An intelligent Internet of Things power distribution cabinet

Abstract

The present invention discloses an intelligent Internet of Things power distribution cabinet, comprising a cabinet body, wherein the upper and lower parts of the cabinet body are both provided with rainproof and heat dissipation components which are symmetrically arranged up and down; the rainproof and heat dissipation components arranged on the upper part of the cabinet body comprise a plurality of fixed slot plates and a plurality of movable slot plates, and the two ends of the fixed slot plates are welded to the openings on the upper part of the cabinet body; the intelligent Internet of Things power distribution cabinet adopts the rainproof and heat dissipation components which are symmetrically arranged up and down, and an electric push rod and an air diffusion fan are arranged on the inner side of the cabinet body, so as to realize automatic adjustment of the heat dissipation effect, improve the safety, reliability and intelligence of the power distribution cabinet, effectively protect the electrical components inside the power distribution cabinet, improve the operation efficiency and maintenance convenience of the power distribution cabinet, realize remote monitoring and intelligent management of the power distribution cabinet by utilizing the Internet of Things technology, and greatly improve the reliability and efficiency of the power distribution system.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution cabinets, and in particular to an intelligent Internet of Things power distribution cabinet. Background Art

[0002] In the power system, the distribution cabinet is a key device for receiving and distributing electric energy. However, due to the complex working environment of the electrical components inside the distribution cabinet, they are easily affected by environmental factors such as temperature and humidity, which can lead to performance degradation or even failure of the distribution cabinet. Therefore, temperature monitoring and control of the distribution cabinet is of great significance.

[0003] With the continuous development of science and technology, the Internet of Things technology has gradually penetrated into various industries, including the power industry. At present, some patents have proposed temperature monitoring and control methods for distribution cabinets. For example, some patents install temperature sensors in the distribution cabinet to monitor temperature parameters in real time and issue alarms based on preset temperature thresholds. However, these methods have some problems. First, traditional temperature monitoring methods can only provide discrete temperature data and cannot accurately reflect the temperature distribution in the distribution cabinet. Secondly, traditional temperature control methods are usually based on fixed thresholds and cannot be flexibly adjusted according to actual temperature changes. In addition, existing temperature monitoring and control methods often lack the ability to respond to and process abnormal temperature signals in a timely manner.

[0004] Based on this, an intelligent Internet of Things distribution cabinet is proposed to improve the accuracy and flexibility of temperature monitoring and control of the distribution cabinet. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent Internet of Things power distribution cabinet to solve the technical problems raised in the background technology.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An intelligent Internet of Things power distribution cabinet, comprising a cabinet body with an open structure at the upper and lower parts, wherein the upper and lower parts of the cabinet body are provided with rainproof and heat dissipation components symmetrically arranged up and down;

[0008] The rainproof and heat dissipation component arranged on the upper part of the cabinet includes a plurality of fixed slot plates and a plurality of movable slot plates, and the two ends of the fixed slot plates are welded to the openings on the upper part of the cabinet;

[0009] A plurality of movable slot plates are connected to form an integral movable slot plate group through a connecting rod, and the movable slot plate group is slidably arranged at the opening on the upper part of the cabinet, an electric push rod and an air diffuser are arranged on the inner side of the cabinet, and the output end of the electric push rod is fixedly connected to the movable slot plate group through a connecting piece;

[0010] An intelligent controller is also provided inside the cabinet, and the electric push rod and the cooling fan are electrically connected to the intelligent controller. The intelligent controller is used to control the start and stop of the electric push rod and the cooling fan according to the temperature parameters and humidity parameters in the cabinet detected by the temperature sensor and the humidity sensor.

[0011] As a further solution of the present invention: the cross-sections of the fixed slot plate and the movable slot plate are both C-shaped structures, and the fixed slot plate and the movable slot plate are staggered and cross-arranged, and a water flow outlet is opened at the connection between the end of the fixed slot plate and the cabinet;

[0012] The inner sides of the fixed slot plate and the movable slot plate are both provided with sealing strips.

[0013] As a further solution of the present invention: the intelligent controller includes:

[0014] The data monitoring terminal is used to monitor and obtain the temperature and humidity parameters in the power distribution cabinet in real time through the Internet of Things technology;

[0015] The data analysis end is used to analyze the temperature parameters and / or humidity parameters and obtain the abnormal state of the corresponding temperature and / or humidity in the power distribution cabinet, and then generate a corresponding abnormal signal according to the abnormal result, and transmit the corresponding abnormal signal to the control execution end;

[0016] The control execution end is used to control the start and stop of the electric push rod and the diffuser fan according to the corresponding abnormal signal;

[0017] As a further solution of the present invention: the data analysis end includes:

[0018] A data processing unit is used to calculate the fault temperature analysis values ​​of multiple standard time nodes in a specified period according to the temperature parameters of multiple distribution cabinets at multiple preset standard time nodes in a specified period before the failure of the multiple distribution cabinets, and draw a corresponding temperature fault matching diagram according to the fault temperature analysis value, and then transmit the temperature fault matching diagram to the data analysis unit, wherein the time difference between multiple adjacent standard time nodes is unified;

[0019] The data processing unit is also used to calculate normal temperature analysis values ​​of multiple standard time nodes in a specified period according to the temperature parameters of multiple distribution cabinets at multiple preset standard time nodes in a specified period during normal operation of the multiple distribution cabinets and / or after the distribution cabinets fail and undergo maintenance;

[0020] Then, a temperature comparison value is obtained based on the fault temperature analysis value and the normal temperature analysis value, and the temperature comparison value is transmitted to the data analysis unit;

[0021] A data analysis unit is used to obtain the current temperature parameter through the data monitoring end according to a preset analysis time node, and compare it with the temperature comparison value, perform abnormal analysis according to the result that the current temperature parameter is less than and / or greater than or equal to the temperature comparison value, generate a corresponding abnormal signal according to the abnormal analysis result, and transmit the corresponding abnormal signal to the control execution end;

[0022] The signal transmission unit is used to transmit the temperature abnormality signal to the control execution end.

[0023] As a further solution of the present invention: the specific analysis method of the data processing unit is as follows:

[0024] SA1. Obtain temperature parameters of multiple power distribution cabinets at multiple preset standard time nodes within a specified period before a failure occurs;

[0025] SA2, mark it as GW g，f , g = 1, 2, ... t, t represents the number of power distribution cabinets, f = 1, 2, ... r, r represents the number of preset standard time nodes within a specified period, where 1, 2, ... r are sorted in the time sequence of the standard time nodes;

[0026] SA3, set the value of f to 1, and then set all GW g，1 Import the variance calculation formula and calculate the discrete degree value of the temperature parameters of each distribution cabinet at the same standard time node;

[0027] SA4. Compare the discrete degree value obtained in step SA3 with the preset discrete degree threshold:

[0028] If the discrete value is greater than the discrete threshold, it means that the discrete values ​​of the temperature parameters of each distribution cabinet at the same standard time node are large, and then according to |GW g，1 -GWp 1 | Delete the corresponding GW in order from large to small g，1 The remaining discrete degree values ​​are calculated accordingly until the discrete degree value is less than or equal to the discrete degree threshold;

[0029] Among them, GWp 1 Indicates the average value of the temperature parameters of each distribution cabinet at the same standard time node when participating in the calculation of the corresponding discrete degree value;

[0030] SA5. When the discrete degree value is less than or equal to the discrete degree threshold, the temperature parameter corresponding to the discrete degree value is calculated at the standard time node, and the average value of the corresponding temperature parameter is obtained, and then the value is marked as the fault temperature analysis value;

[0031] SA6, let the value of f be 2, 3, ..., r, and calculate the fault temperature analysis values ​​corresponding to other standard time nodes according to the subsequent steps of step SA3, and steps SA4 and SA5;

[0032] SA7, select the fault temperature analysis value when f = 1, and record it as the analysis reference value FJ, and record the fault temperature analysis values ​​corresponding to all standard time nodes as FX f ;

[0033] SA8, through FC f =FX f -FJ, calculate the difference FC between the fault temperature analysis value and the analysis benchmark value corresponding to each standard time node f ;

[0034] SA9, according to each FC f Draw a line graph and record the line graph as a temperature fault matching graph.

[0035] As a further solution of the present invention: the specific processing method of the normal temperature analysis value is the same as the processing method of the fault temperature analysis value in steps SA2-SA5.

[0036] As a further solution of the present invention: the temperature comparison value is calculated as follows:

[0037] All fault temperature analysis values ​​are taken as set A;

[0038] At the same time, all normal temperature analysis values ​​are taken as set B;

[0039] Then calculate the intersection between set A and set B;

[0040] like That is, the intersection of A and B is not empty, and then the fault temperature analysis value and the normal temperature analysis value in the intersection are summarized into the set B, and then a fault temperature analysis value and / or a normal temperature analysis value with the smallest value is selected from the set B and used as the temperature comparison value;

[0041] like That is, the intersection of A and B is empty, and then a fault temperature analysis value with the smallest value is selected from set B and used as the temperature comparison value;

[0042] As a further solution of the present invention: the analysis method of the data analysis unit is as follows:

[0043] SS1. Obtain the temperature parameter of the current time node through the data monitoring terminal, and then compare it with the temperature comparison value:

[0044] If the current temperature parameter is greater than or equal to the temperature comparison value, then the temperature parameters of the subsequent multiple time nodes are calculated one by one according to the time difference between the adjacent standard time nodes, and then the temperature parameter of the current time node is recorded as the comparison reference value BJ;

[0045] Then through BC f1 =BX f1 -BJ, calculate the difference BC between the temperature parameter corresponding to each standard time node and the comparison benchmark value f1 , where f1=1, 2, ..., r1, r1 represents the number of the current time node and the subsequent multiple time nodes, and r1<r;

[0046] Then BC f1 Draw a line graph and record it as a temperature comparison and matching graph, and enter step SS2;

[0047] SS2: Perform fusion matching analysis on the temperature comparison matching graph and the temperature fault matching graph in the following manner:

[0048] A broken line node is randomly selected from the temperature comparison matching graph, and then the broken line node is overlapped with each broken line node in the temperature fault matching graph one by one, and each broken line node in the temperature comparison matching graph corresponds to a broken line node in the temperature fault matching graph;

[0049] Take the example where the broken line node coincides with a broken line node in the temperature fault matching graph;

[0050] Then, each broken line node in the temperature comparison matching graph is subtracted from the broken line node corresponding to the temperature fault matching graph to obtain the corresponding difference, and then the number of differences whose values ​​are positive and whose differences are 0 is obtained, and the number is recorded as v1;

[0051] At the same time, the difference value with negative value is extracted;

[0052] Then, the absolute value of the difference that will extract the negative value is obtained, and the absolute value of the difference is compared with the preset difference threshold, and then the number of differences whose corresponding absolute value is greater than or equal to the difference threshold is obtained, and the number is recorded as v2;

[0053] Where v1+v2≤r1;

[0054] Then, by β = / r1, the proportional determination coefficient β is obtained;

[0055] Afterwards, the ratio determination coefficient β is compared with the preset ratio threshold βy:

[0056] If β ≥ βy, it means that the current temperature is abnormal, and then a temperature abnormality signal is generated;

[0057] If β<βy, the broken line node is overlapped with other broken line nodes in the temperature fault matching diagram one by one, and then the corresponding proportional determination coefficient is obtained according to the above method. When the broken line node is fused and matched with all the broken line nodes in the temperature fault matching diagram one by one, and there is no β≥βy, it means that the current temperature detected by the data monitoring end is wrong, and the current temperature in the distribution cabinet is normal, and no temperature abnormality signal is generated.

[0058] As a further solution of the present invention: in step SS1, if the current temperature parameter is less than the temperature comparison value, the next temperature parameter is obtained through the data monitoring terminal according to the preset analysis time node, and is further compared with the temperature comparison value.

[0059] Beneficial effects of the present invention:

[0060] The present invention adopts rainproof and heat dissipation components that are symmetrically arranged up and down, which can effectively prevent rainwater from entering the cabinet, protect the safe operation of the equipment, and extend the service life of the equipment;

[0061] The present invention provides an electric push rod and an air diffuser fan inside the cabinet, and the output end of the electric push rod is fixedly connected to the movable slot plate group through a connecting piece, so that the heat dissipation effect can be automatically adjusted. The movable slot plate group is slidably arranged at the opening on the upper part of the cabinet, and the position of the movable slot plate can be adjusted as needed to achieve flexible heat dissipation control, improve the operation efficiency of the equipment, and reduce the workload of manual operation. The intelligent Internet of Things power distribution cabinet has a reasonable design, a compact structure, is easy to maintain, and improves the reliability and stability of the equipment.

[0062] The present invention enables the data monitoring terminal to monitor and obtain the temperature parameters in the power distribution cabinet in real time, so as to timely discover abnormal temperature conditions and improve the monitoring efficiency of the power distribution cabinet.

[0063] In the present invention, the data analysis end compares and analyzes the temperature parameters with the temperature comparison value, and can accurately determine whether the power distribution cabinet is in a normal state, thereby avoiding the occurrence of misjudgment and missed judgment.

[0064] The present invention can improve the safety, reliability and intelligence of the power distribution cabinet, effectively protect the electrical components inside the power distribution cabinet, improve the operating efficiency and maintenance convenience of the power distribution cabinet, and use the Internet of Things technology to realize remote monitoring and intelligent management of the power distribution cabinet, thereby greatly improving the reliability and efficiency of the power distribution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The present invention will be further described below in conjunction with the accompanying drawings.

[0066] Figure 1 It is a structural cross-sectional view of an intelligent Internet of Things power distribution cabinet of the present invention;

[0067] Figure 2 The present invention Figure 1 A partial enlarged view of the middle A;

[0068] Figure 3 It is a system block diagram of an intelligent Internet of Things power distribution cabinet of the present invention.

