Power distribution equipment on-line detection system based on Internet of Things

Abstract

The invention discloses a power distribution equipment on-line detection system based on the Internet of Things, and relates to the technical field of power distribution equipment on-line detection, the system comprises an Internet of Things center, the Internet of Things center is in communication connection with a data acquisition module, a data processing module, a temperature anomaly primary analysis module, a temperature anomaly secondary analysis module and a fault analysis module; the data acquisition module comprises a current parameter unit and a temperature parameter unit which are respectively used for acquiring current parameters and temperature parameters of the power distribution equipment; the data processing module is used for acquiring a temperature deviation value of a monitoring point position; the temperature anomaly primary analysis module is used for performing preliminary analysis on the point position temperature deviation value to generate a secondary analysis signal; the temperature anomaly secondary analysis module is used for analyzing the internal temperature value and the external temperature value to generate fault analysis information; and the fault analysis module is used for determining a fault area range, eliminating influence factors, determining a fault area and improving maintenance efficiency and pertinence.

Description

Technical Field

[0001] The present invention relates to the technical field of online detection of power distribution equipment, and in particular to an online detection system for power distribution equipment based on the Internet of Things. Background Art

[0002] With the continuous development of power detection methods, the corresponding development of power grid needs has become more and more perfect, and power construction has made great progress. The problem that follows is that the geographical location and environmental conditions of power-related distribution equipment and distribution lines are complex and multifaceted, facing serious safety hazards. On the one hand, these safety hazards cannot be monitored and managed in a timely and effective manner. On the other hand, there are many problems with distribution lines, and distribution equipment failures are often unable to be solved in a timely, effective and targeted manner.

[0003] In the prior art, the Internet of Things technology is used to perform online detection of power distribution equipment. When a power distribution equipment fails, the fault information of the online synchronous power distribution is promptly obtained through the Internet of Things technology. However, the unclear fault location of the power distribution equipment affects the work efficiency of maintenance personnel and the timing of emergency repairs. How to obtain the fault area of ​​the power distribution equipment and analyze the causes of abnormal point temperature of the power distribution equipment are problems we need to solve. To this end, an online detection system for power distribution equipment based on the Internet of Things is now provided. Summary of the invention

[0004] In order to solve the above technical problems, the object of the present invention is to provide an online detection system for power distribution equipment based on the Internet of Things, including a management center, the management center is communicatively connected with a data acquisition module, a data processing module, a primary temperature anomaly analysis module, a secondary temperature anomaly analysis module and a fault analysis module;

[0005] The data acquisition module includes a current parameter unit and a temperature parameter unit, wherein the current parameter unit is used to obtain the current parameters of the monitoring points in the power distribution equipment, and the temperature parameter unit is used to obtain the point temperature value, the internal temperature value and the external temperature value of the monitoring points in the power distribution equipment;

[0006] The data processing module is used to process the current parameters and the point temperature values ​​to obtain the point temperature deviation value;

[0007] The temperature anomaly primary analysis module is used to perform a preliminary analysis on the point temperature deviation value, and determine whether the point temperature deviation value is abnormal based on the preliminary analysis result. If it is abnormal, a secondary analysis signal is generated;

[0008] The temperature anomaly secondary analysis module is used to analyze the internal temperature value and the external temperature value according to the generated secondary analysis signal, determine whether the analysis result is abnormal, and if abnormal, generate a fault analysis signal;

[0009] The fault analysis module is used to determine the scope of the fault area according to the fault analysis signal.

[0010] Furthermore, the process of the current parameter unit obtaining the current parameters of the power distribution equipment includes:

[0011] A number of power distribution lines are arranged in the power distribution equipment, and a number of monitoring points are arranged on each power distribution line;

[0012] The current parameter unit is installed at the corresponding monitoring point for obtaining the current parameters of the corresponding monitoring point in real time;

[0013] The current parameters include the running time and running current of the corresponding monitoring point.

[0014] Furthermore, a superior-subordinate association relationship is set between adjacent monitoring points, and the superior-subordinate association relationship includes the superior point and the subordinate point of the monitoring point.

