A heat management system

Abstract

The application relates to the technical field of heat supply management, and discloses a heat supply management system, a preliminary audit module performs audit on a network access application and executes a network access operation; a curve fitting module acquires real-time heat supply data of a current time node and determines a heat supply data fitting curve; a first calculation module extracts a maximum fitting slope and calculates a heat supply anomaly coefficient; a second calculation module collects heat supply flow data and heat supply temperature data in a preset time range before the current time node and calculates a historical heat supply response coefficient; a data optimization module optimizes the heat supply anomaly coefficient based on the historical heat supply response coefficient to obtain a target heat supply anomaly coefficient; an acceptance signing module judges whether abnormal operation exists according to the target heat supply anomaly coefficient, if not, performs acceptance work, signs a formal contract with a user, and predicts an abnormal state of a heat supply system in advance, so that energy consumption and failure probability are reduced, the intelligence of heat supply acceptance management is ensured, and the reliability of network access process management is ensured.

Description

Technical Field

[0001] This invention relates to the field of heating management technology, and more specifically, to a heating management system. Background Technology

[0002] The heating system consists of a heat source, a heat circulation system, and heat dissipation equipment. It heats low-temperature coal and delivers the heat indoors, where it is released through the heat dissipation equipment to maintain a warm indoor environment. This system is particularly important in cold regions, ensuring a comfortable living and working environment for residents.

[0003] Traditional heating acceptance management relies on manual monitoring and experience-based judgment, lacking real-time and scientific rigor, leading to frequent heating failures and significant energy waste. This approach struggles to handle large-scale, high-dimensional data, exhibiting clear technical bottlenecks. Furthermore, existing heating monitoring and control technologies often focus on optimizing single aspects, lacking comprehensive evaluation of overall performance and fault analysis. Traditional methods have limitations in data processing and analysis, making it difficult to effectively address complex and variable heating environments, ensuring efficient acceptance procedures, and guaranteeing service quality meets standards. Summary of the Invention

[0004] This invention provides a heating management system that, through real-time monitoring, data analysis, and intelligent diagnosis, can predict abnormal states of the heating system in advance, ensuring the intelligence of heating acceptance management, guaranteeing efficient acceptance work, and ensuring that service quality meets standard requirements.

[0005] To achieve the above objectives, the present invention provides a heating management system, comprising:

[0006] The preliminary review module is used to receive network access applications from different types of users, review the network access applications according to preset rules, and perform network access operations when the user passes the review.

[0007] The curve fitting module is used to obtain the real-time heating data corresponding to the heating system at the current time point after performing the network access operation, determine the standard heating data corresponding to the real-time heating data, and determine the heating data fitting curve based on the real-time heating data and the standard heating data.

[0008] The first calculation module is used to analyze the fitting curve of the heating data, extract the maximum fitting slope from the fitting curve, and calculate the heating anomaly coefficient of the heating system based on the maximum fitting slope.

[0009] The second calculation module is used to collect the heating flow rate data and heating temperature data of the heating system within a preset time range before the current time node, and calculate the historical heating response coefficient of the heating system based on the heating flow rate data and heating temperature data.

[0010] The data optimization module is used to set optimization coefficients based on the historical heating response coefficients, and to optimize the heating anomaly coefficients based on the optimization coefficients to obtain the target heating anomaly coefficient of the heating system.

[0011] The acceptance and signing module is used to determine whether the heating system is operating abnormally based on the target heating anomaly coefficient and the preset target heating anomaly coefficient. If not, the acceptance work is carried out and a formal contract is signed with the user.

[0012] Furthermore, the curve fitting module is used for:

[0013] The curve fitting module is used to calculate the difference between the real-time heating data and the standard heating data, and to construct a heating data difference sequence.

[0014] The curve fitting module is used to determine the allowable heating data error range corresponding to the heating system, wherein the allowable heating data error range includes a first allowable heating data error and a second allowable heating data error;

[0015] The curve fitting module is used to remove all heating data differences in the heating data difference sequence that are within the allowable heating data error range based on the allowable heating data error range, and to obtain a second heating data difference sequence.

[0016] The curve fitting module is used to fit the heating data difference within the second heating data difference sequence to obtain the heating data fitting curve.

