Online monitoring system for heat treatment furnace

Abstract

The invention provides an on-line monitoring system for a heat treatment furnace, and belongs to the technical field of on-line monitoring, and the system comprises a part determination module which is used for determining working parts of the heat treatment furnace in different working states; the monitoring deployment module is used for determining working weights and working attributes of the corresponding working parts in different working states according to the working conditions of each working part based on different working states, and deploying a part monitoring set and a space monitoring set corresponding to the positions of the working parts; the on-line monitoring module is used for controlling the component monitoring set to carry out first on-line monitoring and the space monitoring set to carry out second on-line monitoring according to the current set state of the heat treatment furnace; and the exception handling module is used for analyzing and processing the first online monitoring result and the second online monitoring result, determining the current exception of the heat treatment furnace and handling the exception. And efficient treatment of abnormities of the heat treatment furnace is effectively guaranteed, and then the working efficiency of the heat treatment furnace is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of online monitoring, and in particular to an online monitoring system for a heat treatment furnace. Background Art

[0002] Vacuum heat treatment is a comprehensive technology that combines vacuum technology and heat treatment. It means that all or part of the heat treatment process is carried out under vacuum. The vacuum heat treatment furnace has high thermal efficiency, can achieve rapid heating and cooling, can achieve no oxidation, no decarburization, no carburization, can remove phosphorus chips on the surface of the workpiece, and has the functions of degreasing and degassing, so as to achieve the effect of surface brightness and purification.

[0003] In order to ensure the normal operation of the heat treatment furnace during its operation, it is generally manually inspected and maintained periodically. However, the experience of manual inspection will affect the monitoring results of the heat treatment furnace, resulting in low monitoring efficiency of the heat treatment furnace, which will further affect the working efficiency of the heat treatment furnace.

[0004] Therefore, the present invention provides an online monitoring system for a heat treatment furnace. Summary of the invention

[0005] The present invention provides an online monitoring system for a heat treatment furnace, which is used to monitor and deploy components and spaces according to the working weights and working properties of different working components in the heat treatment furnace under different working conditions, thereby realizing online monitoring from two aspects, effectively ensuring efficient processing of abnormalities in the heat treatment furnace, and further ensuring the working efficiency of the heat treatment furnace.

[0006] The present invention provides an online monitoring system for a heat treatment furnace, comprising:

[0007] A component determination module, used to determine the working components involved in different working states of the heat treatment furnace;

[0008] A monitoring deployment module is used to determine the working weight and working attributes of the corresponding working component in different working states according to the working conditions of each working component based on different working states, and deploy a component monitoring set and a spatial monitoring set of the location of the corresponding working component;

[0009] An online monitoring module, for controlling the component monitoring device in the component monitoring set that matches the current set state to perform a first online monitoring on the corresponding working component and the space monitoring device in the space monitoring set that matches the current set state to perform a second online monitoring on the working space of the corresponding working component according to the current set state of the heat treatment furnace;

[0010] The abnormality processing module is used to analyze and process the first online monitoring result and the second online monitoring result, determine the current abnormality of the heat treatment furnace and perform abnormality processing.

[0011] Preferably, the component determination module includes:

[0012] A model acquisition unit, used to acquire the furnace model of the heat treatment furnace;

[0013] A state matching unit, used for matching the working state of the heat treatment furnace from a preset database according to the furnace model;

[0014] The component matching unit is used to match the working components involved in each working state based on the state-component operation mapping table.

[0015] Preferably, the monitoring deployment module includes:

[0016] A first matrix construction unit is used to extract a working vector of each working component in each working state from a work log of the heat treatment furnace, and construct a working matrix of the heat treatment furnace in the corresponding working state;

[0017] A second matrix construction unit is used to extract a standard vector of each working component in each working state from a standard database, and construct a standard matrix of the heat treatment furnace in a corresponding working state;

[0018] An offset weight determination unit is used to compare the working matrix under the same working state with the standard matrix for the same elements, determine the maximum difference and variance in each row vector in the corresponding working matrix, and calculate the row offset coefficient of the corresponding row vector;

[0019]

