Temperature electric field multi-parameter explosion-proof cable joint fault early warning method and system

Abstract

The invention discloses a temperature and electric field multi-parameter explosion-proof cable joint fault early warning method, and belongs to the technical field of online monitoring and fault diagnosis of high-voltage power equipment. The method specifically comprises the following steps: acquiring temperature and electric field signals of a cable joint in the explosion-proof shell to obtain temperature signals and electric field signals; extracting temperature and electric field characteristic parameters according to the collected temperature signals and electric field signals, and constructing a monitoring matrix; according to the constructed monitoring matrix, temperature and electric field characteristic quantity correlation calculation is carried out to obtain a correlation matrix, and an early warning threshold value is calculated based on the correlation matrix; and performing fault early warning according to the obtained early warning threshold value, thereby realizing fault early warning of the explosion-proof shell cable joint. According to the method, the online monitoring efficiency of the cable joint with the explosion-proof shell is improved, and meanwhile, early warning judgment errors caused by subjective manual judgment are reduced.

Description

Technical Field

[0001] The invention belongs to the field of high voltage and insulation, online monitoring and fault diagnosis of electric power equipment, and specifically relates to a temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method. Background Art

[0002] Relevant scientific research institutions at home and abroad have conducted a lot of research on cable joint fault monitoring and early warning, and have achieved many results in cable joint fault monitoring and early warning methods based on heating, partial discharge and other technologies. The common technologies are as follows:

[0003] (1) Infrared temperature measurement method: Infrared temperature measurement technology mainly uses the ability of all objects to radiate infrared rays to perform measurements. The infrared temperature measurement system is mainly composed of an infrared emitting device, a photoelectric detector and a signal amplifier. By receiving infrared rays reflected by the object to be measured, its radiation energy is converted into an electrical signal through a photoelectric detector, and then processed by an amplifier and an integrated circuit to obtain a temperature value. This temperature measurement method is susceptible to interference from the reflectivity of the object, air humidity and the external environment during the temperature measurement process. Depending on the object to be measured, the target emissivity needs to be continuously corrected. In addition, for cable connectors with explosion-proof shells, it is impossible to monitor the heating condition of the cable connector surface through the explosion-proof shell.

[0004] (2) Distributed fiber optic temperature measurement system: The fiber optic temperature measurement system adopts the Raman reflection principle to convert the change of temperature field into a measurable optical signal. The system uses optical signals as the carrier of temperature signals and optical fibers as the medium for collecting and transmitting information. According to the time difference between the emission and reception of the optical signal and the propagation speed in the optical fiber, different humidity parameters are obtained with different emission positions, thus forming a long-distance continuous linear temperature. This method is cumbersome to install, and the optical fiber must be embedded or placed close to the surface of the cable; for embedded optical fibers, the temperature changes of the cable core can be measured. If the optical fiber is damaged, the repair is complicated and the cost is relatively high; for optical fibers that monitor the surface temperature of the cable, the measurement accuracy cannot be guaranteed because it is impossible to determine the humidity relationship between the surface and core of various cables.

[0005] (3) Partial discharge method: Monitoring partial discharge signals is one of the main ways to quantitatively analyze insulation degradation. It can determine whether there are internal defects as a warning or early warning information. The aging of the cable can also be analyzed based on the signal to estimate the remaining service life of the cable. According to relevant data, when the cable is in the early stage of dendrite formation, the partial discharge amount is 0.1PC. When the dendrite formation is severe and reaches dielectric breakdown, the partial discharge amount will reach 10,000 times the initial amount. At this stage, partial discharge signals are more suitable for offline testing. Online monitoring equipment is costly and relatively ineffective.

[0006] It can be seen from the above technologies that heat and discharge can monitor the operation of cable joints. This type of technology is also a commonly used technology at this stage. However, for cable joints with explosion-proof shells, the above monitoring technology has great limitations, and most of the existing public technologies monitor a single parameter for ordinary cable joints. There are few reliable online monitoring and early warning technologies for cable joints with explosion-proof shells. Summary of the invention

[0007] In order to solve the deficiencies in the prior art, the present invention provides a temperature and electric field multi-parameter explosion-proof shell cable joint fault warning method, which can collect the temperature and spatial electric field characteristics of the cable joint in the explosion-proof shell in real time, including the temperature T i , Temperature rise ΔT i , the maximum peak value of the space electric field E maxi , the average effective value of the space electric field E avei , the effective value increment of the spatial electric field signal ΔE avei , and can also calculate the correlation of different monitoring points through the collected temperature and spatial electric field characteristic information, so as to use the temperature and spatial electric field characteristics as the basis for judging the fault warning of the explosion-proof shell built-in cable joint. This method not only improves the efficiency of online monitoring of explosion-proof shell cable joints, but also reduces the warning judgment error caused by subjective human judgment.