[0069] Figure 4 It is a system block diagram of a data analysis terminal of an intelligent Internet of Things power distribution cabinet of the present invention.

[0070] In the figure: 1. Cabinet body; 2. Fixed slot plate; 3. Movable slot plate; 4. Sealing strip; 5. Electric push rod; 6. Exhaust fan. DETAILED DESCRIPTION

[0071] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] Embodiment 1

[0073] See also Figure 1 As shown, the present invention is an intelligent Internet of Things power distribution cabinet, comprising:

[0074] A cabinet body 1, wherein the upper and lower parts of the cabinet body 1 are both open structures;

[0075] The upper and lower parts of the cabinet 1 are provided with rainproof and heat dissipation components symmetrically arranged up and down;

[0076] Taking the rainproof and heat dissipation component arranged on the upper part of the cabinet 1 as an example, it includes a plurality of fixed slot plates 2 and a plurality of movable slot plates 3, and the cross sections of the fixed slot plates 2 and the movable slot plates 3 are both C-shaped structures;

[0077] The notches of the plurality of fixed slot plates 2 face upward, and the two ends of the fixed slot plates 2 are welded to the openings at the upper portion of the cabinet 1;

[0078] A water outlet is provided at the connection between the end of the fixed groove plate 2 and the cabinet body 1;

[0079] The openings of the plurality of movable slot plates 3 face downwards, and the plurality of movable slot plates 3 are connected to form an integral movable slot plate group by connecting rods, and the movable slot plate group is slidably arranged at the opening of the upper part of the cabinet 1, and the fixed slot plates 2 and the movable slot plates 3 are staggered and cross-arranged;

[0080] The inner sides of the fixed slot plate 2 and the movable slot plate 3 are both provided with sealing strips 4;

[0081] By providing sealing strips 4 on the inner sides of the fixed slot plate 2 and the movable slot plate 3, rainwater can be effectively prevented from penetrating through the gaps, thereby improving the waterproof performance of the equipment.

[0082] In this embodiment, by setting a fixed slot plate 2 and a movable slot plate 3, the power distribution cabinet can effectively dissipate heat. At the same time, on rainy days, rainwater is collected by the fixed slot plate 2 with a C-shaped structure and discharged through the fixed slot plate 2, which can effectively prevent rainwater from entering and effectively improve the heat dissipation effect of the equipment.

[0083] An electric push rod 5 and an air dispersing fan 6 are provided on the inner side of the cabinet 1, and the output end of the electric push rod 5 is fixedly connected to the movable slot plate group through a connecting piece.

[0084] This embodiment adopts rainproof and heat dissipation components that are symmetrically arranged up and down, which can effectively prevent rainwater from entering the cabinet, protect the safe operation of the equipment, and extend the service life of the equipment.

[0085] This embodiment provides an electric push rod and an air diffuser fan on the inside of the cabinet. The output end of the electric push rod is fixedly connected to the movable slot plate group through a connecting piece, so that the heat dissipation effect can be automatically adjusted. The movable slot plate group is slidably set at the opening on the upper part of the cabinet. The position of the movable slot plate can be adjusted as needed to achieve flexible heat dissipation control, improve the operating efficiency of the equipment, and reduce the workload of manual operation. The intelligent Internet of Things distribution cabinet has a reasonable design, compact structure, and is easy to maintain, which improves the reliability and stability of the equipment.

[0086] Embodiment 2

[0087] See also Figure 1-Figure 4 As shown, as the second embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the technical solution of this embodiment is based on the first embodiment, and this embodiment also includes:

[0088] An intelligent controller is also provided inside the cabinet 1, and the electric push rod 5 and the air diffuser 6 are electrically connected to the intelligent controller;

[0089] The intelligent controller is used to control the start and stop of the electric push rod 5 and the cooling fan 6 according to the temperature parameters and humidity parameters in the cabinet detected by the temperature sensor and the humidity sensor;

[0090] The data monitoring terminal is used to monitor and obtain the temperature parameters in the power distribution cabinet in real time through the Internet of Things technology. It can detect temperature anomalies in time and improve the monitoring efficiency of the power distribution cabinet.

