A method for gas safety management by learning users' gas usage habits

Abstract

The present invention provides a method for gas safety management by learning user gas usage habits. The specific steps are: S1: Install a smart gas meter on the user's gas pipeline, which reads the flow rate at regular intervals; S2: Establish multiple flow management intervals within the smart gas meter's range, with the maximum value of each flow management interval being 1.2 times the meter's full scale; S3: Based on the user's gas usage habits, the smart gas meter learns autonomously or learns in the cloud and then transmits the learning to the smart gas meter, obtaining a threshold a for the number of flow rate counts in each flow management interval; S4: The smart gas meter monitors real-time flow. If the number of times the real-time flow falls within a flow management interval exceeds a, the flow is determined to be abnormal, the valve is closed, and gas supply is stopped. This method solves the technical problem that existing residential gas leak monitoring requires high modification costs and has limited reliability. The present invention can be widely applied in the field of gas safety control.

Description

Technical Field

[0001] The present invention relates to a gas safety management method, and in particular to a gas safety management method by learning users' gas usage habits. Background Art

[0002] Gas is now widely used in our daily lives. However, while it is convenient to use, it is also flammable and explosive, and leaks can cause immeasurable damage. Therefore, timely and effective monitoring of gas leaks is essential. Existing leak monitoring methods require significant system modifications, resulting in high upgrade costs and limited reliability. Summary of the Invention

[0003] In response to the technical problems that existing residential gas leakage monitoring requires high modification costs and has reliability that needs to be improved, the present invention provides a method for gas safety management by learning users' gas usage habits, which has low modification costs and high reliability.

[0004] To this end, the technical solution of the present invention is a method for gas safety management by learning users' gas usage habits, the specific steps of which are:

[0005] S1: Install a smart gas meter on the user's gas pipeline. The smart gas meter reads the flow value every certain time interval T.

[0006] S2: Establish multiple flow management intervals within the range of the smart gas meter, with the maximum value of the flow management interval being 1.2 times the full scale of the meter;

[0007] S3: Based on the user's gas usage habits, the threshold a for the number of flow value counts in each flow management interval is determined by the smart gas meter through autonomous learning or cloud learning and then sent to the smart gas meter;

[0008] S4: The real-time flow is monitored through the smart gas meter. When the number of times the real-time flow falls into a certain flow management interval is greater than a, it is determined that the gas usage status is abnormal, the valve is closed, and the gas supply is stopped.

[0009] Preferably, the specific steps of obtaining the flow value counting threshold a of each flow management interval by autonomous learning of the smart gas meter are:

[0010] S1.1: Read the real-time flow rate through the smart gas meter. If the flow rate value is zero, discard the record. If the flow rate value is not zero, record the read flow rate value as q1, use q1 as the starting point Q0, and record the number of q1 as 1. After the interval T, read the flow rate value as q2;

[0011] S1.2: Set the flow rate change rate threshold to A. If |q2-q1| / q1≤A, the flow rate is considered unchanged, and the number of times q1 is recorded plus 1. If |q2-q1| / q1>A, the flow rate is considered changed, and the number of times q1 is stored. q2 is used as the starting point Q0 again, and the flow value q3 is read after an interval T. If |q3-q2| / q2≤A, the flow rate is considered unchanged, and the number of times q2 is recorded plus 1. If |q3-q2| / q2>A, the flow rate is considered changed, and the number of times q2 is stored, and so on. A is set according to the metering accuracy of the smart gas meter.

[0012] S1.3: If the flow rate value after the starting point is zero, the number of times the starting point is counted is stored, and the flow rate value is obtained at intervals of time T until a non-zero flow rate value is obtained as the new starting point Q0; repeat S1.2;

[0013] S1.4: After obtaining a Q0, first observe which flow management interval Q0 belongs to in the smart gas meter. The corresponding count of Q0 is the count of that interval. Repeat this step for each subsequent Q0 and Q0 count. If the count of Q0 obtained later is greater than the count of Q0 obtained earlier in the same interval, replace the previous count with the new count, and always maintain the maximum count of Q0 in the interval.