[0008] The present invention adopts the following technical solution.

[0009] The first aspect of the present invention provides a temperature and electric field multi-parameter explosion-proof shell cable connector fault early warning method, comprising:

[0010] Step 1: Collect the temperature and electric field signals of the cable connector in the explosion-proof shell to obtain the temperature signal and the electric field signal;

[0011] Step 2: According to the temperature signal and electric field signal collected in step 1, the temperature and electric field characteristic parameters are extracted to construct a monitoring matrix;

[0012] Step 3: According to the monitoring matrix constructed in step 2, the correlation between the temperature and electric field characteristic quantities is calculated to obtain a correlation matrix, and then the warning threshold is calculated based on the correlation matrix;

[0013] Step 4: Perform a fault warning according to the warning threshold value obtained in step 3 to implement a fault warning for the explosion-proof housing cable connector.

[0014] Preferably, in step 1, a multi-parameter sensor is used to realize temperature and electric field signal acquisition. The multi-parameter sensor includes a miniature SHT21 temperature sensor and a space electric field probe. The multi-parameter sensor collects the surface temperature signal of the cable connector inside the explosion-proof shell through the miniature SHT21 temperature sensor, and collects the surface electric field signal of the cable connector inside the explosion-proof shell through the space electric field probe.

[0015] Preferably, in step 2, the temperature and electric field characteristic parameter extraction includes temperature value extraction, temperature rise extraction, peak value extraction within the electric field signal sampling period, average effective value extraction within the electric field signal sampling period and electric field signal effective value increment extraction.

[0016] Preferably, the temperature value is extracted to extract the temperature amplitude T of the temperature signal collected for the i-th time. i ;

[0017] Temperature rise extraction, the temperature amplitude T of the temperature signal collected for the i-th time at the same monitoring point i and the temperature amplitude T of the temperature signal collected at the i-1th time i-1 The numerical difference is taken as the temperature rise ΔT of the temperature signal collected for the i-th time i , expressed as follows:

[0018] ΔT i =T i -T i-1 (1)

[0019] In the formula,

[0020] ΔT i is the temperature rise of the temperature signal collected for the i-th time.

[0021] Preferably, the average effective value of the electric field signal sampling period is extracted, and the average effective value E of the electric field signal sampling period collected for the i-th time is extracted. avei ;

[0022] The incremental extraction of the effective value of the electric field signal is the average effective value E of the electric field signal sampling period collected for the i-th time at the same monitoring point. avei and the average effective value E of the electric field signal sampling period collected for the i-1th time avei-1 The numerical difference is taken as the effective value increment ΔE of the electric field signal collected for the i-th time. avei , expressed as follows:

[0023] ΔE ave i=E ave i E avei-1 (2)

[0024] In the formula,

[0025] ΔEavei is the effective value increment of the electric field signal collected for the i-th time.

[0026] Preferably, in step 2, the monitoring matrix X of the jth monitoring point j , expressed as follows:

[0027] X j =[Ti j ΔTi jE max i j E ave i j ΔE ave i j ]=[x1-j x2-j x3-j x4-j x5-j] (3)

[0028] In the formula,

[0029] T ij is the temperature amplitude of the temperature signal collected at the jth monitoring point at the ith time,

[0030] ΔT ij is the temperature rise of the temperature signal collected at the jth monitoring point at the ith time,

[0031] E maxij is the maximum peak value of the electric field signal collected at the jth monitoring point in the i-th sampling period,

[0032] E aveij is the average effective value of the electric field signal collected at the jth monitoring point in the i-th sampling period,

[0033] ΔE aveij is the effective value increment of the electric field signal collected at the jth monitoring point at the i-th time,

[0034] x1-j, x2-j, x3-j, x4-j, and x5-j are the characteristic quantities of the j-th monitoring point.