[0020] Among them, P1 i1 X1 represents the row offset coefficient of the i1th row vector; max,i1 represents the maximum difference of the i1th row vector, and the difference of each element in each row vector is the absolute value of the difference between the elements; represents the variance of the i1th row vector; X1 ave,i1 represents the average difference of the i1th row vector;

[0021] Based on all the row deviation coefficients, determining the state deviation coefficient of the heat treatment furnace in the corresponding working state;

[0022]

[0023] Among them, P2 represents the state shift coefficient under the corresponding working state; n1 represents the number of row vectors in the working matrix under the corresponding working state; σ2 2Indicates all P1 in the corresponding working matrix i1 Variance; h1 represents the variance based on all The fitted variance of the constructed variance dispersion plot; h2 represents all The average variance of the probability of satisfying the normal distribution;

[0024] A coefficient determination unit, used for obtaining a characteristic parameter set of each row vector in the corresponding working matrix to determine a difference characteristic to assign an influence coefficient to the corresponding row vector, and calculating the coefficient sum of all influence coefficients;

[0025]

[0026] Among them, Y1 i1 Represents the characteristic parameter set of the i1th row vector; X1 j1 represents the value of the j1th element in the i1th row vector, and the value of j1 is 1, 2, 3, ..., n2; n01 represents the value of the i1th row vector that satisfies X1 j1 ≥X1 ave,i1 The number of elements of ;

[0027] A number determination unit is used to obtain the number of first elements whose difference values ​​are greater than 0, the number of second elements whose difference values ​​are less than 0, and the number of third elements whose difference values ​​are equal to 0 in each row vector in the corresponding working matrix; and calculate the main coefficient and the secondary coefficient of the corresponding row vector according to the number of first elements, the number of second elements, and the number of third elements;

[0028] A compromise unit, configured to obtain a working weight of a corresponding working component under the same working state based on a row offset coefficient, a state offset coefficient, a standard weight under a corresponding working state, and a coefficient sum, and in combination with a compromise condition of the primary coefficient and the secondary coefficient;

[0029] The attribute determination unit is used to obtain the working attribute according to the standard attribute of each working component under the same working state and in combination with the component working deviation.

[0030] Preferably, the monitoring deployment module further includes:

[0031] A first establishing unit, configured to establish a first weight range based on the working weight of each working component in each working state;

[0032] A second establishing unit, configured to establish a first attribute range based on the working attribute of each working component in each working state;

[0033] A monitoring value calculation unit, used to establish a minimum monitoring value and a maximum monitoring value of a corresponding working component in a corresponding working state according to the first weight range and the first attribute range;

[0034] A scheme acquisition unit, configured to deploy a monitoring scheme to a corresponding working component according to the minimum monitoring value and the maximum monitoring value, and based on all monitoring schemes of the same working component;

[0035] The set determination unit is used to retrieve the matching own position and spatial position from the type-position-device mapping table according to the device monitoring type of each monitoring device in all monitoring schemes, and determine the component monitoring set of the corresponding working component and the spatial monitoring set of the location.

[0036] Preferably, the online monitoring module comprises:

[0037] A state acquisition unit, used to acquire the current setting state of the heat treatment furnace, wherein the current setting state is a mode setting performed by a staff before the heat treatment furnace is operated;

[0038] The monitoring control unit is used to control the online monitoring of the device in the monitoring deployment situation corresponding to the state with the highest similarity to the current set state from all working states.

[0039] Preferably, the exception handling module includes:

[0040] A sorting unit, used to arrange the first online monitoring result and the second online monitoring result in order of position according to the processing thread of the heat treatment furnace to obtain an initial monitoring result;

[0041] A comparison unit, used to compare the initial monitoring result with the standard operation result of the current set state, obtain an operation difference result, and construct a difference framework;

[0042] A parsing unit, used for performing a framework analysis on the difference framework to obtain a current abnormality of the heat treatment furnace;

[0043] The means determining unit is used to determine the exception handling means according to the exception type and the exception location of the current exception.

[0044] Preferably, it also includes:

[0045] A communication building module, used to initialize the component monitoring device involved in the first online monitoring and the space monitoring device involved in the second online monitoring, and to build a communication set;

[0046] The communication transmission module is used to bind each communication interface in the communication set with a possible communication event of the corresponding device in the current set state, and after the binding is completed, the monitoring result is transmitted by communication.