[0017] Furthermore, the first computing module is used for:

[0018] The first calculation module is used to construct a first data interval based on the first allowable heating data error and the standard data error;

[0019] The first calculation module is used to construct a second data range based on the second allowable heating data error and the standard data error;

[0020] The first calculation module is used to analyze the removed heating data differences and count the number of first heating data differences that fall into the first data interval.

[0021] The first calculation module is used to count the number of second heating data differences that fall into the second data interval;

[0022] The first calculation module is used to calculate the heating anomaly coefficient of the heating system based on the number of differences between the first heating data and the number of differences between the second heating data.

[0023] Furthermore, the first computing module is used for:

[0024] The first calculation module is used to calculate the heating anomaly coefficient of the heating system according to the following formula:

[0025] ;

[0026] Where a1 is the heating anomaly coefficient of the heating system, n is the number of heating data differences removed, and b i Let be the i-th removed heating data difference, e1 be the first allowable heating data error, e2 be the second allowable heating data error, f1 = n1 / (n1 + n2), n1 be the number of the first heating data difference, n2 be the number of the second heating data difference, f2 = n2 / (n1 + n2), g be the adjustment coefficient of the heating anomaly coefficient, and h be the maximum fitting slope.

[0027] Furthermore, the first computing module is used for:

[0028] The first calculation module is used to determine the adjustment coefficient g of the heating anomaly coefficient according to the following steps;

[0029] The first calculation module is used to count the first number n3 of heating data differences on the heating data fitting curve;

[0030] The first calculation module is used to preset a first preset adjustment coefficient, a second preset adjustment coefficient, and a third preset adjustment coefficient;

[0031] The first calculation module is used to select the first preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when n3 / (n1+n2) < 1;

[0032] The first calculation module is used to select the second preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when 1≤n3 / (n1+n2)<1.2;

[0033] The first calculation module is used to select the third preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when 1.2≤n3 / (n1+n2).

[0034] Furthermore, the second computing module is used for:

[0035] The second calculation module is used to divide the preset time range into multiple time node intervals, and determine the first heating flow data and the second heating flow data for each time node interval. The first heating flow data is the heating flow data corresponding to the end time of each time node interval, and the second heating flow data is the difference between the heating flow data corresponding to the start time and the end time of each time node interval.

[0036] The second calculation module is used to determine the first historical heating response coefficient of the heating system based on the first heating flow data and the second heating flow data, wherein the first historical heating response coefficient is the product of the first heating flow data and the second heating flow data;

[0037] The second calculation module is used to determine the first heating temperature data and the second heating temperature data for each time node interval. The first heating temperature data is the heating temperature data corresponding to the end time of each time node interval, and the second heating temperature data is the difference between the heating temperature data corresponding to the start time and the end time of each time node interval.

[0038] The second calculation module is used to determine the second historical heating response coefficient of the heating system based on the first heating temperature data and the second heating temperature data, wherein the second historical heating response coefficient is the product of the first heating temperature data and the second heating temperature data;

[0039] The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to each time node interval based on the first historical heating response coefficient and the second historical heating response coefficient;

[0040] The second calculation module is used to calculate the historical heating response coefficient of the heating system based on all comprehensive historical heating response coefficients.

[0041] Furthermore, the second computing module is used for:

[0042] The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to the time node interval according to the following formula:

[0043] ;

[0044] Where k is the comprehensive historical heating response coefficient, p1 is the first calculation coefficient, q1 is the first historical heating response coefficient, q2 is the second historical heating response coefficient, p2 is the second calculation coefficient, p1 < 0, p2 < 0.

[0045] Furthermore, the second computing module is used for:

[0046] The second calculation module is used to extract the same comprehensive historical heating response coefficient from all comprehensive historical heating response coefficients and obtain multiple comprehensive historical heating response coefficient sequences;

[0047] The second calculation module is used to count the number of the first comprehensive historical heating response coefficient sequences in the comprehensive historical heating response coefficient sequence;

[0048] The second calculation module is used to extract a comprehensive historical heating response coefficient from all comprehensive historical heating response coefficient sequences, and to calculate the sum of the first comprehensive historical heating response coefficients;

[0049] The second calculation module is used to obtain a preset comprehensive historical heating response coefficient, remove all comprehensive historical heating response coefficient sequences that are less than the preset comprehensive historical heating response coefficient, and count the number of second comprehensive historical heating response coefficient sequences of the remaining comprehensive historical heating response coefficient sequences.