[0035] Preferably, in step 3, the correlation matrix K of the jth monitoring point j , expressed as follows:

[0036]

[0037] In the formula,

[0038] k 1j , k 2j , k 3j , k 4j , k 5j is the correlation matrix K of the jth monitoring point j The elements in

[0039] Y j The calculation process matrix of the correlation between temperature and electric field characteristic quantities is expressed as follows:

[0040] Y j =X j / X1=[y 1j y 2j y 3j y 4j y5j ] (5)

[0041] In the formula,

[0042] X j is the monitoring matrix of the jth monitoring point,

[0043] y1-j, y2-j, y3-j, y4-j, y5-j are the ratios of the characteristic quantity of the jth monitoring point to the corresponding characteristic quantity of the first monitoring point.

[0044] Preferably, the correlation matrix K of the jth monitoring point is j The average value of the elements in k avej As the warning threshold, it is expressed as follows:

[0045] k avej =(k 1j +k 2j +k 3j +k 4j +k 5j ) / 5 (7)

[0046] In the formula,

[0047] k avej is the correlation matrix K of the jth monitoring point j The average value of the elements in .

[0048] Preferably, in step 4, a warning threshold less than 0.2 is set as a safe value, a warning threshold between 0.2 and 0.5 is set as a warning value, a warning threshold greater than 0.5 is set as a dangerous value, and a warning is issued when the warning threshold is greater than 0.2.

[0049] The second aspect of the present invention provides a temperature and electric field multi-parameter explosion-proof shell cable joint fault warning system, which is used to run the temperature and electric field multi-parameter explosion-proof shell cable joint fault warning method, comprising:

[0050] Data acquisition module: used to collect the temperature and electric field signals of the cable connector in the explosion-proof shell to obtain temperature signals and electric field signals;

[0051] Monitoring matrix construction module: used to extract temperature and electric field characteristic parameters and construct a monitoring matrix based on the collected temperature signals and electric field signals;

[0052] Warning threshold solution module: used to calculate the correlation between temperature and electric field characteristic quantities according to the constructed monitoring matrix to obtain the correlation matrix, and then calculate the warning threshold based on the correlation matrix;

[0053] Fault warning module: used to provide fault warning according to the warning threshold and realize explosion-proof shell cable connector fault warning.

[0054] The beneficial effects of the present invention are as follows:

[0055] The present invention provides a temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method, which can collect the temperature and spatial electric field characteristics of the cable joint in the explosion-proof shell in real time, including the temperature T i , Temperature rise ΔT i , the maximum peak value of the space electric field E maxi , the average effective value of the space electric field E avei , the effective value increment of the spatial electric field signal ΔE avei , and can also calculate the correlation of different monitoring points through the collected temperature and spatial electric field characteristic information, so as to use the temperature and spatial electric field characteristics as the basis for judging the fault warning of the explosion-proof shell built-in cable joint. This method not only improves the efficiency of online monitoring of explosion-proof shell cable joints, but also reduces the warning judgment error caused by subjective human judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is the overall flow chart of the present invention;

[0057] Figure 2 It is the arrangement form of temperature electric field sensor;

[0058] Figure 3 is a single sampling period of the electric field signal. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

[0060] Embodiment 1 of the present invention proposes a temperature and electric field multi-parameter explosion-proof shell cable connector fault early warning method, such as Figure 1 As shown, including:

[0061] Step 1: Collect the temperature and electric field signals of the cable connector in the explosion-proof shell to obtain the temperature signal and the electric field signal;

[0062] The temperature and electric field signal acquisition is realized by using a multi-parameter sensor, which includes a micro SHT21 temperature sensor and a space electric field probe, such as Figure 2As shown, the multi-parameter sensor collects the surface temperature value of the cable joint in the explosion-proof shell through the micro SHT21 temperature sensor, and collects the surface electric field value of the cable joint in the explosion-proof shell through the space electric field probe. The temperature value and the electric field value can reflect the operating status of the cable joint.

[0063] Each monitoring point collects temperature and electric field signals of 5 cycles in one monitoring cycle. The temperature value is a single value, such as 40 degrees, but the electric field data is continuous. It may be necessary to collect hundreds of data points in 5 cycles at a time, such as Figure 3 shown.

[0064] The temperature collected at each monitoring point is eventually uploaded to the cloud platform for display and analysis.

[0065] Figure 2 In the figure, 1 indicates the cable connector body, 2 indicates the multi-parameter sensor composed of the miniature SHT21 temperature sensor and the space electric field probe, 3 indicates the explosion-proof housing for explosion-proofing the cable connector, and the multi-parameter sensor is placed inside the explosion-proof housing and is close to the surface of the cable connector.

[0066] Step 2: Based on the temperature signal and electric field signal collected in step 1, extract the temperature and electric field characteristic parameters and construct a monitoring matrix.