[0014] S1.5: When the Q0 count of a certain interval has iterated a certain number of times, or when the number of Q0s obtained reaches the set value, the iteration is stopped, and the last count is multiplied by the safety factor as the count threshold a for the interval; if no Q0 traffic management interval is obtained, a=0.

[0015] Preferably, a communication module is installed on the smart gas meter, and the smart gas meter is connected to the cloud through the communication module. The smart gas meter reads the flow value once every interval T, stores the read flow value, and uploads it to the cloud after storing a certain number of flow values. The cloud processes the data, generates a counting threshold a, and sends it to the meter end.

[0016] Preferably, the cloud processes the data to generate a count threshold a for each traffic management interval. The specific steps are:

[0017] S2.1: The cloud reads the flow data uploaded by the smart gas meter in sequence. If the read flow value is zero, the record is discarded. If the flow value is not zero, the read flow value is recorded as q1, with q1 as the starting point Q0, and the number of q1 is recorded as 1. The next flow value is read as q2;

[0018] S2.2: Set the flow rate change rate threshold to A. If |q2-q1| / q1≤A, the flow rate is considered unchanged, and the number of q1 counts plus 1 is recorded. If |q2-q1| / q1>A, the flow rate is considered changed, and the number of counts of q1 is stored. Using q2 as the starting point Q0, the next flow rate value q3 is read. If |q3-q2| / q2≤A, the flow rate is considered unchanged, and the number of counts of q2 is recorded plus 1. If |q3-q2| / q2>A, the flow rate is considered changed, and the number of counts of q2 is stored, and so on. A is set according to the metering accuracy of the smart gas meter.

[0019] S2.3: If the next flow value after the starting point is detected is zero, the count number of the starting point is stored and the next flow value is obtained until a non-zero flow value is obtained as the new starting point Q0; repeat S2.2;

[0020] S2.4: Establish the same flow management intervals as those on the smart gas meter side on the cloud. When a Q0 is obtained, first observe which flow management interval Q0 belongs to. The corresponding count count of Q0 is the count count of that interval. Repeat this step for each subsequent Q0 and Q0 count count. If the count count of the later obtained Q0 is greater than the earlier count count within the same interval, replace the original count count with the new count count to always maintain the maximum count count of Q0 within the interval.

[0021] S2.5: When the Q0 count of a certain interval has iterated a certain number of times, or when the number of Q0s obtained reaches the set value, the iteration is stopped, and the last count is multiplied by the safety factor as the count threshold a for the traffic management interval; if no Q0 traffic management interval is obtained, a=0.

[0022] The beneficial effects of the present invention are:

[0023] (1) By building an intelligent algorithm on the smart gas meter side, summarizing the gas usage patterns of users, and using the obtained gas usage patterns to manage user gas usage, gas accidents can be effectively avoided;

[0024] (2) If you forget to turn off the fire, the number of times will exceed the threshold a, that is, the gas supply can be automatically turned off after a certain delay to avoid dry burning, which is good news for amnesiacs;

[0025] (3) Constant flow is an important feature of leakage. By controlling the number of times Q0 is counted to control the total gas volume of continuous constant flow, and controlling the total gas volume of constant flow within the explosion limit, explosion accidents can be effectively avoided. DETAILED DESCRIPTION

[0026] The present invention will be further described below with reference to the embodiments.

[0027] Because residential gas users have relatively stable gas usage habits, in addition to the relatively fixed power of their gas-using equipment, summarizing their usage patterns and using this "knowledge" to manage their usage can effectively prevent gas accidents. This can be achieved by building intelligent algorithms within smart gas meters or by generating data in the cloud and then distributing it to smart gas meters.

[0028] The method of gas safety management by learning users' gas usage habits is as follows:

[0029] S1: Install a smart gas meter on the user's gas pipeline. The smart gas meter reads the flow value every certain time interval T.