[0091] In this embodiment, the temperature parameter is obtained by a temperature sensor disposed inside the cabinet 1;

[0092] The data analysis end includes:

[0093] A data processing unit is used to calculate the fault temperature analysis values ​​of multiple standard time nodes in a specified period according to the temperature parameters of multiple distribution cabinets at multiple preset standard time nodes in a specified period before the failure of the multiple distribution cabinets, and draw a corresponding temperature fault matching diagram according to the fault temperature analysis values, and then transmit the temperature fault matching diagram to the data analysis unit;

[0094] Among them, the time difference between multiple adjacent standard time nodes is unified;

[0095] The specific processing methods are as follows:

[0096] SA1. Obtain temperature parameters of multiple power distribution cabinets at multiple preset standard time nodes within a specified period before a failure occurs;

[0097] SA2, mark it as GW g，f , g = 1, 2, ... t, t represents the number of power distribution cabinets, f = 1, 2, ... r, r represents the number of preset standard time nodes within a specified period, where 1, 2, ... r are sorted in the time sequence of the standard time nodes;

[0098] SA3, set the value of f to 1, and then set all GW g，1 Import the variance calculation formula and calculate the discrete degree value of the temperature parameters of each distribution cabinet at the same standard time node;

[0099] SA4. Compare the discrete degree value obtained in step SA3 with the preset discrete degree threshold:

[0100] If the discrete value is greater than the discrete threshold, it means that the discrete values ​​of the temperature parameters of each distribution cabinet at the same standard time node are large, and then according to |GW g，1 -GWp 1 | Delete the corresponding GW in order from large to small g，1 The remaining discrete degree values ​​are calculated accordingly until the discrete degree value is less than or equal to the discrete degree threshold;

[0101] Among them, GWp 1 Indicates the average value of the temperature parameters of each distribution cabinet at the same standard time node when participating in the calculation of the corresponding discrete degree value;

[0102] In this embodiment, the corresponding deleted GW g，f The value means that the switchboard is not affected by temperature when a fault occurs;

[0103] SA5. When the discrete degree value is less than or equal to the discrete degree threshold, the temperature parameter corresponding to the discrete degree value is calculated at the standard time node, and the average value of the corresponding temperature parameter is obtained, and then the value is marked as the fault temperature analysis value;

[0104] SA6, let the value of f be 2, 3, ..., r, and calculate the fault temperature analysis values ​​corresponding to other standard time nodes according to the subsequent steps of step SA3, and steps SA4 and SA5;

[0105] SA7, select the fault temperature analysis value when f = 1, and record it as the analysis reference value FJ, and record the fault temperature analysis values ​​corresponding to all standard time nodes as FX f ;

[0106] SA8, through FC f =FX f -FJ, calculate the difference FC between the fault temperature analysis value and the analysis benchmark value corresponding to each standard time node f ;

[0107] SA9, according to each FC f Draw a line graph, and record the line graph as a temperature fault matching graph;

[0108] The data processing unit is also used to calculate the normal temperature analysis values ​​of multiple standard time nodes in a specified period according to the temperature parameters of multiple distribution cabinets at multiple preset standard time nodes in a specified period during normal operation of the multiple distribution cabinets and / or after the distribution cabinets fail and undergo maintenance, and the specific method is the same as that of steps SA2-SA5;

[0109] SA10, take all fault temperature analysis values ​​as set A;

[0110] At the same time, all normal temperature analysis values ​​are taken as set B;

[0111] Then calculate the intersection between set A and set B;

[0112] like That is, the intersection of A and B is not empty, and then the fault temperature analysis value and the normal temperature analysis value in the intersection are summarized into the set B, and then a fault temperature analysis value and / or a normal temperature analysis value with the smallest value is selected from the set B and used as the temperature comparison value;

[0113] like That is, the intersection of A and B is empty, and then a fault temperature analysis value with the smallest value is selected from set B and used as the temperature comparison value;

[0114] The temperature comparison value is then transmitted to a data analysis unit;

[0115] A data analysis unit is used to obtain the current temperature parameter through the data monitoring terminal according to a preset analysis time node, and compare it with the temperature comparison value, and perform abnormal analysis according to the result that the current temperature parameter is less than and / or greater than or equal to the temperature comparison value;

[0116] The time difference between multiple adjacent analysis time nodes is unified, and the time difference between adjacent analysis time nodes is u times the time difference between adjacent standard time nodes, and u is a multiple value preset by the operation and maintenance management personnel;

[0117] The method is as follows:

[0118] SS1. Obtain the temperature parameter of the current time node through the data monitoring terminal, and then compare it with the temperature comparison value:

[0119] If the current temperature parameter is less than the temperature comparison value, the next temperature parameter is obtained through the data monitoring terminal according to the preset analysis time node, and it is compared with the temperature comparison value;

[0120] If the current temperature parameter is greater than or equal to the temperature comparison value, then the temperature parameters of the subsequent multiple time nodes are calculated one by one according to the time difference between the adjacent standard time nodes, and then the temperature parameter of the current time node is recorded as the comparison reference value BJ;

[0121] Then through BC f1 =BX f1 -BJ, calculate the difference BC between the temperature parameter corresponding to each standard time node and the comparison benchmark value f1 , where f1=1, 2, ..., r1, r1 represents the number of the current time node and the subsequent multiple time nodes, and r1<r;