[0050] The second calculation module is used to extract one comprehensive historical heating response coefficient from the remaining comprehensive historical heating response coefficient sequence, and to calculate the second comprehensive historical heating response coefficient and its value.

[0051] The second calculation module is used to calculate the historical heating response coefficient of the heating system based on the number of the first comprehensive historical heating response coefficient sequence, the number of the second comprehensive historical heating response coefficient sequence, the sum of the first comprehensive historical heating response coefficient and the sum of the second comprehensive historical heating response coefficient.

[0052] Furthermore, the data optimization module is used for:

[0053] The first preset historical heating response coefficient and the second preset historical heating response coefficient are set in advance;

[0054] Pre-set the first preset optimization coefficient, the second preset optimization coefficient, and the third preset optimization coefficient;

[0055] When the historical heating response coefficient is less than the first preset historical heating response coefficient, the product of the first preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system.

[0056] When the historical heating response coefficient is greater than or equal to the first preset historical heating response coefficient and less than the second preset historical heating response coefficient, the product of the second preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system.

[0057] When the historical heating response coefficient is greater than or equal to the second preset historical heating response coefficient, the product of the third preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system.

[0058] Furthermore, the acceptance and signing module is used for:

[0059] The acceptance and signing module is used to determine that the heating system does not have abnormal operation when the target heating anomaly coefficient is less than the preset target heating anomaly coefficient.

[0060] The acceptance and signing module is used to determine that the heating system is operating abnormally when the target heating anomaly coefficient is greater than or equal to the preset target heating anomaly coefficient.

[0061] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0062] This invention discloses a heating management system. A preliminary review module reviews network access applications and executes the network access operation. A curve fitting module acquires real-time heating data at the current time point and determines the heating data fitting curve. A first calculation module extracts the maximum fitting slope and calculates the heating anomaly coefficient. A second calculation module collects heating flow and temperature data within a preset time range before the current time point and calculates the historical heating response coefficient. A data optimization module optimizes the heating anomaly coefficient based on the historical heating response coefficient to obtain the target heating anomaly coefficient. An acceptance and signing module determines whether there is abnormal operation based on the target heating anomaly coefficient. If not, acceptance work is carried out, and a formal contract is signed with the user. This system predicts abnormal states of the heating system in advance, reduces energy consumption and the probability of failure, ensures the intelligence of heating acceptance management, and guarantees the reliability of the network access process management. Attached Figure Description

[0063] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0064] Figure 1 A schematic diagram of a heating management system according to an embodiment of the present invention is shown. Detailed Implementation

[0065] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0066] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0067] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0068] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0069] The following is a description of preferred embodiments of the present invention in conjunction with the accompanying drawings.

[0070] like Figure 1 As shown, an embodiment of the present invention discloses a heating management system, comprising:

[0071] The preliminary review module is used to receive network access applications from different types of users, review the network access applications according to preset rules, and perform network access operations when the user passes the review.

[0072] The curve fitting module is used to obtain the real-time heating data corresponding to the heating system at the current time point after performing the network access operation, determine the standard heating data corresponding to the real-time heating data, and determine the heating data fitting curve based on the real-time heating data and the standard heating data.

[0073] The first calculation module is used to analyze the fitting curve of the heating data, extract the maximum fitting slope from the fitting curve, and calculate the heating anomaly coefficient of the heating system based on the maximum fitting slope.

[0074] The second calculation module is used to collect the heating flow rate data and heating temperature data of the heating system within a preset time range before the current time node, and calculate the historical heating response coefficient of the heating system based on the heating flow rate data and heating temperature data.

[0075] The data optimization module is used to set optimization coefficients based on the historical heating response coefficients, and to optimize the heating anomaly coefficients based on the optimization coefficients to obtain the target heating anomaly coefficient of the heating system.

[0076] The acceptance and signing module is used to determine whether the heating system is operating abnormally based on the target heating anomaly coefficient and the preset target heating anomaly coefficient. If not, the acceptance work is carried out and a formal contract is signed with the user.

[0077] In this embodiment, network access applications are received from different types of users (including residential communities, hospitals, factories, and small users).