[0067] Temperature and electric field characteristic parameter extraction, including temperature value extraction, temperature rise extraction, peak value extraction within the electric field signal sampling period, average effective value extraction within the electric field signal sampling period, and electric field signal effective value increment extraction.

[0068] The temperature value extraction is to extract the temperature amplitude of the temperature signal collected for the i-th time, which is recorded as T i , i represents the signal returned in the i-th monitoring cycle;

[0069] The monitoring period can be adjusted at any time based on field operation experience. It can be 15 minutes or several hours. The shorter the monitoring period, the more frequent the monitoring data and the more information obtained, but the device also consumes more power. Considering the issue of low power consumption, the period can be appropriately lengthened. Assuming the monitoring period is 15 minutes, then the signal is actually collected once every 15 minutes.

[0070] The temperature rise extraction extracts the temperature amplitude of the temperature signal collected twice from the same monitoring point uploaded from the cloud platform, that is, the temperature amplitude T of the temperature signal collected for the i-th time. i and the temperature amplitude T of the temperature signal collected at the i-1th time i-1 The numerical difference is taken as the temperature rise of the temperature signal collected for the i-th time and recorded as ΔT i , expressed as follows:

[0071] ΔT i =Ti -T i-1 (1)

[0072] The peak value of the electric field signal sampling period is extracted. The collected electric field signal is a sine signal. The maximum peak value of the electric field signal sampling period collected for the ith time is extracted and recorded as E maxi , a single sampling period is 0.1s, and the electric field data of 5 power frequency cycles are collected, such as Figure 3 shown.

[0073] The average effective value extraction within the electric field signal sampling period is to extract the average effective value of the electric field signal sampling period collected for the i-th time and record it as E avei ;

[0074] The incremental extraction of the effective value of the electric field signal extracts the average effective value of the electric field signal sampling period collected twice from the same monitoring point uploaded from the cloud platform, that is, the average effective value E of the electric field signal sampling period collected for the i-th time avei and the average effective value E of the electric field signal sampling period collected for the i-1th time avei-1 The numerical difference is taken as the effective value increment of the electric field signal collected for the i-th time and recorded as ΔE avei , expressed as follows:

[0075] ΔE avei =E avei -E avei-1 (2)

[0076] The temperature and electric field multi-parameter feature correlation calculation calculates the latest temperature and electric field feature correlation of different monitoring points of the cable joint, and the feature quantities are respectively the temperature amplitude T of the temperature signal collected for the i-th time i , the temperature rise ΔT of the temperature signal collected for the i-th time i , the maximum peak value E of the electric field signal collected during the i-th sampling period maxi , the average effective value E of the electric field signal collected during the i-th sampling period avei , the effective value increment ΔE of the electric field signal collected for the i-th time avei , the data of j different monitoring points are formed into j matrices X j , the monitoring matrix X of the jth monitoring point j , expressed as follows:

[0077] X j =[ T ij ΔT ij E maxij E aveij ΔE aveij ]=[x1-j x2-j x3-j x4-j x5-j] (3)

[0078] In the formula,

[0079] T ij is the temperature amplitude of the temperature signal collected at the jth monitoring point at the ith time,

[0080] ΔT ij is the temperature rise of the temperature signal collected at the jth monitoring point at the ith time,

[0081] E maxij is the maximum peak value of the electric field signal collected at the jth monitoring point in the i-th sampling period,

[0082] E aveij is the average effective value of the electric field signal collected at the jth monitoring point in the i-th sampling period,

[0083] ΔE aveij is the effective value increment of the electric field signal collected at the jth monitoring point at the i-th time,

[0084] x1-j, x2-j, x3-j, x4-j, and x5-j are the characteristic quantities of the j-th monitoring point.

[0085] In the case of the present invention, the value of j is taken as 3, and the characteristic data of the three cable joint monitoring points are respectively:

[0086]

[0087] Step 3: Based on the monitoring matrix constructed in step 2, the correlation between temperature and electric field characteristic quantities is calculated to obtain a correlation matrix, and then the warning threshold is calculated based on the correlation matrix.

[0088] The calculation matrix of the correlation between temperature and electric field characteristic quantity is Y j , expressed as follows:

[0089] Y j =X j / X1=[y 1j y 2j y 3j y 4j y 5j ] (5)

[0090] In the formula,

[0091] y1-j, y2-j, y3-j, y4-j, y5-j are the ratios of the characteristic quantity of the jth monitoring point to the corresponding characteristic quantity of the first monitoring point.

