential water level influencing factors at the current sampling time are obtained. The flowchart for obtaining the potential water level influencing factors is as follows: Figure 2 shown.

[0072] Step S004: adjust the water level data at the current sampling moment according to the potential water level influencing factor at the current sampling moment to obtain the liquid level measurement result of the fire water tank.

[0073] Kalman filtering is a recursive algorithm. The Kalman gain in Kalman filtering can adjust the predicted state during the observation update process, so that the Kalman filter can update the state estimation in time according to the collected data, making the state estimation result obtained by the Kalman filter closer to the real state. Therefore, the Kalman filter algorithm is used to estimate the water level data of the underground closed fire water pool, calibrate the collected water level data, and improve the liquid level measurement accuracy of the underground closed fire water pool.

[0074] The Kalman filter algorithm is used to process the water level data at the current collection time to obtain the Kalman gain at the current collection time. The Kalman gain at the current collection time is the ratio of the covariance of the prediction error to the covariance of the observation noise, which determines the degree of influence of the observation data on the prediction state. The observation data here is the water level data at the current collection time.

[0075] According to the potential water level influencing factor and the Kalman gain at the current sampling moment, the adjusted Kalman gain at the current sampling moment is obtained.

[0076] Preferably, as an embodiment of the present application, the product of the normalized value of the potential water level influencing factor at the current sampling moment, the Kalman gain at the current acquisition moment, and the number 2 is recorded as the adjusted Kalman gain at the current sampling moment.

[0077] Among them, the calculation formula of the adjusted Kalman gain at the current sampling time is:

[0078]

[0079] In the formula, Represents the adjusted Kalman gain at the current sampling moment; Represents the Kalman gain at the current sampling moment; Represents the sigmoid function, which is a normalization function; Indicates the potential water level influencing factor at the current sampling moment.

[0080] The adjusted Kalman gain at the current sampling moment is used as the value of the Kalman gain, and the Kalman filter algorithm is used to process the water level data at the current collection moment to obtain the optimal estimate, and the value of the optimal estimate is used as the liquid level measurement result of the underground closed fire water tank.

[0081] At this point, the liquid level measurement results of the fire water tank are obtained.

[0082] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for measuring the liquid level of a fire water tank, characterized in that: The method comprises the following steps: Collect water level data and pressure data at the current sampling time and at each sampling time in the previous local time period to obtain the water level sequence and pressure sequence at the current sampling time; Obtain the first-order difference sequence of the pressure sequence at the current sampling moment, record the ratio of the number of data not equal to 0 in the first-order difference sequence to the number of all data contained in the first-order difference sequence as the fluctuation data ratio at the current sampling moment; record the data segment consisting of consecutive adjacent data not equal to 0 in the first-order difference sequence as the continuous fluctuation data segment, record the average of the number of data contained in all continuous fluctuation data segments in the first-order difference sequence as the continuous fluctuation length; record the number of all continuous fluctuation data segments in the first-order difference sequence as the continuous fluctuation number; record the product of the fluctuation data ratio, the continuous fluctuation number and the continuous fluctuation length at the current sampling moment as the change continuity at the current sampling moment; Perform straight line fitting on the pressure sequence at the current sampling moment, obtain the slope of the fitted straight line, and record the absolute value of the slope of the fitted straight line as the change trend at the current sampling moment; record the product of the change trend at the current sampling moment and the change duration as the fluctuation factor at the current sampling moment; Any water level data in the water level sequence at the current sampling moment is recorded as the target water level data, and the range of a preset number of water level data adjacent to the target water level data is recorded as the fluctuation difference of the target water level data; the product of the standard deviation of all fluctuation differences in the local fluctuation sequence at the current sampling moment and the fluctuation difference of the water level data at the current sampling moment is recorded as the water level change index at the current sampling moment; the ratio of the fluctuation factor at the current sampling moment to the water level change index is recorded as the potential water level influencing factor at the current sampling moment; The water level data at the current sampling time is adjusted according to the potential water level influencing factors at the current sampling time to obtain the liquid level measurement result of the fire water tank; The method of adjusting the water level data at the current sampling time according to the potential water level influencing factor at the current sampling time to obtain the liquid level measurement result of the fire water tank includes the following specific methods: The water level data at the current acquisition moment is processed using the Kalman filter algorithm to obtain the Kalman gain at the current acquisition moment, and the adjusted Kalman gain at the current sampling moment is obtained according to the potential water level influencing factor and the Kalman gain at the current sampling moment; The adjusted Kalman gain at the current sampling moment is used as the value of the Kalman gain, and the Kalman filter algorithm is used to process the water level data at the current acquisition moment to obtain the optimal estimate, and the value of the optimal estimate is used as the liquid level measurement result of the underground closed fire water tank; The specific method for obtaining the adjusted Kalman gain at the current sampling moment is: The product of the normalized value of the potential water level influencing factor at the current sampling moment, the Kalman gain at the current acquisition moment, and the number 2 is recorded as the adjusted Kalman gain at the current sampling moment.

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