[0078] In this embodiment, a contact application service can be provided to small users through a mini-program or webpage.

[0079] In this embodiment, the presence of abnormal operation in the heating system is determined based on the target heating anomaly coefficient and the preset target heating anomaly coefficient, and acceptance work can be carried out to ensure that the service quality meets the standard requirements.

[0080] In this embodiment, a formal contract is signed with the user to clarify the rights and obligations of both parties.

[0081] In this embodiment, the system can track the progress of each node in real time throughout the process and send reminder notifications to relevant personnel. The platform will permanently store all user information and historical data from all participants in the network access process as record-keeping materials for future contact or retrieval. In this embodiment, real-time heating data includes supply water temperature, return water temperature, heating pressure, and heating flow rate.

[0082] In this embodiment, the standard heating data and the real-time heating data correspond one-to-one, and the specific correspondence is determined according to the actual situation.

[0083] The beneficial effects of the above technical solution are: the present invention can predict abnormal states of the heating system in advance, thereby improving the operating efficiency and stability of the heating system and reducing energy consumption and the probability of failure.

[0084] In some embodiments of this application, the curve fitting module is used for:

[0085] The curve fitting module is used to calculate the difference between the real-time heating data and the standard heating data, and to construct a heating data difference sequence.

[0086] The curve fitting module is used to determine the allowable heating data error range corresponding to the heating system, wherein the allowable heating data error range includes a first allowable heating data error and a second allowable heating data error;

[0087] The curve fitting module is used to remove all heating data differences in the heating data difference sequence that are within the allowable heating data error range based on the allowable heating data error range, and to obtain a second heating data difference sequence.

[0088] The curve fitting module is used to fit the heating data difference within the second heating data difference sequence to obtain the heating data fitting curve.

[0089] In this embodiment, the heating data difference is the absolute value of the difference between real-time heating data and standard heating data.

[0090] In this embodiment, the allowable error range is set by the staff. In actual heating, a certain error is allowed. For example, if the allowable heating data error range is temperature, then the first allowable heating data error is -1℃ and the second allowable heating data error is 2℃.

[0091] The beneficial effects of the above technical solution are: the present invention fits the heating data difference within the second heating data difference sequence to obtain a heating data fitting curve. By obtaining the heating data fitting curve, the present invention can lay the foundation for subsequent analysis.

[0092] In some embodiments of this application, the first computing module is used for:

[0093] The first calculation module is used to construct a first data interval based on the first allowable heating data error and the standard data error;

[0094] The first calculation module is used to construct a second data range based on the second allowable heating data error and the standard data error;

[0095] The first calculation module is used to analyze the removed heating data differences and count the number of first heating data differences that fall into the first data interval.

[0096] The first calculation module is used to count the number of second heating data differences that fall into the second data interval;

[0097] The first calculation module is used to calculate the heating anomaly coefficient of the heating system based on the number of differences between the first heating data and the number of differences between the second heating data.

[0098] In this embodiment, the method for determining the slope will not be repeated here; simply take the maximum slope.

[0099] In this embodiment, the standard data error is 0. As mentioned above, the first data interval is constructed based on -1℃ and 0, and the second data interval is constructed based on 0 and 2℃.

[0100] In this embodiment, the removed heating data difference falls into one of these two intervals. Therefore, the number of the first heating data difference and the number of the second heating data difference can be counted.

[0101] The beneficial effects of the above technical solution are: the present invention calculates the heating anomaly coefficient of the heating system based on the number of differences between the first heating data and the number of differences between the second heating data, which ensures the calculation accuracy of the heating anomaly coefficient and avoids errors.

[0102] In some embodiments of this application, the first computing module is used for:

[0103] The first calculation module is used to calculate the heating anomaly coefficient of the heating system according to the following formula:

[0104] ;

[0105] Where a1 is the heating anomaly coefficient of the heating system, n is the number of heating data differences removed, and b i Let be the i-th removed heating data difference, e1 be the first allowable heating data error, e2 be the second allowable heating data error, f1 = n1 / (n1 + n2), n1 be the number of the first heating data difference, n2 be the number of the second heating data difference, f2 = n2 / (n1 + n2), g be the adjustment coefficient of the heating anomaly coefficient, and h be the maximum fitting slope.