[0092] The correlation matrix K of the jth monitoring point j Defined as the process matrix Y j The absolute value of the difference from a matrix whose element values ​​are all 1 is:

[0093]

[0094] k 1j , k 2j , k 3j , k 4j , k 5j is the correlation matrix K of the jth monitoring point j The elements in .

[0095] The correlation matrix K of the jth monitoring point j The average value of the elements in k avej As the warning threshold, it is expressed as follows:

[0096] k avej =(k 1j +k 2j +k 3j +k 4j +k 5j ) / 5 (7)

[0097] Step 4: Use the warning threshold obtained in step 3 to perform fault warning, so as to realize explosion-proof shell cable connector fault warning.

[0098] The explosion-proof shell cable connector fault warning is performed according to the correlation between the temperature and electric field characteristic quantities of different monitoring points and the setting of warning thresholds. The present invention sets k based on field operation experience. avej Less than 0.2 is a safe value, k avej The value between 0.2 and 0.5 is the warning value, k avej A value greater than 0.5 is considered dangerous. avej When it is greater than 0.2, an early warning is given. avej The larger the value, the higher the danger level. Different measures should be taken for different danger levels.

[0099] The beneficial effects of the present invention are:

[0100] The present invention provides a temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method, which can collect the temperature and spatial electric field characteristics of the cable joint in the explosion-proof shell in real time, including the temperature T i , temperature rise ΔTi, maximum peak value of electric field in space E maxi , the average effective value of the space electric field E avei , the effective value increment of the spatial electric field signal ΔE avei , and can also calculate the correlation of different monitoring points through the collected temperature and spatial electric field characteristic information, so as to use the temperature and spatial electric field characteristics as the basis for judging the fault warning of the explosion-proof shell built-in cable joint. This method not only improves the efficiency of online monitoring of explosion-proof shell cable joints, but also reduces the warning judgment error caused by subjective human judgment.

[0101] Embodiment 2 of the present invention proposes a temperature and electric field multi-parameter explosion-proof shell cable joint fault warning system, which is used to run a temperature and electric field multi-parameter explosion-proof shell cable joint fault warning method proposed in embodiment 1, including: a data acquisition module: used to collect the temperature and electric field signals of the cable joint in the explosion-proof shell to obtain a temperature signal and an electric field signal;

[0102] Monitoring matrix construction module: used to extract temperature and electric field characteristic parameters and construct a monitoring matrix based on the collected temperature signals and electric field signals;

[0103] Warning threshold solution module: used to calculate the correlation between temperature and electric field characteristic quantities according to the constructed monitoring matrix to obtain the correlation matrix, and then calculate the warning threshold based on the correlation matrix;

[0104] Fault warning module: used to provide fault warning according to the warning threshold and realize explosion-proof shell cable connector fault warning.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A temperature and electric field multi-parameter explosion-proof shell cable joint fault warning method, characterized in that: include: Step 1: Collect the temperature and electric field signals of the cable connector in the explosion-proof shell to obtain the temperature signal and the electric field signal; Step 2: According to the temperature signal and electric field signal collected in step 1, the temperature and electric field characteristic parameters are extracted to construct a monitoring matrix; Step 3: According to the monitoring matrix constructed in step 2, the correlation between the temperature and electric field characteristic quantities is calculated to obtain a correlation matrix, and then the warning threshold is calculated based on the correlation matrix; Step 4: Perform a fault warning according to the warning threshold value obtained in step 3 to implement a fault warning for the explosion-proof housing cable connector.

2. According to claim 1, a temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method is characterized by: In step 1, a multi-parameter sensor is used to realize temperature and electric field signal acquisition. The multi-parameter sensor includes a miniature SHT21 temperature sensor and a space electric field probe. The multi-parameter sensor collects the surface temperature signal of the cable connector in the explosion-proof shell through the miniature SHT21 temperature sensor, and collects the surface electric field signal of the cable connector in the explosion-proof shell through the space electric field probe.

3. The temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method according to claim 1 is characterized by: In step 2, temperature and electric field characteristic parameters are extracted, including temperature value extraction, temperature rise extraction, peak value extraction within the electric field signal sampling period, average effective value extraction within the electric field signal sampling period, and electric field signal effective value increment extraction.

