A method and system for monitoring an mc4 connection

Abstract

The application provides a kind of monitoring method and system for MC4 joint, it is related to MC4 joint monitoring technical field, including the target monitoring data obtained by collecting the MC4 joint environment data;The first judgment result obtained by the target monitoring data transmission to monitoring equipment is modified and predicted, and the result is transmitted to control center;Control center responds to MC4 joint according to the received data, and the generated alarm information is stored in monitoring alarm database.Through the initial judgment of the environment data obtained by monitoring MC4 joint, the state of MC4 joint is determined, and the alarm information in abnormal state is generated;Based on the characteristic analysis of historical alarm data, the MC4 joint in normal state and possible abnormal state is modified and predicted for alarm data;Control center makes targeted response according to the received modification and prediction results and alarm information, effectively ensures the operation safety of MC4, and then improves the working efficiency of photovoltaic system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of MC4 joint monitoring, in particular to a monitoring method and system for MC4 joint. BACKGROUND

[0002] MC4 joint is a plug-in connector for connecting photovoltaic components, combiner boxes and inverters and other photovoltaic power generation system components. It is composed of two parts of metal and insulation, which can ensure the safe and efficient operation of photovoltaic system, and is one of the most common photovoltaic connectors on the market. The advantages of this joint are that it can realize fast, safe and easy operation connection, and adapt to various harsh environmental conditions, but there are often safety hazards such as fire caused by failure to discover temperature and humidity rise in time.

[0003] Therefore, the present application provides a monitoring method and system for MC4 joint, which effectively ensures the safe operation of MC4. SUMMARY

[0004] The present application provides a monitoring method and system for MC4 joint, which determines the state of MC4 joint by preliminary judgment of the environmental data obtained by monitoring MC4 joint, and generates alarm information in abnormal state; based on the characteristic analysis of historical alarm data, the MC4 joint in normal state and possible abnormal state is corrected and predicted; the control center makes targeted response according to the received correction and prediction results and alarm information, effectively ensures the safe operation of MC4, and further improves the working efficiency of photovoltaic system.

[0005] The present application provides a monitoring method for MC4 joint, comprising:

[0006] Step 1: using the preset target detection element to collect the environmental data of MC4 joint in real time to obtain target monitoring data;

[0007] Step 2: transmitting the target monitoring data to the monitoring device for initial abnormality judgment to obtain the first judgment result;

[0008] Step 3: based on the characteristic analysis of historical alarm data, the first judgment result is corrected and predicted, and the result is transmitted to the control center;

[0009] Step 4: the control center makes corresponding response to MC4 joint according to the received data, and stores the generated alarm information into the monitoring alarm database.

[0010] Preferably, the target monitoring element refers to temperature sensor and humidity sensor; the target monitoring data refers to real-time temperature value and real-time humidity value.

[0011] Preferably, the target monitoring data is transmitted to a monitoring device for initial abnormality judgment, obtaining a first judgment result, including:

[0012] The target monitoring data is transmitted to a relay gateway by using wireless communication technology, and then transmitted to the monitoring device in real time by using Ethernet;

[0013] The real-time temperature value in the target monitoring data is analyzed and processed to determine the current temperature value of the MC4 joint;

[0014] The current temperature value and the real-time humidity value are compared with the corresponding set threshold value respectively to obtain a first comparison result;

[0015] According to the first comparison result, if the current temperature value is greater than the preset temperature threshold value, and the absolute temperature difference is greater than the set temperature difference value, it is judged that the current MC4 joint state is abnormal, and temperature alarm information is generated and transmitted to the control center;

[0016] Otherwise, it is judged that the current MC4 joint state may be abnormal, and the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated;

[0017] If the current temperature value is not greater than the preset temperature threshold value, and the absolute temperature difference is greater than the set temperature difference value, it is judged that the current MC4 joint state is normal, and the current MC4 joint is marked as normal, and normal state data is generated;

[0018] Otherwise, it is judged that the current MC4 joint state may be abnormal, and the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated;

[0019] If the real-time humidity value is greater than the preset humidity threshold value, and the absolute humidity difference is greater than the set humidity difference value, it is judged that the current MC4 joint state is abnormal, and humidity alarm information is generated and transmitted to the control center;