[0015] Furthermore, the process of the temperature parameter unit obtaining the temperature parameters of the power distribution equipment includes:

[0016] The temperature parameter unit is installed at the corresponding monitoring point for obtaining the point temperature value of the corresponding monitoring point in real time;

[0017] The temperature parameter unit is also arranged inside and on the outer surface of the power distribution equipment, and is used for obtaining the internal temperature value and the external temperature value of the power distribution equipment respectively.

[0018] Furthermore, the process of the data processing module processing the current parameters and the point temperature values includes:

[0019] Construct a two-dimensional coordinate system of time versus current;

[0020] Generate a corresponding current change curve according to the running current of each obtained monitoring point, map the generated current change curve into the two-dimensional coordinate system, and set a corresponding monitoring period in the two-dimensional coordinate system;

[0021] Obtain the power consumption value used by the corresponding monitoring point within the monitoring period, and obtain the theoretical point temperature value generated by the corresponding monitoring point within the monitoring period. Obtain the point temperature deviation value of the monitoring point according to the point temperature value and the theoretical point temperature value;

[0022] Set a temperature deviation threshold range (-u, u). When the obtained point temperature deviation value belongs to the temperature deviation threshold range (-u, u), the monitoring point is marked as a normal point;

[0023] When the obtained point temperature deviation value does not belong to the temperature deviation threshold range (-u, u), a first-level analysis signal is generated.

[0024] Furthermore, the process of the primary temperature anomaly analysis module for preliminarily analyzing the point temperature deviation value includes:

[0025] Set the primary temperature fluctuation range (-β, β);

[0026] According to the primary analysis signal, when the point temperature deviation value is less than or equal to -u, obtain the theoretical internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point within the monitoring period;

[0027] Compare the point temperature value with the internal temperature value. When the point temperature value is greater than or equal to the internal temperature value, mark this monitoring point as a faulty point;

[0028] When the point temperature value is less than the internal temperature value, obtain the internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point within the monitoring period;

[0029] Obtain the temperature deviation value inside the power distribution equipment corresponding to the monitoring point according to the internal temperature difference value and the theoretical internal temperature difference value, and record it as the internal temperature deviation value;

[0030] When the point temperature deviation value is greater than u, obtain the theoretical internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point within the monitoring period;

[0031] Compare the point temperature value with the internal temperature value. When the point temperature value is greater than or equal to the internal temperature value, mark this monitoring point as a faulty point;

[0032] When the point temperature value is less than the internal temperature value, obtain the internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point within the monitoring period;

[0033] Obtain the temperature deviation value inside the power distribution equipment corresponding to the monitoring point according to the internal temperature difference value and the theoretical internal temperature difference value, and record it as the internal temperature deviation value;

[0034] Obtain the primary point temperature correction parameter according to the internal temperature deviation value;

[0035] When the primary point temperature correction parameter belongs to the primary temperature fluctuation range (-β, β), mark the monitoring point as a normal point;

[0036] When the primary point temperature correction parameter k does not belong to the primary temperature fluctuation range (-β, β), generate a secondary analysis signal.

[0037] Furthermore, the process of the secondary temperature anomaly analysis module for analyzing the internal temperature value and the external temperature value includes;

[0038] Set the secondary temperature fluctuation range (-θ, θ);

[0039] According to the secondary analysis signal, when the internal temperature deviation value is less than or equal to -β, obtain the theoretical external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point within the monitoring period;

[0040] Compare the external temperature value with the internal temperature value. When the internal temperature value is greater than or equal to the external temperature value, mark this monitoring point as a fault point;

[0041] When the internal temperature value is less than the external temperature value, obtain the external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point within the monitoring period;

[0042] Obtain the temperature deviation value of the outer surface of the power distribution equipment corresponding to the monitoring point according to the external temperature difference value and the theoretical external temperature difference value, and record it as the external temperature deviation value;

[0043] When the internal temperature deviation value is greater than β, the theoretical external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point within the monitoring period;

[0044] Compare the external temperature value with the internal temperature value. When the internal temperature value is greater than or equal to the external temperature value, mark this monitoring point as a fault point;