[0122] Then BC f1 Draw a line graph and record it as a temperature comparison and matching graph, and enter step SS2;

[0123] SS2: Perform fusion matching analysis on the temperature comparison matching graph and the temperature fault matching graph in the following manner:

[0124] A broken line node is randomly selected from the temperature comparison matching graph, and then the broken line node is overlapped with each broken line node in the temperature fault matching graph one by one, and each broken line node in the temperature comparison matching graph corresponds to a broken line node in the temperature fault matching graph;

[0125] Take the example where the broken line node coincides with a broken line node in the temperature fault matching graph;

[0126] Then, each broken line node in the temperature comparison matching graph is subtracted from the broken line node corresponding to the temperature fault matching graph to obtain the corresponding difference, and then the number of differences whose values ​​are positive and whose differences are 0 is obtained, and the number is recorded as v1;

[0127] At the same time, the difference value with negative value is extracted;

[0128] Then, the absolute value of the difference that will extract the negative value is obtained, and the absolute value of the difference is compared with the preset difference threshold, and then the number of differences whose corresponding absolute value is greater than or equal to the difference threshold is obtained, and the number is recorded as v2;

[0129] Where v1+v2≤r1;

[0130] Then, the proportional determination coefficient β is obtained by β=v1+v2 / r1;

[0131] Afterwards, the ratio determination coefficient β is compared with the preset ratio threshold βy:

[0132] If β ≥ βy, it means that the current temperature is abnormal, and then a temperature abnormality signal is generated;

[0133] If β<βy, the broken line node is overlapped with other broken line nodes in the temperature fault matching diagram one by one, and then the corresponding proportional determination coefficient is obtained according to the above method. When the broken line node is fused and matched with all the broken line nodes in the temperature fault matching diagram one by one, and there is no β≥βy, it means that the current temperature detected by the data monitoring end is wrong, and the current temperature in the power distribution cabinet is normal, and no temperature abnormality signal is generated;

[0134] By comparing and analyzing the temperature parameters with the temperature comparison values, it is possible to accurately determine whether the power distribution cabinet is in a normal state, thus avoiding misjudgment and missed judgment.

[0135] A signal transmission unit, used for transmitting the temperature abnormality signal to the control execution end;

[0136] The control execution end is used to control the start and stop of the electric push rod 5 and the air diffuser fan 6 according to the temperature abnormality signal;

[0137] Specifically, when the control execution end receives a temperature abnormality signal, the electric push rod 5 is controlled to extend, thereby pushing the movable slot plate group upward, so that a flow gap is formed between the fixed slot plate 2 and the movable slot plate 3, and the air dissipation fan 6 is controlled to be turned on, so that the heat inside the power distribution cabinet is discharged out of the cabinet through the flow gap formed between the fixed slot plate 2 and the movable slot plate 3;

[0138] The data monitoring terminal then monitors and obtains the temperature parameters in the power distribution cabinet in real time;

[0139] The data analysis end compares the temperature parameter with the temperature comparison value:

[0140] When the temperature parameter is greater than or equal to the temperature comparison value, the electric push rod 5 remains unchanged and the air diffuser 6 continues to operate;

[0141] When the temperature parameter is less than the temperature comparison value, the electric push rod 5 is controlled to shrink and the air diffuser 6 stops running, so that the side of the movable slot plate 3 contacts the sealing strip 4 in the fixed slot plate 2, and the side of the fixed slot plate 2 contacts the sealing strip 4 in the movable slot plate 3, so that a sealing structure is formed between the movable slot plate 3 and the fixed slot plate 2, thereby preventing external dust or humid gas from entering the interior of the distribution cabinet and affecting the service life of the electrical components inside the distribution cabinet;

[0142] This embodiment can improve the safety, reliability and intelligence of the power distribution cabinet, effectively protect the electrical components inside the power distribution cabinet, and improve the operating efficiency and maintenance convenience of the power distribution cabinet.

[0143] Embodiment 3

[0144] As the third embodiment of the present invention, when the present application is specifically implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments, and the difference between the technical solution of this embodiment and the first and second embodiments is that, in this embodiment;

[0145] The data monitoring terminal is also used to monitor and obtain humidity parameters in the power distribution cabinet in real time through the Internet of Things technology;

[0146] In this embodiment, the humidity parameters are obtained by humidity sensors disposed inside the cabinet 1;

[0147] Then, according to the method of the second embodiment, the corresponding humidity abnormality signal is obtained through the data analysis end, and then the start and stop of the electric push rod 5 and the air diffuser fan 6 are controlled according to the humidity abnormality signal through the control execution end.