[0106] In some embodiments of this application, the first computing module is used for:

[0107] The first calculation module is used to determine the adjustment coefficient g of the heating anomaly coefficient according to the following steps;

[0108] The first calculation module is used to count the first number n3 of heating data differences on the heating data fitting curve;

[0109] The first calculation module is used to preset a first preset adjustment coefficient, a second preset adjustment coefficient, and a third preset adjustment coefficient;

[0110] The first calculation module is used to select the first preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when n3 / (n1+n2) < 1;

[0111] The first calculation module is used to select the second preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when 1≤n3 / (n1+n2)<1.2;

[0112] The first calculation module is used to select the third preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when 1.2≤n3 / (n1+n2).

[0113] In this embodiment, the first preset adjustment coefficient is preferably 0.85, the second preset adjustment coefficient is preferably 1.15, and the third preset adjustment coefficient is preferably 1.25.

[0114] The beneficial effects of the above technical solution are: the present invention selects different adjustment coefficients based on the first number of heating data differences on the heating data fitting curve, thereby realizing the dynamic adjustment of the heating anomaly coefficient and further ensuring the calculation accuracy.

[0115] In some embodiments of this application, the second computing module is used for:

[0116] The second calculation module is used to divide the preset time range into multiple time node intervals, and determine the first heating flow data and the second heating flow data for each time node interval. The first heating flow data is the heating flow data corresponding to the end time of each time node interval, and the second heating flow data is the difference between the heating flow data corresponding to the start time and the end time of each time node interval.

[0117] The second calculation module is used to determine the first historical heating response coefficient of the heating system based on the first heating flow data and the second heating flow data, wherein the first historical heating response coefficient is the product of the first heating flow data and the second heating flow data;

[0118] The second calculation module is used to determine the first heating temperature data and the second heating temperature data for each time node interval. The first heating temperature data is the heating temperature data corresponding to the end time of each time node interval, and the second heating temperature data is the difference between the heating temperature data corresponding to the start time and the end time of each time node interval.

[0119] The second calculation module is used to determine the second historical heating response coefficient of the heating system based on the first heating temperature data and the second heating temperature data, wherein the second historical heating response coefficient is the product of the first heating temperature data and the second heating temperature data;

[0120] The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to each time node interval based on the first historical heating response coefficient and the second historical heating response coefficient;

[0121] The second calculation module is used to calculate the historical heating response coefficient of the heating system based on all comprehensive historical heating response coefficients.

[0122] In this embodiment, the preset duration range can be set to 10 minutes, and the multiple time node intervals are {0,2}, {2,4}, {4,6}, {6,8}, and {8,10}, in minutes. It can also be set according to the actual situation.

[0123] In this embodiment, the first heating data refers to the heating flow data corresponding to the 2nd minute, 4th minute, 6th minute, 8th minute, and 10th minute.

[0124] In this embodiment, the second heating flow rate data is the difference between the heating flow rate data in the 4th minute and the heating flow rate data in the 2nd minute. The rest will not be shown individually.

[0125] In this embodiment, the first heating temperature data and the second heating temperature data are determined in the same way as described above, and will not be repeated here.

[0126] In this embodiment, the comprehensive historical heating response coefficient corresponding to each time node interval can be obtained.

[0127] The beneficial effects of the above technical solution are: the present invention calculates the historical heating response coefficient of the heating system based on all comprehensive historical heating response coefficients, avoids the calculation errors caused by manual calculation, and provides a basis for optimizing the heating anomaly coefficient.

[0128] In some embodiments of this application, the second computing module is used for:

[0129] The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to the time node interval according to the following formula:

[0130] ;

[0131] Where k is the comprehensive historical heating response coefficient, p1 is the first calculation coefficient, q1 is the first historical heating response coefficient, q2 is the second historical heating response coefficient, p2 is the second calculation coefficient, p1 < 0, p2 < 0.