[0045] When the internal temperature value is less than the external temperature value, obtain the external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point within the monitoring period;

[0046] Obtain the temperature deviation value of the outer surface of the power distribution equipment corresponding to the monitoring point according to the external temperature difference value and the theoretical external temperature difference value, and record it as the external temperature deviation value;

[0047] Obtain the secondary correction parameter of the monitoring point according to the external temperature deviation value;

[0048] When the secondary correction parameter of the point belongs to the secondary temperature fluctuation range (-θ, θ), mark the monitoring point as a normal point;

[0049] When the secondary correction parameter of the point does not belong to the secondary temperature fluctuation range (-θ, θ), mark the monitoring point as a fault point and generate a fault analysis signal.

[0050] Furthermore, the process by which the fault analysis module determines the fault area range according to the fault analysis signal includes:

[0051] According to the fault analysis signal, obtain the point numbers of all fault points, and obtain the point numbers of the upper-level points and lower-level points of the fault points;

[0052] When the monitored point is a fault point, if the lower-level point of the monitored point is a fault point and the upper-level point of the monitored point is a fault point, then the lower-level point is recorded as the lower fault point, and the upper-level point is recorded as the upper fault point. Continue to detect the lower-level point of the lower fault point and the upper-level point of the upper fault point. If the lower-level point of the lower fault point is a fault point and the upper-level point of the upper fault point is a normal point, then the lower-level point is recorded as the lower fault point, and the upper-level point is recorded as the normal upper point. And so on, until both the detected upper-level point and lower-level point are normal points, then the line area from the lower-level point of the normal upper point to the upper-level point of the normal lower point is recorded as the fault area, and the fault area is sent to the maintenance personnel.

[0053] Compared with the prior art, the beneficial effects of the present invention are as follows: By setting monitored points for the power distribution lines of power distribution equipment, the present invention obtains the theoretical point temperature value according to the current parameters, compares the point temperature value with the theoretical point temperature value, analyzes the influencing factors of the abnormal point temperature value, and determines whether the abnormal point temperature value is affected by the internal temperature of the equipment or the external environment of the equipment by setting the first-level temperature fluctuation range and the second-level temperature fluctuation range. If neither is the case, it is a fault of the line itself. The monitored point is marked as a fault point, the fault area is determined according to the states of the upper-level point and lower-level point of the fault point, and the fault area is sent to the maintenance personnel for maintenance, so as to determine the fault area, improve the maintenance efficiency and accuracy. Description of the Drawings

[0054] Figure 1 It is a schematic diagram of an online detection system for power distribution equipment based on the Internet of Things according to an embodiment of the present application. Detailed Embodiments

[0055] As Figure 1 shown, an online detection system for power distribution equipment based on the Internet of Things includes an Internet of Things center, and the Internet of Things center is communicatively connected to a data acquisition module, a data processing module, a first-level temperature anomaly analysis module, a second-level temperature anomaly analysis module, and a fault analysis module;

[0056] The data acquisition module includes a current parameter unit and a temperature parameter unit. The current parameter unit is used to obtain the current parameters of the monitored points in the power distribution equipment, and the temperature parameter unit is used to obtain the point temperature value, internal temperature value, and external temperature value of the monitored points in the power distribution equipment;

[0057] The data processing module is used to process the current parameters and the point temperature value to obtain the point temperature deviation value;

[0058] The first-level temperature anomaly analysis module is used to preliminarily analyze the point temperature deviation value. According to the preliminary analysis result, it determines whether the point temperature deviation value is abnormal. If it is abnormal, it generates a second-level analysis signal;

[0059] The second-level temperature anomaly analysis module is used to analyze the internal temperature value and the external temperature value according to the generated second-level analysis signal, and determine whether the analysis result is abnormal. If it is abnormal, it generates a fault analysis signal;

[0060] The fault analysis module is used to determine the fault area range according to the fault analysis signal.