[0047] Preferably, the communication transmission module includes:

[0048] An information acquisition unit, used to acquire historical monitoring information of different devices involved in a working state whose matching degree with the current set state is greater than a preset degree;

[0049] A table construction unit, used to extract all monitoring reference information consistent with each device involved in the current set state from all historical monitoring information, and construct an event mapping table for the device, wherein the event mapping table includes the event occurrence probability, the probability of causing an abnormality, and the probability of associated abnormality for each event;

[0050] An importance assigning unit, configured to assign communication importance to each device involved in the current setting state based on the event mapping table;

[0051] The protocol binding unit is used to combine the event mapping table of the corresponding device with the communication importance to bind the corresponding communication security protocol to the corresponding device and perform communication transmission of the monitoring results.

[0052] Preferably, the compromise unit comprises:

[0053]

[0054] Among them, bq represents the standard weight under the corresponding working state; sumy1 represents the coefficient sum under the corresponding working state; y1 i1 represents the influence coefficient of the i1th row vector in the working matrix under the corresponding working state; m01 represents the corresponding first number; m02 represents the corresponding second number; m03 represents the corresponding third number; T1 represents the working weight of the corresponding working component under the same working state; represents the main coefficient; Represents the minor coefficient.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0057] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0059] Figure 1The structure diagram of an online monitoring system for a heat treatment furnace in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0061] The present invention provides an online monitoring system for a heat treatment furnace, such as Figure 1 As shown, including:

[0062] A component determination module, used to determine the working components involved in different working states of the heat treatment furnace;

[0063] A monitoring deployment module is used to determine the working weight and working attributes of the corresponding working component in different working states according to the working conditions of each working component based on different working states, and deploy a component monitoring set and a spatial monitoring set of the location of the corresponding working component;

[0064] An online monitoring module, for controlling the component monitoring device in the component monitoring set that matches the current set state to perform a first online monitoring on the corresponding working component and the space monitoring device in the space monitoring set that matches the current set state to perform a second online monitoring on the working space of the corresponding working component according to the current set state of the heat treatment furnace;

[0065] The abnormality processing module is used to analyze and process the first online monitoring result and the second online monitoring result, determine the current abnormality of the heat treatment furnace and perform abnormality processing.

[0066] In this embodiment, for example, there are state 1, state 2 and state 3 for the working state of the heat treatment furnace, which may be modes related to annealing, quenching and the like.

[0067] In this embodiment, the working parts may be a heating furnace body, a combustion device, an automatic control system, etc. in a heat treatment furnace.

[0068] In this embodiment, for example, state 1 involves component 01, component 02 and component 03, state 2 involves component 01, component 02 and component 04, and state 3 involves component 01 and component 02. At this time, we can obtain component 01--state 1, state 2 and state 3, component 02--state 1, state 2 and state 3, component 03--state 1, component 04--state 2.

[0069] In this embodiment, the component working weights and standard attributes of the working components involved in each working state are set at the factory. The working attributes refer to the actual attributes of the corresponding working components in the corresponding working state, and the purpose of attribute acquisition is to perform component monitoring on the components.

[0070] In this embodiment, the component monitoring set refers to the monitoring devices required for the corresponding working components under different working conditions, that is, the collection of monitoring devices set on the working components themselves. The space monitoring set refers to the collection of various monitoring devices set at the space monitoring positions corresponding to the corresponding components under all working conditions, because the monitoring devices required by different components are different.

[0071] In this embodiment, the current setting state refers to the state of the setting mode of the heat treatment furnace at the current moment.

[0072] In this embodiment, the matching of the monitoring devices in the current setting state is achieved based on the corresponding component monitoring set and the space monitoring set, and online monitoring can be directly performed after matching.

[0073] In this embodiment, the purpose of the analysis and processing is to compare the actual monitoring results with the standard results to effectively determine the existence of abnormalities, and the standard results are pre-set.

[0074] The beneficial effect of the above technical solution is: according to the working weights and working properties of different working components in the heat treatment furnace under different working conditions, the monitoring deployment of components and space is carried out, and online monitoring is realized from two aspects, which effectively ensures the efficient handling of abnormalities in the heat treatment furnace, thereby ensuring the working efficiency of the heat treatment furnace.