[0030] S2: Establish multiple flow management intervals within the range of the smart gas meter, with the maximum value of the flow management interval being 1.2 times the full scale of the meter;

[0031] S3: Based on the user's gas usage habits, the threshold a for the number of flow value counts in each flow management interval is obtained through autonomous learning by the smart gas meter or after learning in the cloud and then sent to the smart gas meter;

[0032] S4: The real-time flow is monitored through the smart gas meter. When the number of times the real-time flow falls into a certain flow management interval is greater than a, it is determined that the gas usage status is abnormal, the valve is closed, and the gas supply is stopped.

[0033] Example 1

[0034] By building an intelligent algorithm in the smart gas meter, the user's gas usage pattern is generated, specifically:

[0035] (1) During the user's gas use, the flow value is read once at a certain interval of time T (for example, 90 seconds). If the read flow value is zero, the record is discarded; if the read flow value is not zero, the flow value is recorded as the starting point q1, and the count number for q1 is 1; let the flow value read next time be q2, if |q2-q1| / q1≤3% (3% is a parameter, which can be set according to the metering accuracy), it is considered that the flow has not changed, that is, the user or the gas-using equipment has not adjusted the gas power, at this time, the count number for q1 is increased by one; if |q2-q1| / q1>3%, it is considered that the flow has changed, that is, the user or the gas-using equipment has adjusted the gas power, at this time, the count number of q1 is stored, and q2 is used as the new starting point to continue monitoring the next flow value, and the count number is restarted according to the above rules; during the flow value monitoring process, if the read flow value is zero, the count number of the previous flow value is stored, and the next starting point is found, and the above steps are restarted, and so on;

[0036] (2) Establish multiple flow management intervals for the starting point of the flow value, such as [0.036, 0.1), [0.1, 0.2), [0.2, 0.3), [0.3, 0.4), [0.4, 0.5) ... and so on, which can be equally spaced or unequally spaced, and established up to 1.2 times the full scale of the meter. After obtaining the number of counts of the starting point of a flow value, first check which flow management interval the flow value belongs to, and record the obtained number of counts as the number of counts of the flow management interval. Repeat the above process for each subsequent flow value starting point and the number of counts of the starting point. If the obtained flow value starting point belongs to a certain interval, and the number of counts of the flow value is greater than the number of counts of the starting point already stored in the interval, then replace the original number of counts with the new number of counts, that is, always save the maximum number of counts of the starting point;

[0037] (3) When the number of times the flow value starting point of a certain interval is iterated reaches a certain number (for example, 100 times, which can be set according to actual conditions), or when the number of flow value starting points obtained reaches a set value (for example, 300), the iteration is stopped, and the number of flow value starting points saved is increased by a certain margin (for example, 10%) as the counting threshold of the flow value in the flow management interval, which is set to a. In the interval where no flow starting point appears, that is, the flow is always zero during the learning process, then a = 0;

[0038] (4) During gas use, if the number of times the starting point falls into the flow management interval is greater than a, the valve will be closed and the gas supply will be stopped to ensure the safety of the user's gas use.

[0039] Example 2

[0040] A communication module is added to the smart gas meter. The calculation method in Example 1 can also be transplanted to the cloud. The counting threshold is obtained in the cloud and then sent to the smart gas meter. Specifically:

[0041] (1) The smart gas meter reads the flow value every certain time interval T (e.g., 90 seconds), stores the read flow value, and uploads a certain number of values, e.g., 100, to the cloud;

[0042] (2) Cloud data processing method:

[0043] a. If the flow value is zero, discard the record; if the flow value is not zero, record the flow value q1 as the starting point, and count the number of times for q1 as 1; set the next flow value to q2, if |q2-q1| / q1≤3% (3% is a parameter, which can be set according to the metering accuracy), it is considered that the flow has not changed, that is, the user or gas-using equipment has not adjusted the gas power. At this time, q1 is still the starting point, and the count of q1 is increased by one; if |q2-q1| / q1>3%, it is considered that the flow has changed, that is, the user or gas-using equipment has adjusted the gas power. At this time, store the count of q1, and use q2 as the new starting point, continue to monitor the next flow value, and restart the count according to the above rules; during the flow value monitoring process, if the flow value is read as zero, store the count of the previous flow value, find the next starting point, and restart the above steps, and so on;