[0061] The data acquisition module includes a current parameter unit and a temperature parameter unit. The current parameter unit is used to obtain the current parameters of the monitoring points in the power distribution equipment, and the temperature parameter unit is used to obtain the point temperature value, the internal temperature value and the external temperature value of the monitoring points in the power distribution equipment. The specific process includes:

[0062] A number of power distribution lines are set in the power distribution equipment, and each power distribution line is numbered cd1, cd2,..., cd j , j>0, and the power distribution line number cd j represents the jth power distribution line in the power distribution equipment;

[0063] A number of monitoring points are set on each power distribution line, and each monitoring point is numbered pn11, pn12,..., pnj s , s>0, and the point number pnj s represents the sth monitoring point in the jth power distribution line of the power distribution equipment. There is an upper and lower level association relationship between adjacent monitoring points, and the upper and lower level association relationship includes the upper point and the lower point of the monitoring point;

[0064] It should be further noted that in the specific implementation process, there are monitoring points a, monitoring point b and monitoring point c on the power distribution line. The current on the power distribution line flows from monitoring point a to monitoring point b and from monitoring point b to monitoring point c. Then monitoring point a is the upper point of monitoring point b, monitoring point b is the lower point of monitoring point a, monitoring point b is the upper point of monitoring point c, monitoring point c is the lower point of monitoring point b, and there is no upper and lower level association relationship between monitoring point a and monitoring point c;

[0065] The current parameter unit and the temperature parameter unit are installed at the corresponding monitoring points, and are respectively used to obtain the current parameters and temperature parameters of the corresponding monitoring points in real time;

[0066] The current parameter includes the running time and running current of the corresponding monitoring point. The running time is denoted as t, and the running current is denoted as Ijs The temperature parameter is the line temperature at the location of the monitoring point, denoted as the point temperature value yj s ;

[0067] It should be further noted that in the specific implementation process, the running time of the running current of all monitoring points is the running time of the power distribution equipment;

[0068] The temperature parameter unit is also set inside and on the outer surface of the power distribution equipment, and is used to obtain the temperature value inside the power distribution equipment and the temperature value on the outer surface of the power distribution equipment respectively. Denote the temperature value inside the power distribution equipment as the internal temperature value Te, and the temperature value on the outer surface of the power distribution equipment as the external temperature value Tu.

[0069] The data processing module is used to process the current parameter and the point temperature value to obtain the point temperature deviation value. The specific process includes:

[0070] Construct a two-dimensional coordinate system of time versus current;

[0071] Generate a current change curve for the corresponding monitoring point according to the running current of each obtained monitoring point. Denote the generated current change curve as I(t), and map the generated current change curve into the two-dimensional coordinate system. Set a corresponding monitoring period in the two-dimensional coordinate system, where the duration of the monitoring period is T;

[0072] Obtain the power consumption value used by the corresponding monitoring point during the monitoring period, denoted as Q(t);

[0073] Then

[0074] According to the power consumption value used during the monitoring period, obtain the theoretical point temperature value generated by the corresponding monitoring point during the monitoring period, denoted as W(t);

[0075] Then

[0076] where is the heat conversion coefficient;

[0077] Obtain the temperature deviation value of the monitoring point according to the point temperature value and the theoretical point temperature value, denoted as the point temperature deviation value hj s , then hj s =W(t)-yj s ;

[0078] Set the temperature deviation threshold range (-u, u), where u is the temperature deviation threshold;

[0079] When the obtained point temperature deviation value hj sWhen it belongs to the temperature deviation threshold range (-u, u), the point temperature value of the monitoring point is normal, the point number of the monitoring point is obtained, and the monitoring point is marked as a normal point;

[0080] When the obtained point temperature deviation value hj s does not belong to the temperature deviation threshold range (-u, u), the point temperature value of the monitoring point is abnormal, and a first-level analysis signal is generated.