[0075] The present invention provides an online monitoring system for a heat treatment furnace, wherein the component determination module comprises:

[0076] A model acquisition unit, used to acquire the furnace model of the heat treatment furnace;

[0077] A state matching unit, used for matching the working state of the heat treatment furnace from a preset database according to the furnace model;

[0078] The component matching unit is used to match the working components involved in each working state based on the state-component operation mapping table.

[0079] In this embodiment, the furnace model can be directly obtained from the factory information of the heat treatment furnace.

[0080] In this embodiment, the preset database includes different furnace models and working states matching the furnace models, which can be directly obtained.

[0081] In this embodiment, the state-component operation mapping table includes different states and the working components that match the states, and can also be directly obtained.

[0082] The beneficial effects of the above technical solution are: matching the working status consistent with the furnace model from the preset database, and further matching the working components matching the working status from the mapping table, providing convenience for the subsequent deployment of monitoring devices.

[0083] The present invention provides an online monitoring system for a heat treatment furnace, wherein the monitoring deployment module comprises:

[0084] A first matrix construction unit is used to extract a working vector of each working component in each working state from a work log of the heat treatment furnace, and construct a working matrix of the heat treatment furnace in the corresponding working state;

[0085] A second matrix construction unit is used to extract a standard vector of each working component in each working state from a standard database, and construct a standard matrix of the heat treatment furnace in a corresponding working state;

[0086] An offset weight determination unit is used to compare the working matrix under the same working state with the standard matrix for the same elements, determine the maximum difference and variance in each row vector in the corresponding working matrix, and calculate the row offset coefficient of the corresponding row vector;

[0087]

[0088] Among them, P1 i1 X1 represents the row offset coefficient of the i1th row vector; max,i1 represents the maximum difference of the i1th row vector, and the difference of each element in each row vector is the absolute value of the difference between the elements; represents the variance of the i1th row vector; X1 ave,i1 represents the average difference of the i1th row vector;

[0089] Based on all the row deviation coefficients, determining the state deviation coefficient of the heat treatment furnace in the corresponding working state;

[0090]

[0091] Among them, P2 represents the state shift coefficient under the corresponding working state; n1 represents the number of row vectors in the working matrix under the corresponding working state; σ2 2 Indicates all P1 in the corresponding working matrix i1 Variance; h1 represents the variance based on all The fitted variance of the constructed variance dispersion plot; h2 represents all The average variance of the probability of satisfying the normal distribution;

[0092] A coefficient determination unit, used for obtaining a characteristic parameter set of each row vector in the corresponding working matrix to determine a difference characteristic to assign an influence coefficient to the corresponding row vector, and calculating the coefficient sum of all influence coefficients;

[0093]

[0094] Among them, Y1 i1 Represents the characteristic parameter set of the i1th row vector; X1 j1 represents the value of the j1th element in the i1th row vector, and the value of j1 is 1, 2, 3, ..., n2; n01 represents the value of the i1th row vector that satisfies X1 j1 ≥X1 ave,i1 The number of elements of ;

[0095] A number determination unit is used to obtain the number of first elements whose difference values ​​are greater than 0, the number of second elements whose difference values ​​are less than 0, and the number of third elements whose difference values ​​are equal to 0 in each row vector in the corresponding working matrix; and calculate the main coefficient and the secondary coefficient of the corresponding row vector according to the number of first elements, the number of second elements, and the number of third elements;

[0096] A compromise unit, configured to obtain a working weight of a corresponding working component under the same working state based on a row offset coefficient, a state offset coefficient, a standard weight under a corresponding working state, and a coefficient sum, and in combination with a compromise condition of the primary coefficient and the secondary coefficient;

[0097] The attribute determination unit is used to obtain the working attribute according to the standard attribute of each working component under the same working state and in combination with the component working deviation.

[0098] Preferably, the compromise unit comprises:

[0099]

[0100] Among them, bq represents the standard weight under the corresponding working state; sumy1 represents the coefficient sum under the corresponding working state; y1 i1 represents the influence coefficient of the i1th row vector in the working matrix under the corresponding working state; m01 represents the corresponding first number; m02 represents the corresponding second number; m03 represents the corresponding third number; T1 represents the working weight of the corresponding working component under the same working state; represents the main coefficient; Represents the minor coefficient.