[0132] In some embodiments of this application, the second computing module is used for:

[0133] The second calculation module is used to extract the same comprehensive historical heating response coefficient from all comprehensive historical heating response coefficients and obtain multiple comprehensive historical heating response coefficient sequences;

[0134] The second calculation module is used to count the number of the first comprehensive historical heating response coefficient sequences in the comprehensive historical heating response coefficient sequence;

[0135] The second calculation module is used to extract a comprehensive historical heating response coefficient from all comprehensive historical heating response coefficient sequences, and to calculate the sum of the first comprehensive historical heating response coefficients;

[0136] The second calculation module is used to obtain a preset comprehensive historical heating response coefficient, remove all comprehensive historical heating response coefficient sequences that are less than the preset comprehensive historical heating response coefficient, and count the number of second comprehensive historical heating response coefficient sequences of the remaining comprehensive historical heating response coefficient sequences.

[0137] The second calculation module is used to extract one comprehensive historical heating response coefficient from the remaining comprehensive historical heating response coefficient sequence, and to calculate the second comprehensive historical heating response coefficient and its value.

[0138] The second calculation module is used to calculate the historical heating response coefficient of the heating system based on the number of the first comprehensive historical heating response coefficient sequence, the number of the second comprehensive historical heating response coefficient sequence, the sum of the first comprehensive historical heating response coefficient and the sum of the second comprehensive historical heating response coefficient.

[0139] In this embodiment, multiple comprehensive historical heating response coefficient sequences are obtained, such as {2,2}, {4,4,4}, {6,6}, and {8,8,8}. The first comprehensive historical heating response coefficient sequence has 4 sequences. One comprehensive historical heating response coefficient is extracted from each of the sequences, which is 2,4,6,8. The preset comprehensive historical heating response coefficient is 3. Then the remaining comprehensive historical heating response coefficient sequences are {4,4,4}, {6,6}, and {8,8,8}. One comprehensive historical heating response coefficient is extracted from each of the remaining sequences, which is 4,6,8.

[0140] In this embodiment, the historical heating response coefficient of the heating system is calculated according to the following formula:

[0141] ;

[0142] Where u is the historical heating response coefficient of the heating system, w1 is the number of sequences of the first comprehensive historical heating response coefficient, w2 is the number of sequences of the second comprehensive historical heating response coefficient, w3 is the sum of the first comprehensive historical heating response coefficients, and w4 is the sum of the second comprehensive historical heating response coefficients.

[0143] The beneficial effects of the above technical solution are: the present invention calculates the historical heating response coefficient of the heating system based on the number of sequences of the first comprehensive historical heating response coefficient, the number of sequences of the second comprehensive historical heating response coefficient, the sum of the first comprehensive historical heating response coefficient and the sum of the second comprehensive historical heating response coefficient, thus ensuring the accuracy of the calculation of the historical heating response coefficient.

[0144] In some embodiments of this application, the data optimization module is used for:

[0145] The first preset historical heating response coefficient and the second preset historical heating response coefficient are set in advance;

[0146] Pre-set the first preset optimization coefficient, the second preset optimization coefficient, and the third preset optimization coefficient;

[0147] When the historical heating response coefficient is less than the first preset historical heating response coefficient, the product of the first preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system.

[0148] When the historical heating response coefficient is greater than or equal to the first preset historical heating response coefficient and less than the second preset historical heating response coefficient, the product of the second preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system.

[0149] When the historical heating response coefficient is greater than or equal to the second preset historical heating response coefficient, the product of the third preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system.

[0150] In this embodiment, the first preset historical heating response coefficient is preferably 6, and the second preset historical heating response coefficient is preferably 9.

[0151] In this embodiment, the first preset optimization coefficient is preferably 0.95, the second preset optimization coefficient is preferably 1.05, and the third preset optimization coefficient is preferably 1.1.

[0152] The beneficial effects of the above technical solution are: the present invention sets optimization coefficients based on historical heating response coefficients, first preset historical heating response coefficients and second preset historical heating response coefficients, thereby achieving fine-tuning of heating anomaly coefficients and ensuring comprehensive calculation.

[0153] In some embodiments of this application, the acceptance and signing module is used for:

[0154] The acceptance and signing module is used to determine that the heating system does not have abnormal operation when the target heating anomaly coefficient is less than the preset target heating anomaly coefficient.

[0155] The acceptance and signing module is used to determine that the heating system is operating abnormally when the target heating anomaly coefficient is greater than or equal to the preset target heating anomaly coefficient.

[0156] In this embodiment, the preset target heating anomaly coefficient is 8.