[0081] The temperature anomaly first-level analysis module is used to perform a preliminary analysis on the point temperature deviation value according to the first-level analysis signal. According to the preliminary analysis result, it is judged whether the point temperature deviation value is abnormal. If it is abnormal, a second-level analysis signal is generated. The specific process includes:

[0082] Set the first-level temperature fluctuation range (-β, β);

[0083] It should be further noted that in the specific implementation process, -β is the lower limit value of the first-level temperature fluctuation range, β is the upper limit value of the first-level temperature fluctuation range, and the lower limit value -β of the first-level temperature fluctuation range = -b1 * (Te - yj s ), the upper limit value β of the first-level temperature fluctuation range = b1 * (Te - yj s ), where b1 is a proportionality factor;

[0084] According to the first-level analysis signal, the point temperature deviation value is compared with the temperature deviation threshold. When the point temperature deviation value hj s is less than or equal to the temperature deviation threshold -u, then according to the point temperature deviation value hj s and the temperature deviation threshold u, the theoretical internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained, denoted as f;

[0085] Then f = -u - hj s ;

[0086] The point temperature value is compared with the internal temperature value. When the point temperature value is greater than or equal to the internal temperature value, it means that the internal temperature of the power distribution equipment is too low to increase the point temperature value, indicating that the line temperature of the corresponding monitoring point is abnormal due to the line itself, and the monitoring point is marked as a fault point;

[0087] When the point temperature value is less than the internal temperature value, the internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained according to the point temperature value and the internal temperature value, denoted as fn;

[0088] Then fn = Te - yj s ;

[0089] Obtain the temperature deviation value inside the power distribution equipment corresponding to the monitoring point according to the internal temperature difference value and the theoretical internal temperature difference value, and denote it as the internal temperature deviation value FN, then FN = f - fn;

[0090] When the point temperature deviation value hj s is greater than the temperature deviation threshold u, then according to the point temperature deviation value hj s and the temperature deviation threshold u, obtain the theoretical internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point during the monitoring period, and denote it as f;

[0091] Then f = hj s - u;

[0092] Compare the point temperature value with the internal temperature value. When the point temperature value is greater than the internal temperature value, it means that the internal temperature of the power distribution equipment is too low to increase the point temperature value, indicating that the line temperature of the corresponding monitoring point is abnormal due to the line itself, and mark this monitoring point as a fault point;

[0093] When the point temperature value is less than the internal temperature value, obtain the internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point during the monitoring period according to the point temperature value and the internal temperature value, and denote it as fn;

[0094] Then fn = Te - yj s ;

[0095] Obtain the temperature deviation value inside the power distribution equipment corresponding to the monitoring point according to the internal temperature difference value and the theoretical internal temperature difference value, and denote it as the internal temperature deviation value FN, then FN = f - fn;

[0096] Analyze the influencing factors of the point temperature abnormality according to the internal temperature deviation value FN, and obtain the first-level correction parameter k of the point temperature according to the internal temperature deviation value FN as

[0097]

[0098] where δ is the first-level correction factor, and the first-level correction factor is used to correct the temperature influence of the internal temperature of the power distribution equipment on the point temperature value;

[0099] It should be further noted that in the specific implementation process, there is a temperature difference between the internal temperature value and the point temperature value in actual situations. The point temperature is affected by the internal temperature. If the internal temperature value is higher than the point temperature value, the power distribution equipment will dissipate internal heat to the line at the point, and the point temperature value will increase due to the influence of the internal temperature of the power distribution equipment. If the point temperature value is higher than the internal temperature value, the line temperature at the point will dissipate heat to the inside of the power distribution equipment, and the point temperature value will decrease due to the influence of the internal temperature of the power distribution equipment;

[0100] When the point temperature first-level correction parameter k belongs to the first-level temperature fluctuation range (-β, β), the abnormal point temperature value is caused by the influence of the internal temperature of the power distribution equipment. Obtain the point number of the monitoring point, and mark the monitoring point as a normal point;

[0101] When the point temperature first-level correction parameter k does not belong to the first-level temperature fluctuation range (-β, β), a second-level analysis signal is generated.