[0044] b. Establish multiple traffic management intervals for the starting point of the flow value in the cloud, such as [0.036, 0.1), [0.1, 0.2), [0.2, 0.3), [0.3, 0.4), [0.4, 0.5)... and so on. The intervals can be equal or unequal, and they can be established up to 1.2 times the full scale of the meter. After obtaining the number of counts of the starting point of a flow value, first check which interval the flow value of the starting point belongs to, and record the obtained number of counts as the number of counts of the starting point in the interval. Repeat the above process for each subsequent flow value starting point and the number of counts of the starting point. If the obtained starting point flow value belongs to a certain interval, and the number of counts of the starting point is greater than the number of counts of the starting point already stored in the interval, then the new number of counts will replace the original number of counts, that is, the maximum number of counts of the starting point of the flow value in the interval is always saved;

[0045] c. When the number of times the starting point counts of a certain flow management interval has been iterated reaches a certain number (for example, 100 times, which can be set according to actual conditions), or when the number of flow value starting points obtained reaches a set value (for example, 300), the iteration is stopped, and the saved starting point counts are increased by a certain margin (for example, by 10%) as the count threshold of the starting point in the interval, which is set to a. For intervals without flow starting points, that is, when the flow value is always zero during the learning process, a = 0;

[0046] d. Establish a flow management interval on the meter side for the starting point of the flow value, which is the same as that on the cloud side. Send the interval counting threshold a obtained on the cloud side to the meter side as the counting threshold for the starting point of the flow value in this management interval. During the gas use process, if the meter side finds that the counting number of the starting point falling into this interval is greater than a, it will close the valve and stop gas supply to ensure the safety of gas use for users.

[0047] By building an intelligent algorithm on the smart gas meter end, summarizing users' gas usage patterns, and using the obtained gas usage patterns to manage users' gas usage, gas accidents can be effectively avoided. If you forget to turn off the fire, the number of counts will exceed the threshold a, that is, the gas supply can be automatically shut off after a certain delay to avoid dry burning, which is good news for amnesiacs. Constant flow is a key feature of leakage. By controlling the number of counts of Q0 to control the total gas volume of continuous constant flow, and keeping the total gas volume of constant flow within the combustion and explosion limit, combustion and explosion accidents can be effectively avoided.

[0048] There are two main types of gas metering instruments used by residential users in my country: diaphragm gas meters and ultrasonic gas meters. The method of the present invention is applicable to smart gas meters. Diaphragm gas meters can be upgraded to smart gas meters through intelligent transformation. Ultrasonic meters themselves are smart gas meters. Therefore, when this solution is applied to the transformation of existing equipment, it will not incur large transformation costs and is easy to promote.

[0049] However, the above description is merely a specific embodiment of the present invention and should not be used to limit the scope of implementation of the present invention. Therefore, the replacement of equivalent components, or equivalent changes and modifications made according to the scope of protection of the present invention should still fall within the scope covered by the claims of the present invention.