[0157] The beneficial effects of the above technical solution are: the present invention determines whether there is abnormal operation based on the target heating anomaly coefficient and the preset target heating anomaly coefficient, and predicts the abnormal state of the heating system in advance, thereby improving the operating efficiency and stability of the heating system and reducing energy consumption and the probability of failure.

[0158] In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0159] Although the invention has been described above with reference to embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, as long as there is no structural conflict, the features in the embodiments disclosed in this invention can be combined with each other in any way. The fact that not all of these combinations are described in this specification is merely for the sake of brevity and resource conservation.

[0160] It will be understood by those skilled in the art that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A heating management system, characterized in that, include: The preliminary review module is used to receive network access applications from different types of users, review the network access applications according to preset rules, and perform network access operations when the user passes the review. The curve fitting module is used to obtain the real-time heating data corresponding to the heating system at the current time point after performing the network access operation, determine the standard heating data corresponding to the real-time heating data, and determine the heating data fitting curve based on the real-time heating data and the standard heating data. The first calculation module is used to analyze the fitting curve of the heating data, extract the maximum fitting slope from the fitting curve, and calculate the heating anomaly coefficient of the heating system based on the maximum fitting slope. The second calculation module is used to collect the heating flow rate data and heating temperature data of the heating system within a preset time range before the current time node, and calculate the historical heating response coefficient of the heating system based on the heating flow rate data and heating temperature data. The data optimization module is used to set optimization coefficients based on the historical heating response coefficients, and to optimize the heating anomaly coefficients based on the optimization coefficients to obtain the target heating anomaly coefficient of the heating system. The acceptance and signing module is used to determine whether the heating system is operating abnormally based on the target heating anomaly coefficient and the preset target heating anomaly coefficient. If not, the acceptance work is carried out and a formal contract is signed with the user.

2. The heating management system according to claim 1, characterized in that, The curve fitting module is used for: The curve fitting module is used to calculate the difference between the real-time heating data and the standard heating data, and to construct a heating data difference sequence. The curve fitting module is used to determine the allowable heating data error range corresponding to the heating system, wherein the allowable heating data error range includes a first allowable heating data error and a second allowable heating data error; The curve fitting module is used to remove all heating data differences in the heating data difference sequence that are within the allowable heating data error range based on the allowable heating data error range, and to obtain a second heating data difference sequence. The curve fitting module is used to fit the heating data difference within the second heating data difference sequence to obtain the heating data fitting curve.

3. The heating management system according to claim 2, characterized in that, The first calculation module is used for: The first calculation module is used to construct a first data interval based on the first allowable heating data error and the standard data error; The first calculation module is used to construct a second data range based on the second allowable heating data error and the standard data error; The first calculation module is used to analyze the removed heating data differences and count the number of first heating data differences that fall into the first data interval. The first calculation module is used to count the number of second heating data differences that fall into the second data interval; The first calculation module is used to calculate the heating anomaly coefficient of the heating system based on the number of differences between the first heating data and the number of differences between the second heating data.

4. The heating management system according to claim 3, characterized in that, The first calculation module is used for: The first calculation module is used to calculate the heating anomaly coefficient of the heating system according to the following formula: ； Where a1 is the heating anomaly coefficient of the heating system, n is the number of heating data differences removed, and b i Let be the i-th removed heating data difference, e1 be the first allowable heating data error, e2 be the second allowable heating data error, f1 = n1 / (n1 + n2), n1 be the number of the first heating data difference, n2 be the number of the second heating data difference, f2 = n2 / (n1 + n2), g be the adjustment coefficient of the heating anomaly coefficient, and h be the maximum fitting slope.

5. The heating management system according to claim 4, characterized in that, The first calculation module is used for: The first calculation module is used to determine the adjustment coefficient g of the heating anomaly coefficient according to the following steps; The first calculation module is used to count the first number n3 of heating data differences on the heating data fitting curve; The first calculation module is used to preset a first preset adjustment coefficient, a second preset adjustment coefficient, and a third preset adjustment coefficient; The first calculation module is used to select the first preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when n3 / (n1+n2) < 1; The first calculation module is used to select the second preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when 1≤n3 / (n1+n2)<1.2; The first calculation module is used to select the third preset adjustment coefficient as the adjustment coefficient g of the heating anomaly coefficient when 1.2≤n3 / (n1+n2).