[0102] The temperature anomaly second-level analysis module is used to analyze the internal temperature value and the external temperature value according to the second-level analysis signal, and judge whether the analysis result is abnormal. If it is abnormal, a fault analysis signal is generated. The specific process includes:

[0103] Set the second-level temperature fluctuation range (-θ, θ);

[0104] It should be further noted that in the specific implementation process, -θ is the lower limit value of the second-level temperature fluctuation range, θ is the upper limit value of the second-level temperature fluctuation range. The lower limit value -θ of the second-level temperature fluctuation range = -a1*(Tu - Te), and the upper limit value θ of the second-level temperature fluctuation range = a1*(Tu - Te), where a1 is a proportionality factor;

[0105] According to the second-level analysis signal, compare the internal temperature deviation value with the first-level temperature fluctuation value. When the internal temperature deviation value FN is less than or equal to the first-level temperature fluctuation value -β, then obtain the theoretical external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point during the monitoring period according to the internal temperature deviation value FN and the first-level temperature fluctuation value -β, denoted as s;

[0106] Then s = -β - FN;

[0107] Compare the external temperature value with the internal temperature value. When the internal temperature value is greater than or equal to the external temperature value, it means that the external environment temperature of the power distribution equipment is too low to increase the internal temperature value, indicating that the abnormal temperature of the corresponding monitoring point line is caused by the line itself. Mark the monitoring point as a fault point;

[0108] When the internal temperature value is less than the external temperature value, obtain the external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point during the monitoring period according to the internal temperature value and the external temperature value, denoted as sa;

[0109] Then sa = Tu - Te;

[0110] Obtain the temperature deviation value of the outer surface of the power distribution equipment corresponding to the monitoring point according to the external temperature difference value and the theoretical external temperature difference value, denoted as the external temperature deviation value SA. Then SA = s - sa;

[0111] When the internal temperature deviation value FN is greater than the first-level temperature fluctuation value β, the theoretical external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point within the monitoring period is obtained based on the internal temperature deviation value FN and the first-level temperature fluctuation value β, denoted as s;

[0112] Then s = FN - β;

[0113] Compare the external temperature value with the internal temperature value. When the internal temperature value is greater than or equal to the external temperature value, it means that the external environment temperature of the power distribution equipment cannot increase the internal temperature value, indicating that the line temperature anomaly at the corresponding monitoring point is caused by the line itself, and this monitoring point is denoted as a fault point;

[0114] When the internal temperature value is less than the external temperature value, the external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point within the monitoring period is obtained based on the internal temperature value and the external temperature value, denoted as sa;

[0115] Then sa = Tu - Te;

[0116] Based on the external temperature difference value and the theoretical external temperature difference value, the temperature deviation value of the outer surface of the power distribution equipment corresponding to the monitoring point is obtained, denoted as the external temperature deviation value SA, then SA = s - sa;

[0117] Then, based on the external temperature deviation value SA, analyze the influencing factors of the point temperature anomaly, and obtain the point secondary correction parameter d for the point according to the external temperature deviation value SA as

[0118]

[0119] Among them, is the secondary correction factor, and the secondary correction factor is used to correct the influence of the external temperature of the power distribution equipment on the internal temperature value;

[0120] It should be further noted that in the specific implementation process, there are temperature differences between the external temperature value, the internal temperature value and the point temperature value in actual situations. The temperature of the outer surface of the power distribution equipment affects the internal temperature of the power distribution equipment, and the change of the internal temperature of the power distribution equipment causes the change of the point temperature value;

[0121] When the point secondary correction parameter d belongs to the secondary temperature fluctuation range (-θ, θ), the point temperature value anomaly is caused by the combined influence of the external surface temperature and the internal temperature of the power distribution equipment. Obtain the point number of the point and mark the point as a normal point;

[0122] When the point secondary correction parameter d does not belong to the secondary temperature fluctuation range (-θ, θ), the abnormal point temperature value has nothing to do with the external surface temperature and internal temperature of the power distribution equipment. Then the abnormal point temperature value is related to the line fault at the monitoring point. Obtain the point number of the monitoring point, mark the monitoring point as a fault point, and generate a fault analysis signal.

[0123] The fault analysis module is used to determine the fault area range according to the fault analysis signal. The specific process includes:

[0124] According to the fault analysis signal, obtain the point numbers of all fault points, and obtain the point numbers of the upper-level points and lower-level points of the fault points.