[0101] In this embodiment, the heat treatment furnace work log is a record of the operation data of the heat treatment furnace by the intelligent system or personnel during the operation of the heat treatment furnace. It is known data, that is, different working parts will have multiple parameters that need to be analyzed during the operation process, so there will be corresponding work vectors.

[0102] In this embodiment, the working vector of the working component 01 in the working state 1 is {operating parameter 1 operating parameter 2 operating parameter 3 . . .}.

[0103]

[0104] In this embodiment, the standard database is set before the heat treatment furnace leaves the factory, and the standard matrix is ​​constructed according to the construction principle of the working matrix.

[0105] In this embodiment, element standardization is performed during element comparison, mainly to facilitate calculation.

[0106] In this embodiment, the same element comparison refers to comparing the elements at the same position in two matrices, so as to determine the maximum difference and variance in the corresponding rows.

[0107] In this embodiment, the working attributes are the actual attributes of the corresponding working parts, and can be obtained by adjusting the standard attributes based on the working deviation. The standard-deviation-actual mapping table includes different standard attributes, working deviation combinations and working attributes corresponding to the combinations, which can be directly obtained.

[0108] The beneficial effects of the above technical solution are: comparing the working matrix of the heat treatment furnace in different working states with the standard matrix to determine the row offset coefficient of each row, and then comprehensively obtaining the state offset coefficient of the corresponding working state. At the same time, by determining the difference characteristics to assign the influence coefficient, to assign the working weight to the corresponding working component, to obtain the actual attributes, to facilitate the subsequent setting of monitoring devices, and indirectly improve the working efficiency of the heat treatment furnace.

[0109] The present invention provides an online monitoring system for a heat treatment furnace, wherein the monitoring deployment module further comprises:

[0110] A first establishing unit, configured to establish a first weight range based on the working weight of each working component in each working state;

[0111] A second establishing unit, configured to establish a first attribute range based on the working attribute of each working component in each working state;

[0112] A monitoring value calculation unit, used to establish a minimum monitoring value and a maximum monitoring value of a corresponding working component in a corresponding working state according to the first weight range and the first attribute range;

[0113] A scheme acquisition unit, configured to deploy a monitoring scheme to a corresponding working component according to the minimum monitoring value and the maximum monitoring value, and based on all monitoring schemes of the same working component;

[0114] The set determination unit is used to retrieve the matching own position and spatial position from the type-position-device mapping table according to the device monitoring type of each monitoring device in all monitoring schemes, and determine the component monitoring set of the corresponding working component and the spatial monitoring set of the location.

[0115] In this embodiment, the first weight range is:

[0116] In this embodiment, the first attribute range is:

[0117] In this embodiment, the maximum monitoring value = the maximum value of the first weight range × the first normalization coefficient + the maximum value of the first attribute range × the second normalization coefficient;

[0118] Minimum monitoring value = minimum value of the first weight range × first normalization coefficient + minimum value of the first attribute range × second normalization coefficient;

[0119] In this embodiment, the deployment monitoring scheme is based on the maximum monitoring value, the minimum monitoring value and the monitoring scheme matching these two values, thereby obtaining the same monitoring scheme for the corresponding working component under each working state.

[0120] In this embodiment, the type-position-device mapping table includes component class devices of different original working parts, device types, and setting positions for monitoring the working parts according to the devices. Therefore, the spatial setting position and the inherent setting position of each monitoring device can be directly retrieved. All spatial setting positions can constitute a spatial monitoring set, and all inherent setting positions can constitute a component monitoring set.

[0121] The beneficial effect of the above technical solution is: by establishing a weight range and an attribute range, it is convenient to determine the maximum monitoring value and the minimum monitoring value of the corresponding working state, and then it is convenient to obtain the monitoring set of the corresponding component and then it is convenient to obtain the spatial monitoring set, which provides a basis for the effective monitoring of the working parts and indirectly ensures the working efficiency of the heat treatment furnace.

[0122] The present invention provides an online monitoring system for a heat treatment furnace, wherein the online monitoring module comprises:

[0123] A state acquisition unit, used to acquire the current setting state of the heat treatment furnace, wherein the current setting state is a mode setting performed by a staff before the heat treatment furnace is operated;

[0124] The monitoring control unit is used to control the online monitoring of the device in the monitoring deployment situation corresponding to the state with the highest similarity to the current set state from all working states.