6. The heating management system according to claim 1, characterized in that, The second calculation module is used for: The second calculation module is used to divide the preset time range into multiple time node intervals, and determine the first heating flow data and the second heating flow data for each time node interval. The first heating flow data is the heating flow data corresponding to the end time of each time node interval, and the second heating flow data is the difference between the heating flow data corresponding to the start time and the end time of each time node interval. The second calculation module is used to determine the first historical heating response coefficient of the heating system based on the first heating flow data and the second heating flow data, wherein the first historical heating response coefficient is the product of the first heating flow data and the second heating flow data; The second calculation module is used to determine the first heating temperature data and the second heating temperature data for each time node interval. The first heating temperature data is the heating temperature data corresponding to the end time of each time node interval, and the second heating temperature data is the difference between the heating temperature data corresponding to the start time and the end time of each time node interval. The second calculation module is used to determine the second historical heating response coefficient of the heating system based on the first heating temperature data and the second heating temperature data, wherein the second historical heating response coefficient is the product of the first heating temperature data and the second heating temperature data; The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to each time node interval based on the first historical heating response coefficient and the second historical heating response coefficient; The second calculation module is used to calculate the historical heating response coefficient of the heating system based on all comprehensive historical heating response coefficients.

7. The heating management system according to claim 6, characterized in that, The second calculation module is used for: The second calculation module is used to calculate the comprehensive historical heating response coefficient corresponding to the time node interval according to the following formula: ； Where k is the comprehensive historical heating response coefficient, p1 is the first calculation coefficient, q1 is the first historical heating response coefficient, q2 is the second historical heating response coefficient, p2 is the second calculation coefficient, p1 < 0, p2 < 0.

8. The heating management system according to claim 1, characterized in that, The second calculation module is used for: The second calculation module is used to extract the same comprehensive historical heating response coefficient from all comprehensive historical heating response coefficients and obtain multiple comprehensive historical heating response coefficient sequences; The second calculation module is used to count the number of the first comprehensive historical heating response coefficient sequences in the comprehensive historical heating response coefficient sequence; The second calculation module is used to extract a comprehensive historical heating response coefficient from all comprehensive historical heating response coefficient sequences, and to calculate the sum of the first comprehensive historical heating response coefficients; The second calculation module is used to obtain a preset comprehensive historical heating response coefficient, remove all comprehensive historical heating response coefficient sequences that are less than the preset comprehensive historical heating response coefficient, and count the number of second comprehensive historical heating response coefficient sequences of the remaining comprehensive historical heating response coefficient sequences. The second calculation module is used to extract one comprehensive historical heating response coefficient from the remaining comprehensive historical heating response coefficient sequence, and to calculate the second comprehensive historical heating response coefficient and its value. The second calculation module is used to calculate the historical heating response coefficient of the heating system based on the number of the first comprehensive historical heating response coefficient sequence, the number of the second comprehensive historical heating response coefficient sequence, the sum of the first comprehensive historical heating response coefficient and the sum of the second comprehensive historical heating response coefficient.

9. The heating management system according to claim 1, characterized in that, The data optimization module is used for: The first preset historical heating response coefficient and the second preset historical heating response coefficient are set in advance; Pre-set the first preset optimization coefficient, the second preset optimization coefficient, and the third preset optimization coefficient; When the historical heating response coefficient is less than the first preset historical heating response coefficient, the product of the first preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system. When the historical heating response coefficient is greater than or equal to the first preset historical heating response coefficient and less than the second preset historical heating response coefficient, the product of the second preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system. When the historical heating response coefficient is greater than or equal to the second preset historical heating response coefficient, the product of the third preset optimization coefficient and the heating anomaly coefficient is calculated and used as the target heating anomaly coefficient of the heating system.

10. The heating management system according to claim 1, characterized in that, The acceptance and signing module is used for: The acceptance and signing module is used to determine that the heating system does not have abnormal operation when the target heating anomaly coefficient is less than the preset target heating anomaly coefficient. The acceptance and signing module is used to determine that the heating system is operating abnormally when the target heating anomaly coefficient is greater than or equal to the preset target heating anomaly coefficient.

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