[0020] Otherwise, it is judged that the current MC4 joint state may be abnormal, and the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated;

[0021] If the real-time humidity value is not greater than the preset humidity threshold value, and the absolute humidity difference is greater than the set humidity difference value, it is judged that the current MC4 joint state is normal, and the current MC4 joint is marked as normal, and normal state data is generated;

[0022] Otherwise, it is judged that the current MC4 joint state may be abnormal, and the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated;

[0023] The pre-alarm data and the normal state data are output as the first judgment result.

[0024] Preferably, the real-time temperature value in the target monitoring data is analyzed and processed to determine the current temperature value of the MC4 joint, including:

[0025] The real-time temperature value in the target monitoring data is decomposed by using an integrated empirical mode decomposition method to obtain a plurality of sub-sequences;

[0026] A long short-term memory model is introduced to predict the sub-sequences obtained by decomposition to obtain a first result;

[0027] The first result is integrated, and the analysis of the external environment temperature is combined to calculate the current temperature value of the MC4 joint, wherein the calculation formula of the current temperature value is as follows:

[0028]

[0029] T d represents the current temperature value of the MC4 joint; T i represents the first result predicted by the long short-term memory model for the i-th sub-sequence, wherein i∈1, 2, 3, …, n; I represents the current; R represents the resistance; t represents the current use time of the MC4 joint; represents the temperature difference between the current external environment temperature and the real-time temperature value; T w represents the external environment temperature; α1 represents the influence weight of the external environment temperature on the temperature of the MC4 joint; α2 represents the influence weight of the energy generated by the current flowing through the joint on the temperature of the MC4 joint; ε represents the loss factor for calculating the current temperature value of the MC4 joint; W w represents the standard power.

[0030] Preferably, based on the characteristic analysis of the historical alarm data, the first judgment result is corrected and predicted, and the result is transmitted to the control center, including:

[0031] All parameters of the MC4 joint are screened based on principal component analysis to obtain key parameters;

[0032] A preset amount of historical alarm data is extracted from the monitoring alarm database as a training sample, and the key parameters are input into the training model as input to obtain an abnormal prediction model;

[0033] According to the first judgment result, the current key parameters of the MC4 joint marked as normal are combined with the normal state data and input into the abnormal prediction model for abnormal prediction to obtain an abnormal prediction time, and then transmitted to the control center;

[0034] The target monitoring element matched with the MC4 joint marked as possibly abnormal is analyzed to determine a correction coefficient;

[0035] The pre-warning data is modified by using the correction coefficient to obtain modified warning data, and then the modified warning data is transmitted to the control center.

[0036] Preferably, the target monitoring element matched with the MC4 joint marked as possible abnormality is subjected to influence degree analysis to determine the data correction coefficient, including:

[0037] A plurality of reference monitoring elements with the same service life as the MC4 joint marked as abnormality and normal state of the currently matched MC4 joint are selected from the element monitoring database;

[0038] The monitoring data and signal value of the reference monitoring element at the current time are obtained and output as reference data and reference signal value, respectively;

[0039] The observation data is obtained by screening the monitoring data of the reference monitoring element by using the set data change amplitude;

[0040] The observation data is subjected to data fitting to obtain a first correlation coefficient;

[0041] The pre-warning data is modified based on the first correlation coefficient, in combination with the reference data and reference signal to construct a data correction coefficient;

[0042] The calculation formula of the data correction coefficient is as follows:

[0043] In the formula, F represents the data correction coefficient; g represents the first correlation coefficient; x d represents the signal value of the target monitoring element matched with the MC4 joint marked as abnormality at the current time; Δx represents the average value of the reference signal values of all reference monitoring elements; s d represents the pre-warning data; Δs represents the average value of the reference monitoring data of all reference monitoring elements; f c represents the slope of data fitting; σ represents the monitoring element detection error estimation factor; and δ represents the loss factor for calculating the data correction coefficient.