4. The temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method according to claim 3 is characterized by: Temperature value extraction, extract the temperature amplitude T of the temperature signal collected for the i-th time i ; Temperature rise extraction, the temperature amplitude T of the temperature signal collected for the i-th time at the same monitoring point i and the temperature amplitude T of the temperature signal collected at the i-1th time i-1 The numerical difference is taken as the temperature rise ΔT of the temperature signal collected for the i-th time i , expressed as follows: ΔT i =T i -T i-1 (1) In the formula, ΔT i is the temperature rise of the temperature signal collected for the i-th time.

5. The temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method according to claim 3 is characterized by: Extract the average effective value of the electric field signal sampling period, and extract the average effective value E of the electric field signal sampling period collected for the i-th time avei ; The incremental extraction of the effective value of the electric field signal is the average effective value E of the electric field signal sampling period collected for the i-th time at the same monitoring point. avei and the average effective value E of the electric field signal sampling period collected for the i-1th time avei-1 The numerical difference is taken as the effective value increment ΔE of the electric field signal collected for the i-th time avei , expressed as follows: ΔE ave i=E ave i-E ave i -1 (2) In the formula, ΔEavei is the effective value increment of the electric field signal collected for the i-th time.

6. The temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method according to claim 1 is characterized by: In step 2, the monitoring matrix X of the jth monitoring point j , expressed as follows: X j =[ Ti j ΔTi j E max i j E ave i j ΔE ave i j ]=[ x 1 -j x 2 -j x 3 -j x 4 -j x 5 -j] (3) In the formula, T ij is the temperature amplitude of the temperature signal collected at the jth monitoring point at the ith time, ΔT ij is the temperature rise of the temperature signal collected at the jth monitoring point at the ith time, E maxij is the maximum peak value of the electric field signal collected at the jth monitoring point in the i-th sampling period, E aveij is the average effective value of the electric field signal collected at the jth monitoring point in the i-th sampling period, ΔE aveij is the effective value increment of the electric field signal collected at the jth monitoring point at the i-th time, x1-j, x2-j, x3-j, x4-j, and x5-j are the characteristic quantities of the j-th monitoring point.

7. The temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method according to claim 1 is characterized by: In step 3, the correlation matrix K of the jth monitoring point j , expressed as follows: K j =|And j -[1 1 1 1 1]| =|[and 1j -1 and 2j -1 and 3j -1 and 4j -1 and 5j -1]| (6) =[k 1j k 2j k 3j k 4j k 5j ] In the formula, k 1j , k 2j , k 3j , k 4j , k 5j is the correlation matrix K of the jth monitoring point j The elements in Y j The calculation process matrix of the correlation between temperature and electric field characteristic quantities is expressed as follows: AND j =X j / X 1 =[and 1 j and 2 j and 3 j and 4 j and 5 j ] (5) In the formula, X j is the monitoring matrix of the jth monitoring point, y1-j, y2-j, y3-j, y4-j, y5-j are the ratios of the characteristic quantity of the jth monitoring point to the corresponding characteristic quantity of the first monitoring point.

8. The temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method according to claim 7 is characterized by: The correlation matrix K of the jth monitoring point j The average value of the elements in k avej As the warning threshold, it is expressed as follows: k avej =(k 1j +k 2j +k 3j +k 4j +k 5j ) / 5 (7) In the formula, k avej is the correlation matrix K of the jth monitoring point j The average value of the elements in .

9. The temperature and electric field multi-parameter explosion-proof shell cable joint fault early warning method according to claim 1 is characterized by: In step 4, the warning threshold is set to be less than 0.2 as a safe value, the warning threshold is between 0.2 and 0.5 as a warning value, the warning threshold is greater than 0.5 as a dangerous value, and a warning is issued when the warning threshold is greater than 0.

2.

10. A temperature and electric field multi-parameter explosion-proof shell cable joint fault warning system, used to run a temperature and electric field multi-parameter explosion-proof shell cable joint fault warning method according to any one of claims 1 to 9, characterized in that: include: Data acquisition module: used to collect the temperature and electric field signals of the cable connector in the explosion-proof shell to obtain temperature signals and electric field signals; Monitoring matrix construction module: used to extract temperature and electric field characteristic parameters and construct a monitoring matrix based on the collected temperature signals and electric field signals; Warning threshold solution module: used to calculate the correlation between temperature and electric field characteristic quantities according to the constructed monitoring matrix to obtain the correlation matrix, and then calculate the warning threshold based on the correlation matrix; Fault warning module: used to provide fault warning according to the warning threshold and realize explosion-proof shell cable connector fault warning.

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