[0125] When the monitoring point is a fault point, if the lower-level point of the monitoring point is a fault point and the upper-level point of the monitoring point is a fault point, then the lower-level point is recorded as the fault lower point, and the upper-level point is recorded as the fault upper point. Continue to detect the lower-level point of the lower-level point and the upper-level point of the upper-level point. If the lower-level point of the fault lower point is a fault point and the upper-level point of the fault upper point is a normal point, then the lower-level point is recorded as the fault lower point, and the upper-level point is recorded as the normal upper point, and so on. Until the detected upper-level point and lower-level point are both normal points, then the line area from the lower-level point of the normal upper point to the upper-level point of the normal lower point is recorded as the fault area, and the fault area is sent to the maintenance personnel.

[0126] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An online detection system for power distribution equipment based on the Internet of Things, including an Internet of Things center, characterized in that: The Internet of Things center is communicatively connected with a data acquisition module, a data processing module, a temperature anomaly primary analysis module, a temperature anomaly secondary analysis module and a fault analysis module; The data acquisition module includes a current parameter unit and a temperature parameter unit, wherein the current parameter unit is used to obtain the current parameters of the monitoring points in the power distribution equipment, and the temperature parameter unit is used to obtain the point temperature value, the internal temperature value and the external temperature value of the monitoring points in the power distribution equipment; The data processing module is used to process the current parameters and the point temperature values ​​to obtain the point temperature deviation value; The temperature anomaly primary analysis module is used to perform a preliminary analysis on the point temperature deviation value, and determine whether the point temperature deviation value is abnormal based on the preliminary analysis result. If it is abnormal, a secondary analysis signal is generated; The temperature anomaly secondary analysis module is used to analyze the internal temperature value and the external temperature value according to the generated secondary analysis signal, determine whether the analysis result is abnormal, and if abnormal, generate a fault analysis signal; The fault analysis module is used to determine the scope of the fault area according to the fault analysis signal.

2. According to the Internet of Things-based power distribution equipment online detection system of claim 1, it is characterized in that: The process of the current parameter unit acquiring the current parameter of the power distribution equipment includes: A plurality of distribution lines are arranged in the power distribution equipment, and a plurality of monitoring points are arranged on each of the distribution lines; The current parameter unit is installed at the corresponding monitoring point to obtain the current parameter of the corresponding monitoring point in real time; The current parameters include the operating time and operating current of the corresponding monitoring point.

3. According to the Internet of Things-based power distribution equipment online detection system of claim 2, it is characterized in that: A superior-subordinate relationship is set between adjacent monitoring points, and the superior-subordinate relationship includes the superior point and the subordinate point of the monitoring point.

4. According to the Internet of Things-based power distribution equipment online detection system of claim 3, it is characterized in that: The process of the temperature parameter unit acquiring the temperature parameters of the power distribution equipment includes: The temperature parameter unit is installed at the corresponding monitoring point to obtain the point temperature value of the corresponding monitoring point in real time; The temperature parameter unit is also arranged on the inside and outside of the power distribution equipment, and is used to obtain the internal temperature value and the external temperature value of the power distribution equipment respectively.

5. The online detection system for power distribution equipment based on the Internet of Things according to claim 4 is characterized in that: The process of the data processing module processing the current parameters and the point temperature values ​​includes: Construct a two-dimensional coordinate system of time with respect to current; Generate a corresponding current change curve according to the operating current of each monitoring point obtained, map the generated current change curve into a two-dimensional coordinate system, and set a corresponding monitoring period in the two-dimensional coordinate system; Obtain the power value used by the corresponding monitoring point during the monitoring period, and obtain the theoretical point temperature value generated by the corresponding monitoring point during the monitoring period, and obtain the point temperature deviation value of the monitoring point according to the point temperature value and the theoretical point temperature value; Setting a temperature deviation threshold range (-u, u), when the obtained point temperature deviation value belongs to the temperature deviation threshold range (-u, u), the monitoring point is marked as a normal point; When the obtained point temperature deviation value does not belong to the temperature deviation threshold range (-u, u), a primary analysis signal is generated.