[0044] Preferably, the control center makes a corresponding response according to the received modified warning data, and stores the warning information into the monitoring warning database, including:

[0045] The control center makes a response to the corresponding MC4 joint according to the received temperature warning information and humidity warning information, and stores the information into the monitoring warning database;

[0046] The received modified warning data is analyzed, the MC4 joint marked as possible abnormality with the modified warning data greater than the preset warning threshold is determined as abnormal, corresponding warning information is generated and stored into the monitoring warning database, and a corresponding response is made;

[0047] The MC4 joint with the modified alarm data not greater than the preset alarm threshold is marked as a possible abnormal MC4 joint, and the early warning level is marked as a priority level;

[0048] The risk MC4 joint is sequentially filled into the early warning table of the priority level according to the modified alarm data from large to small;

[0049] Then, the time difference between the received abnormal prediction time and the current prediction time is determined, and the early warning level of the MC4 joint is marked as a first level, a second level or a third level based on the set time difference;

[0050] The MC4 joint with the marked early warning level is sequentially filled into the early warning table of the corresponding level from small to large based on the time difference;

[0051] The staff sequentially maintains and repairs the MC4 joints in the priority, first level, second level and third level early warning tables.

[0052] The application provides a monitoring system for an MC4 joint, comprising:

[0053] A data acquisition module is configured to acquire environmental data of the MC4 joint in real time by using a preset target detection element to obtain target monitoring data;

[0054] A data preliminary judgment module is configured to transmit the target monitoring data to a monitoring device for initial abnormality judgment to obtain a first judgment result;

[0055] A prediction and correction module is configured to correct and predict the first judgment result based on characteristic analysis of historical alarm data, and transmit the result to a control center;

[0056] A response module is configured to enable the control center to make a corresponding response to the MC4 joint according to the received data, and store generated alarm information in a monitoring alarm database.

[0057] Compared with the prior art, the application has the following beneficial effects:

[0058] The environmental data of the monitored MC4 joint is preliminarily judged to determine the state of the MC4 joint and generate alarm information in an abnormal state; based on characteristic analysis of historical alarm data, the MC4 joint in a normal state and a possible abnormal state is corrected and predicted; the control center makes a targeted response according to the received correction and prediction results and alarm information, effectively ensures the operation safety of the MC4, and further improves the working efficiency of the photovoltaic system.

[0059] Additional features and advantages of the present application will be set forth in the description that follows, and in part will be apparent from the description, or can be learned by practice of the application. The objectives and other advantages of the present application will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0060] The technical solutions of the present application are described in further detail below with the aid of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0061] The accompanying drawings are included to provide a further understanding of the present application and are incorporated in and constitute a part of the specification, illustrate embodiments of the present application and are used to explain the present application, but are not intended to limit the present application. In the drawings:

[0062] Figure 1 A flow chart of a monitoring method for an MC4 connector according to an embodiment of the present application;

[0063] Figure 2 A structural diagram of a monitoring system for an MC4 connector according to an embodiment of the present application. DETAILED DESCRIPTION

[0064] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, and it should be understood that the preferred embodiments described herein are merely intended to illustrate and explain the present application, and are not intended to limit the present application.

[0065] An embodiment of the present application provides a monitoring method for an MC4 connector, as shown in Figure 1 The monitoring method comprises the following steps:

[0066] Step 1: Real-time collection of environmental data of the MC4 connector by using a preset target detection element to obtain target monitoring data;

[0067] Step 2: Transmission of the target monitoring data to a monitoring device for initial abnormality judgment to obtain a first judgment result;

[0068] Step 3: Correction and prediction of the first judgment result based on characteristic analysis of historical alarm data, and transmission of the result to a control center;

[0069] Step 4: Response of the control center to the MC4 connector according to the received data, and storage of generated alarm information in a monitoring alarm database.

[0070] In this embodiment, the target detection element refers to a temperature sensor and a humidity sensor, which are arranged at the cavity wall of the MC4 connector protective shell; the target monitoring data refers to real-time temperature values and real-time humidity values; the environmental data refers to temperature and humidity data; and the MC4 connector is a special connector for photovoltaic power stations, mainly used for circuit connection of outdoor cell panels to inverters / converging boxes.