[0148] Embodiment 4

[0149] As the fourth embodiment of the present invention, when the present application is specifically implemented, compared with the first, second and third embodiments, the technical solution of this embodiment is to combine and implement the solutions of the above-mentioned first, second and third embodiments.

[0150] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent Internet of Things power distribution cabinet, comprising a cabinet body (1) with an opening structure at both the upper and lower parts, characterized in that: The upper and lower parts of the cabinet (1) are both provided with rainproof and heat dissipation components symmetrically arranged up and down; The rainproof and heat dissipation component arranged on the upper part of the cabinet (1) comprises a plurality of fixed slot plates (2) and a plurality of movable slot plates (3), and the two ends of the fixed slot plates (2) are welded to the openings on the upper part of the cabinet (1); A plurality of movable slot plates (3) are connected to form an integral movable slot plate group via a connecting rod, and the movable slot plate group is slidably arranged at an opening at the upper portion of the cabinet (1), an electric push rod (5) and an air diffuser fan (6) are arranged on the inner side of the cabinet (1), and an output end of the electric push rod (5) is fixedly connected to the movable slot plate group via a connecting piece; An intelligent controller is also provided inside the cabinet (1), and the electric push rod (5) and the cooling fan (6) are electrically connected to the intelligent controller, and the intelligent controller is used to control the start and stop of the electric push rod (5) and the cooling fan (6) according to the temperature parameters and humidity parameters in the cabinet detected by the temperature sensor and the humidity sensor; The intelligent controller comprises: The data monitoring terminal is used to monitor and obtain the temperature and humidity parameters in the power distribution cabinet in real time through the Internet of Things technology; The data analysis end is used to analyze the temperature parameters and / or humidity parameters and obtain the abnormal state of the corresponding temperature and / or humidity in the power distribution cabinet, and then generate a corresponding abnormal signal according to the abnormal result, and transmit the corresponding abnormal signal to the control execution end; The data analysis end includes: A data processing unit is used to calculate the fault temperature analysis values ​​of multiple standard time nodes in a specified period according to the temperature parameters of multiple distribution cabinets at multiple preset standard time nodes in a specified period before the failure of the multiple distribution cabinets, and draw a corresponding temperature fault matching diagram according to the fault temperature analysis value, and then transmit the temperature fault matching diagram to the data analysis unit, wherein the time difference between multiple adjacent standard time nodes is unified; The data processing unit is also used to calculate normal temperature analysis values ​​of multiple standard time nodes in a specified period according to the temperature parameters of multiple distribution cabinets at multiple preset standard time nodes in a specified period during normal operation of the multiple distribution cabinets and / or after the distribution cabinets fail and undergo maintenance; The specific analysis method of the data processing unit is as follows: SA1. Obtain temperature parameters of multiple power distribution cabinets at multiple preset standard time nodes within a specified period before a failure occurs; SA2, mark it as GW g，f , g = 1, 2, ... t, t represents the number of power distribution cabinets, f = 1, 2, ... r, r represents the number of preset standard time nodes within a specified period, where 1, 2, ... r are sorted in the time sequence of the standard time nodes; SA3, set the value of f to 1, and then set all GW g，1 Import the variance calculation formula and calculate the discrete degree value of the temperature parameters of each distribution cabinet at the same standard time node; SA4. Compare the discrete degree value obtained in step SA3 with the preset discrete degree threshold: If the discrete value is greater than the discrete threshold, it means that the discrete values ​​of the temperature parameters of each distribution cabinet at the same standard time node are large, and then according to |GW g，1 -GWp1|Delete the corresponding GWs in order from largest to smallest g，1 The remaining discrete degree values ​​are calculated accordingly until the discrete degree value is less than or equal to the discrete degree threshold; Among them, GWp1 represents the average value of the temperature parameters of each distribution cabinet used at the same standard time node when participating in the calculation of the corresponding discrete degree value; SA5. When the discrete degree value is less than or equal to the discrete degree threshold, the temperature parameter corresponding to the discrete degree value is calculated at the standard time node, and the average value of the corresponding temperature parameter is obtained, and then the value is marked as the fault temperature analysis value; SA6, let the value of f be 2, 3, ..., r, and calculate the fault temperature analysis values ​​corresponding to other standard time nodes according to the subsequent steps of step SA3, and steps SA4 and SA5; SA7, select the fault temperature analysis value when f = 1, and record it as the analysis reference value FJ, and record the fault temperature analysis values ​​corresponding to all standard time nodes as FX f ; SA8, through FC f =FX f -FJ, calculate the difference FC between the fault temperature analysis value and the analysis benchmark value corresponding to each standard time node f ; SA9, according to each FC f Draw a line graph, and record the line graph as a temperature fault matching graph; The specific processing method of the normal temperature analysis value is the same as the processing method of the fault temperature analysis value in steps SA2-SA5; Then, a temperature comparison value is obtained based on the fault temperature analysis value and the normal temperature analysis value, and the temperature comparison value is transmitted to the data analysis unit; A data analysis unit is used to obtain the current temperature parameter through the data monitoring end according to a preset analysis time node, and compare it with the temperature comparison value, perform abnormal analysis according to the result that the current temperature parameter is less than and / or greater than or equal to the temperature comparison value, generate a corresponding abnormal signal according to the abnormal analysis result, and transmit the corresponding abnormal signal to the control execution end; The data analysis unit performs the following analysis: SS1. Obtain the temperature parameter of the current time node through the data monitoring terminal, and then compare it with the temperature comparison value: If the current temperature parameter is greater than or equal to the temperature comparison value, then the temperature parameters of the subsequent multiple time nodes are calculated one by one according to the time difference between the adjacent standard time nodes, and then the temperature parameter of the current time node is recorded as the comparison reference value BJ; Then through BC f1 =BX f1 -BJ, calculate the difference BC between the temperature parameter corresponding to each standard time node and the comparison benchmark value f1 , where f1=1, 2, ..., r1, r1 represents the number of the current time node and the subsequent multiple time nodes, and r1<r; Then BC f1 Draw a line graph and record it as a temperature comparison and matching graph, and enter step SS2; SS2: Perform fusion matching analysis on the temperature comparison matching graph and the temperature fault matching graph in the following manner: A broken line node is randomly selected from the temperature comparison matching graph, and then the broken line node is overlapped with each broken line node in the temperature fault matching graph one by one, and each broken line node in the temperature comparison matching graph corresponds to a broken line node in the temperature fault matching graph; Take the example where the broken line node coincides with a broken line node in the temperature fault matching graph; Then, each broken line node in the temperature comparison matching graph is subtracted from the broken line node corresponding to the temperature fault matching graph to obtain the corresponding difference, and then the number of differences whose values ​​are positive and whose differences are 0 is obtained, and the number is recorded as v1; At the same time, the difference value with negative value is extracted; Then, the absolute value of the difference that will extract the negative value is obtained, and the absolute value of the difference is compared with the preset difference threshold, and then the number of differences whose corresponding absolute value is greater than or equal to the difference threshold is obtained, and the number is recorded as v2; Where v1+v2≤r1; Then, the proportional determination coefficient β is obtained by β = (v1 + v2) / r1; Afterwards, the ratio determination coefficient β is compared with the preset ratio threshold βy: If β ≥ βy, it means that the current temperature is abnormal, and then a temperature abnormality signal is generated; If β<βy, the broken line node is overlapped with other broken line nodes in the temperature fault matching diagram one by one, and then the corresponding proportional determination coefficient is obtained according to the above method. When the broken line node is fused and matched with all the broken line nodes in the temperature fault matching diagram one by one, and there is no β≥βy, it means that the current temperature detected by the data monitoring end is wrong, and the current temperature in the distribution cabinet is normal, and no temperature abnormality signal is generated; A signal transmission unit, used for transmitting the temperature abnormality signal to the control execution end; The control execution end is used to control the start and stop of the electric push rod (5) and the air diffuser fan (6) according to the corresponding abnormal signal.