6. The online detection system for power distribution equipment based on the Internet of Things according to claim 5 is characterized in that: The process of the temperature anomaly primary analysis module performing a preliminary analysis on the point temperature deviation value includes: Set the first-level temperature fluctuation range (-β, β); According to the primary analysis signal, when the point temperature deviation value is less than or equal to -u, the theoretical internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained; Compare the point temperature value with the internal temperature value. When the point temperature value is greater than or equal to the internal temperature value, the monitoring point is recorded as a fault point. When the point temperature value is less than the internal temperature value, the internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained; According to the internal temperature difference value and the theoretical internal temperature difference value, the temperature deviation value inside the power distribution equipment corresponding to the monitoring point is obtained, which is recorded as the internal temperature deviation value; When the point temperature deviation value is greater than u, the theoretical internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained; Compare the point temperature value with the internal temperature value. When the point temperature value is greater than or equal to the internal temperature value, the monitoring point is recorded as a fault point. When the point temperature value is less than the internal temperature value, the internal temperature difference value generated inside the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained; According to the internal temperature difference value and the theoretical internal temperature difference value, the temperature deviation value inside the power distribution equipment corresponding to the monitoring point is obtained, which is recorded as the internal temperature deviation value; Obtain the first-level correction parameter of the point temperature according to the internal temperature deviation value; When the first-level correction parameter of the point temperature belongs to the first-level temperature fluctuation range (-β, β), the monitoring point is marked as a normal point; When the first-level correction parameter k of the point temperature does not belong to the first-level temperature fluctuation range (-β, β), a second-level analysis signal is generated.

7. The online detection system for power distribution equipment based on the Internet of Things according to claim 6 is characterized in that: The process of the temperature anomaly secondary analysis module analyzing the internal temperature value and the external temperature value according to the secondary analysis signal includes: Set the secondary temperature fluctuation range (-θ, θ); According to the secondary analysis signal, when the internal temperature deviation value is less than or equal to -β, the theoretical external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained; Compare the external temperature value with the internal temperature value. When the internal temperature value is greater than or equal to the external temperature value, the monitoring point is recorded as a fault point. When the internal temperature value is lower than the external temperature value, the external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained; According to the external temperature difference value and the theoretical external temperature difference value, the temperature deviation value of the outer surface of the power distribution equipment corresponding to the monitoring point is obtained, which is recorded as the external temperature deviation value; When the internal temperature deviation value is greater than β, the theoretical external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point during the monitoring period; Compare the external temperature value with the internal temperature value. When the internal temperature value is greater than or equal to the external temperature value, the monitoring point is recorded as a fault point. When the internal temperature value is lower than the external temperature value, the external temperature difference value generated on the outer surface of the power distribution equipment corresponding to the monitoring point during the monitoring period is obtained; According to the external temperature difference value and the theoretical external temperature difference value, the temperature deviation value of the outer surface of the power distribution equipment corresponding to the monitoring point is obtained, which is recorded as the external temperature deviation value; Obtaining secondary correction parameters of the monitoring points according to the external temperature deviation value; When the secondary correction parameter of the point belongs to the secondary temperature fluctuation range (-θ, θ), the monitoring point is marked as a normal point; When the secondary correction parameter of the point does not belong to the secondary temperature fluctuation interval (-θ, θ), the monitoring point is marked as a fault point and a fault analysis signal is generated.

8. The online detection system for power distribution equipment based on the Internet of Things according to claim 7 is characterized in that: The process of the fault analysis module determining the fault area range according to the fault analysis signal includes: According to the fault analysis signal, the point numbers of all fault points are obtained, and the point numbers of the upper and lower points of the fault point are obtained; When the monitoring point is a fault point, if the subordinate point of the monitoring point is a fault point and the superior point of the monitoring point is a fault point, the subordinate point is recorded as the fault lower point, and the superior point is recorded as the fault upper point, and the subordinate point of the subordinate point and the superior point of the superior point are continued to be detected. If the subordinate point of the fault lower point is a fault point and the superior point of the fault upper point is a normal point, the subordinate point is recorded as the fault lower point, and the superior point is recorded as the normal upper point, and the same process is repeated until the superior point and the subordinate point detected are both normal points. Then the line area from the subordinate point of the normal upper point to the superior point of the normal lower point is recorded as the fault area, and the fault area is sent to the maintenance personnel.

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