[0125] In this embodiment, similarity matching is achieved based on a similarity function.

[0126] The beneficial effect of the above technical solution is that the device can be monitored online by acquiring the current setting state and matching it with the existing working state for similarity.

[0127] The present invention provides an online monitoring system for a heat treatment furnace, wherein the abnormality processing module comprises:

[0128] A sorting unit, used to arrange the first online monitoring result and the second online monitoring result in order of position according to the processing thread of the heat treatment furnace to obtain an initial monitoring result;

[0129] A comparison unit, used to compare the initial monitoring result with the standard operation result of the current set state, obtain an operation difference result, and construct a difference framework;

[0130] A parsing unit, used for performing a framework analysis on the difference framework to obtain a current abnormality of the heat treatment furnace;

[0131] The means determining unit is used to determine the exception handling means according to the exception type and the exception location of the current exception.

[0132] In this embodiment, the first online monitoring result is to monitor the corresponding working components according to the component monitoring set under the corresponding working state, and the second online monitoring result is to monitor the working components according to the space monitoring set, that is, the order of positions is pre-set, and the results can be arranged in this order and then compared with the standard operation results.

[0133] In this embodiment, the standard operation result is pre-set, and the existing parameter monitoring type is consistent with the parameter monitoring type in the adjusted monitoring result.

[0134] In this embodiment, the running difference result = {difference of parameter 1, difference of parameter 2, difference of parameter 3, ...}.

[0135] In this embodiment, the difference framework is obtained by inputting the difference results into the difference analysis model. The model is based on different operation difference results and the expert's framework construction of the operation difference results as samples to train the neural network model, so as to directly obtain the difference framework.

[0136] In this embodiment, the difference frame is analyzed by comparing the difference frame with the normal frame of the heat treatment furnace (factory set), so that the information of the difference can be determined, and then the current abnormality can be obtained, that is, the abnormal location can be directly determined from the architecture.

[0137] In this embodiment, the abnormal means are obtained based on the abnormal type-location-means mapping table, and the mapping table includes different abnormal types, abnormal locations and abnormal means matching the two.

[0138] The beneficial effects of the above technical solution are: by arranging the two online monitoring results in sequence and adjusting the results, it is convenient to obtain the results to be compared, and by comparing the difference framework constructed with the standard operation results, and then comparing it with the normal framework of the heat treatment furnace, the treatment means are determined to ensure the effective treatment of heat treatment thermal anomalies, thereby indirectly improving the working efficiency of the heat treatment furnace.

[0139] The present invention provides an online monitoring system for a heat treatment furnace, further comprising:

[0140] A communication building module, used to initialize the component monitoring device involved in the first online monitoring and the space monitoring device involved in the second online monitoring, and to build a communication set;

[0141] The communication transmission module is used to bind each communication interface in the communication set with a possible communication event of the corresponding device in the current set state, and after the binding is completed, the monitoring result is transmitted by communication.

[0142] In this embodiment, the purpose of initialization is to effectively establish a communication connection.

[0143] In this embodiment, the possible communication event is to determine the communication protocol and implement communication transmission.

[0144] The beneficial effects of the above technical solution are: initializing the device, building a communication set, and then binding it with possible communication events, facilitating subsequent communication transmission, and realizing effective monitoring of the operating data of the heat treatment furnace.

[0145] The present invention provides an online monitoring system for a heat treatment furnace, wherein the communication transmission module comprises:

[0146] An information acquisition unit, used to acquire historical monitoring information of different devices involved in a working state whose matching degree with the current set state is greater than a preset degree;

[0147] A table construction unit, used to extract all monitoring reference information consistent with each device involved in the current set state from all historical monitoring information, and construct an event mapping table for the device, wherein the event mapping table includes the event occurrence probability, the probability of causing an abnormality, and the probability of associated abnormality for each event;

[0148] An importance assigning unit, configured to assign communication importance to each device involved in the current setting state based on the event mapping table;

[0149] The protocol binding unit is used to combine the event mapping table of the corresponding device with the communication importance to bind the corresponding communication security protocol to the corresponding device and perform communication transmission of the monitoring results.