2. According to claim 1, the intelligent Internet of Things power distribution cabinet is characterized in that: The cross-sections of the fixed groove plate (2) and the movable groove plate (3) are both C-shaped structures, and the fixed groove plate (2) and the movable groove plate (3) are staggered and cross-arranged, and a water flow outlet is provided at the connection between the end of the fixed groove plate (2) and the cabinet (1); The inner sides of the fixed groove plate (2) and the movable groove plate (3) are both provided with sealing strips (4).

3. The intelligent Internet of Things power distribution cabinet according to claim 1, characterized in that: The temperature comparison value is calculated as follows: All fault temperature analysis values ​​are taken as set A; At the same time, all normal temperature analysis values ​​are taken as set B; Then calculate the intersection between set A and set B; like That is, the intersection of A and B is not empty, and then the fault temperature analysis values ​​and normal temperature analysis values ​​in the intersection are summarized into set B, and then a fault temperature analysis value and / or normal temperature analysis value with the smallest value is selected from set B and used as the temperature comparison value.

4. The intelligent Internet of Things power distribution cabinet according to claim 3 is characterized in that: like That is, the intersection of A and B is empty, and then a fault temperature analysis value with the smallest value is selected from set B and used as the temperature comparison value.

5. The intelligent Internet of Things power distribution cabinet according to claim 1, characterized in that: In step SS1, if the current temperature parameter is less than the temperature comparison value, the next temperature parameter is obtained through the data monitoring terminal according to the preset analysis time node, and is continuously compared with the temperature comparison value.

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