Claims

1. A method for gas safety management by learning users' gas usage habits, characterized by: The specific steps are: S1: Install a smart gas meter on the user's gas pipeline. The smart gas meter reads the flow value every certain time interval T. S2: Establish multiple flow management intervals within the range of the smart gas meter, with the maximum value of the flow management interval being 1.2 times the full scale of the meter; S3: Based on the user's gas usage habits, the smart gas meter automatically learns to obtain the threshold a for the number of flow rate counts in each flow management interval; S4: The real-time flow rate is monitored through the smart gas meter. If the real-time flow rate falls into a certain flow management interval for more than a times, it is determined that the gas usage status is abnormal, and the valve is closed to stop the gas supply. The specific steps for obtaining the flow value counting threshold a for each flow management interval through autonomous learning of the smart gas meter are as follows: S3.1: Read the real-time flow rate from the smart gas meter. If the flow rate value is zero, discard the record. If the flow rate value is not zero, record the read flow rate value as q1, using q1 as the starting point Q0, and record the number of q1 as 1. After an interval T, read the flow rate value as q2. S3.2: Set the flow rate change threshold to A. If / ≤A, the flow rate is considered to have not changed, and the number of q1 is recorded plus 1; if / >A, it is considered that the flow rate has changed, the count of q1 is stored, q2 is used as the starting point Q0 again, and the flow rate value q3 is read after the interval T. If / 2≤A, the flow rate is considered to have not changed, and the number of times q2 is recorded plus 1; if / If 2>A, the flow rate is considered to have changed, and the count of q2 is stored, and so on; where A is set according to the measurement accuracy of the smart gas meter; S3.3: If the flow rate value after the starting point is zero, the number of times the starting point is counted is stored, and the flow rate value is obtained at intervals of time T until a non-zero flow rate value is obtained as the new starting point Q0; repeat S3.2; S3.4: After obtaining a Q0, first observe which flow management interval Q0 belongs to of the smart gas meter. The corresponding count of Q0 is the count of that interval. Repeat this step for each subsequent Q0 and Q0 count. If the count of Q0 obtained later is greater than the count of Q0 obtained earlier within the same interval, replace the previous count with the new count, and always maintain the maximum count of Q0 within the interval. S3.5: When the Q0 count of a certain interval has iterated a certain number of times, or when the number of Q0s obtained reaches the set value, the iteration is stopped, and the last count is multiplied by the safety factor as the count threshold a for the interval; if the traffic management interval of Q0 is not obtained, a=0.

2. A method for gas safety management by learning users' gas usage habits, characterized by: The specific steps are: S1: Install a smart gas meter on the user's gas pipeline. The smart gas meter reads the flow value every certain time interval T. S2: Establish multiple flow management intervals within the range of the smart gas meter, with the maximum value of the flow management interval being 1.2 times the full scale of the meter; S3: Based on the user's gas usage habits, the smart gas meter cloud learns and sends the result to the smart gas meter to obtain the threshold a for the number of flow value counts in each flow management interval; S4: The real-time flow rate is monitored through the smart gas meter. If the real-time flow rate falls into a certain flow management interval for more than a times, it is determined that the gas usage status is abnormal, and the valve is closed to stop the gas supply. A communication module is installed on the smart gas meter, and the smart gas meter is connected to the cloud through the communication module. The smart gas meter reads the flow value once every interval T, stores the read flow value, and uploads it to the cloud after a certain number of flow values ​​are stored. The cloud processes the data, generates a counting threshold a, and sends it to the meter end; The cloud processes the data and generates the flow value counting threshold a for each flow management interval. The specific steps are as follows: S3.1: The cloud reads the flow data uploaded by the smart gas meter in sequence. If the read flow value is zero, the record is discarded. If the flow value is not zero, the read flow value is recorded as q1, with q1 as the starting point Q0, and the number of q1 is recorded as 1. The next flow value is read as q2; S3.2: Set the flow rate change threshold to A. If / ≤A, the flow rate is considered to have not changed, and the number of q1 is recorded plus 1; if / > A, the flow rate is considered to have changed, the count of q1 is stored, q2 is used as the starting point Q0 again, and the next flow rate value q3 is read. / 2≤A, the flow rate is considered to have not changed, and the number of times q2 is recorded plus 1; if / If 2>A, the flow rate is considered to have changed, and the count of q2 is stored, and so on; where A is set according to the measurement accuracy of the smart gas meter; S3.3: If the next flow value after the starting point is detected is zero, the count number of the starting point is stored and the next flow value is obtained until a non-zero flow value is obtained as the new starting point Q0; repeat S3.2; S3.4: Establish the same flow management intervals on the cloud as those on the smart gas meter. When a Q0 is obtained, first observe which flow management interval Q0 belongs to. The corresponding count count of Q0 is the count count of that interval. Repeat this step for each subsequent Q0 and Q0 count count. If the count count of a later Q0 is greater than the count count of the earlier one within the same interval, replace the previous count with the new count count to always maintain the maximum count count of Q0 within the interval. S3.5: When the Q0 count of a certain interval has iterated a certain number of times, or when the number of Q0s obtained reaches the set value, the iteration is stopped, and the last count is multiplied by the safety factor as the count threshold a for the traffic management interval; if no Q0 traffic management interval is obtained, a=0.