[0150] In this embodiment, the preset value is 0.6, and the matching degree ranges from 0 to 1.

[0151] In this embodiment, the historical monitoring information is obtained based on a historical monitoring database of the heat treatment furnace under different working conditions.

[0152] In this embodiment, the purpose of acquiring the event mapping table is to determine whether the corresponding device is intact. The monitoring result of the heat treatment furnace obtained by monitoring is accurate only when there is no abnormality in the device.

[0153] In this embodiment, communication importance=n11×(1-max(event occurrence probability, abnormality causing probability, associated abnormality probability)), where n11 is the number of events in the corresponding event mapping table.

[0154] In this embodiment, the communication security protocol is obtained based on the combination result-protocol mapping table. The table is based on different event mapping tables and communication importance, and the protocol combined therewith can be directly obtained.

[0155] The beneficial effect of the above technical solution is: by acquiring historical monitoring information to construct an event mapping table and then calculating the communication importance, and then determining the communication security protocol through matching, so as to achieve effective transmission of component monitoring data by the device.

[0156] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An online monitoring system for a heat treatment furnace, characterized in that: include: A component determination module, used to determine the working components involved in different working states of the heat treatment furnace; A monitoring deployment module is used to determine the working weight and working attributes of the corresponding working component in different working states according to the working conditions of each working component based on different working states, and deploy a component monitoring set and a spatial monitoring set of the location of the corresponding working component; An online monitoring module, for controlling the component monitoring device in the component monitoring set that matches the current set state to perform a first online monitoring on the corresponding working component and the space monitoring device in the space monitoring set that matches the current set state to perform a second online monitoring on the working space of the corresponding working component according to the current set state of the heat treatment furnace; The abnormality processing module is used to analyze and process the first online monitoring result and the second online monitoring result, determine the current abnormality of the heat treatment furnace and perform abnormality processing.

2. The online monitoring system for a heat treatment furnace according to claim 1, characterized in that: The component determination module includes: A model acquisition unit, used to acquire the furnace model of the heat treatment furnace; A state matching unit, used for matching the working state of the heat treatment furnace from a preset database according to the furnace model; The component matching unit is used to match the working components involved in each working state based on the state-component operation mapping table.

3. The online monitoring system for a heat treatment furnace according to claim 1, characterized in that: The monitoring deployment module includes: A first matrix construction unit is used to extract a working vector of each working component in each working state from a work log of the heat treatment furnace, and construct a working matrix of the heat treatment furnace in the corresponding working state; A second matrix construction unit is used to extract a standard vector of each working component in each working state from a standard database, and construct a standard matrix of the heat treatment furnace in a corresponding working state; An offset weight determination unit is used to compare the working matrix under the same working state with the standard matrix for the same elements, determine the maximum difference and variance in each row vector in the corresponding working matrix, and calculate the row offset coefficient of the corresponding row vector; Among them, P1 i1 X1 represents the row offset coefficient of the i1th row vector; max，i1 represents the maximum difference of the i1th row vector, and the difference of each element in each row vector is the absolute value of the difference between the elements; represents the variance of the i1th row vector; X1 ave，i1 represents the average difference of the i1th row vector; Based on all the row deviation coefficients, determining the state deviation coefficient of the heat treatment furnace in the corresponding working state; Among them, P2 represents the state shift coefficient under the corresponding working state; n1 represents the number of row vectors in the working matrix under the corresponding working state; σ2 2 Indicates all P1 in the corresponding working matrix i1 Variance; h1 represents the variance based on all The fitted variance of the constructed variance dispersion plot; h2 represents all The average variance of the probability of satisfying the normal distribution; A coefficient determination unit, used for obtaining a characteristic parameter set of each row vector in the corresponding working matrix to determine a difference characteristic to assign an influence coefficient to the corresponding row vector, and calculating the coefficient sum of all influence coefficients; Among them, Y1 i1 Represents the characteristic parameter set of the i1th row vector; X1 j1 represents the value of the j1th element in the i1th row vector, and the value of j1 is 1, 2, 3, ..., n2; n01 represents the value of the i1th row vector that satisfies X1 j1 ≥X1 ave，i1 The number of elements of ; A number determination unit is used to obtain the number of first elements whose difference values ​​are greater than 0, the number of second elements whose difference values ​​are less than 0, and the number of third elements whose difference values ​​are equal to 0 in each row vector in the corresponding working matrix; and calculate the main coefficient and the secondary coefficient of the corresponding row vector according to the number of first elements, the number of second elements, and the number of third elements; A compromise unit, configured to obtain a working weight of a corresponding working component under the same working state based on a row offset coefficient, a state offset coefficient, a standard weight under a corresponding working state, and a coefficient sum, and in combination with a compromise condition of the primary coefficient and the secondary coefficient; The attribute determination unit is used to obtain the working attribute according to the standard attribute of each working component under the same working state and in combination with the component working deviation.

4. The online monitoring system for a heat treatment furnace according to claim 3, characterized in that: The monitoring deployment module further includes: A first establishing unit, configured to establish a first weight range based on the working weight of each working component in each working state; A second establishing unit, configured to establish a first attribute range based on the working attribute of each working component in each working state; A monitoring value calculation unit, used to establish a minimum monitoring value and a maximum monitoring value of a corresponding working component in a corresponding working state according to the first weight range and the first attribute range; A scheme acquisition unit, configured to deploy a monitoring scheme to a corresponding working component according to the minimum monitoring value and the maximum monitoring value, and based on all monitoring schemes of the same working component; The set determination unit is used to retrieve the matching own position and spatial position from the type-position-device mapping table according to the device monitoring type of each monitoring device in all monitoring schemes, and determine the component monitoring set of the corresponding working component and the spatial monitoring set of the location.

5. The online monitoring system for a heat treatment furnace according to claim 1, characterized in that: The online monitoring module comprises: A state acquisition unit, used to acquire the current setting state of the heat treatment furnace, wherein the current setting state is a mode setting performed by a staff before the heat treatment furnace is operated; The monitoring control unit is used to control the online monitoring of the device in the monitoring deployment situation corresponding to the state with the highest similarity to the current set state from all working states.

6. The online monitoring system for a heat treatment furnace according to claim 1, characterized in that: The exception handling module comprises: A sorting unit, used to arrange the first online monitoring result and the second online monitoring result in order of position according to the processing thread of the heat treatment furnace to obtain an initial monitoring result; A comparison unit, used to compare the initial monitoring result with the standard operation result of the current set state, obtain an operation difference result, and construct a difference framework; A parsing unit, used for performing a framework analysis on the difference framework to obtain a current abnormality of the heat treatment furnace; The means determining unit is used to determine the exception handling means according to the exception type and the exception location of the current exception.

7. The online monitoring system for a heat treatment furnace according to claim 1, characterized in that: Also includes: A communication building module, used to initialize the component monitoring device involved in the first online monitoring and the space monitoring device involved in the second online monitoring, and to build a communication set; The communication transmission module is used to bind each communication interface in the communication set with a possible communication event of the corresponding device in the current set state, and after the binding is completed, the monitoring result is transmitted by communication.

8. The online monitoring system for a heat treatment furnace according to claim 7, characterized in that: The communication transmission module comprises: An information acquisition unit, used to acquire historical monitoring information of different devices involved in a working state whose matching degree with the current set state is greater than a preset degree; A table construction unit, used to extract all monitoring reference information consistent with each device involved in the current set state from all historical monitoring information, and construct an event mapping table for the device, wherein the event mapping table includes the event occurrence probability, the probability of causing an abnormality, and the probability of associated abnormality for each event; An importance assigning unit, configured to assign communication importance to each device involved in the current setting state based on the event mapping table; The protocol binding unit is used to combine the event mapping table of the corresponding device with the communication importance to bind the corresponding communication security protocol to the corresponding device and perform communication transmission of the monitoring results.

9. The online monitoring system for a heat treatment furnace according to claim 3, characterized in that: The compromise unit comprises: Among them, bq represents the standard weight under the corresponding working state; sumy1 represents the coefficient sum under the corresponding working state; y1 i1 represents the influence coefficient of the i1th row vector in the working matrix under the corresponding working state; m01 represents the corresponding first number; m02 represents the corresponding second number; m03 represents the corresponding third number; T1 represents the working weight of the corresponding working component under the same working state; represents the main coefficient; Represents the minor coefficient.

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