[0071] In the embodiment, the monitoring device is used for making abnormality judgment and abnormality prediction on the received data, and sending the abnormality judgment result or the prediction result to the control center; the first judgment result refers to an abnormality initial judgment result of the target monitoring data, including pre-warning data and normal state data, wherein the pre-warning data refers to real-time temperature data and humidity data of the MC4 joint judged as possibly abnormal, and the normal state data refers to real-time temperature data and humidity data of the MC4 joint in a normal state.

[0072] In the embodiment, the historical warning data is extracted from the monitoring warning database, and is used for correction and prediction analysis of the first judgment result; the control center is used for receiving and responding to the warning information effectively, so as to discover and handle the MC4 joint fault in time.

[0073] In the embodiment, the warning information includes warning time, warning reason, and warning MC4 joint, etc.; the monitoring warning database is mainly composed of warning information and warning data.

[0074] The above technical scheme has the beneficial effects that: the state of the MC4 joint is determined by making an initial judgment on the environment data of the monitored MC4 joint, and the warning information in an abnormal state is generated; the MC4 joint in a normal state and a possibly abnormal state is corrected and predicted based on the characteristic analysis of the historical warning data; the control center responds to the received correction and prediction results and the warning information, effectively ensuring the operation safety of the MC4, and further improving the working efficiency of the photovoltaic system.

[0075] The embodiment of the application provides a monitoring method for an MC4 joint, which comprises the following steps:

[0076] The target monitoring data is transmitted to a relay gateway by using wireless communication technology, and then the data is transmitted to a monitoring device in real time by using Ethernet;

[0077] The real-time temperature value in the target monitoring data is analyzed and processed to determine the current temperature value of the MC4 joint.

[0078] The current temperature value and the real-time humidity value are compared with corresponding set threshold values respectively to obtain a first comparison result.

[0079] According to the first comparison result, if the current temperature value is greater than a preset temperature threshold value, and an absolute temperature difference is greater than a set temperature difference value, it is judged that the current MC4 joint is abnormal, and temperature warning information is generated and transmitted to the control center.

[0080] Otherwise, it is judged that the current MC4 joint state is possibly abnormal, the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated again;

[0081] If the current temperature value is not greater than the preset temperature threshold value, and the absolute temperature difference is greater than the set temperature difference value, it is judged that the current MC4 joint state is normal, the current MC4 joint is marked as normal, and normal state data is generated again;

[0082] Otherwise, it is judged that the current MC4 joint state is possibly abnormal, the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated again;

[0083] If the real-time humidity value is greater than the preset humidity threshold value, and the absolute humidity difference is greater than the set humidity difference value, it is judged that the current MC4 joint state is abnormal, and humidity alarm information is generated and transmitted to the control center;

[0084] Otherwise, it is judged that the current MC4 joint state is possibly abnormal, the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated again;

[0085] If the real-time humidity value is not greater than the preset humidity threshold value, and the absolute humidity difference is greater than the set humidity difference value, it is judged that the current MC4 joint state is normal, the current MC4 joint is marked as normal, and normal state data is generated again;

[0086] Otherwise, it is judged that the current MC4 joint state is possibly abnormal, the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated again;

[0087] The pre-alarm data and the normal state data are output as the first judgment result.

[0088] In this embodiment, the wireless communication technology refers to a communication technology that utilizes the characteristics of electromagnetic wave signals that can propagate in free space and inverse information exchange; the target monitoring data includes real-time temperature values and real-time humidity values; the relay gateway provides an Ethernet port to realize network interconnection through a preset protocol; the Ethernet is a computer local area network technology that can realize data transmission.

[0089] In this embodiment, the monitoring device is used for abnormality judgment and abnormality prediction of the received data, and sends the abnormality judgment result or the prediction result to the control center; the real-time temperature value refers to the real-time detection obtained by using a temperature sensor; the current temperature value refers to the temperature of the MC4 joint based on the analysis of the real-time temperature value.

[0090] In this embodiment, the set threshold value includes a preset temperature threshold value and a preset humidity threshold value; the first comparison result refers to the comparison result of the current temperature value and the real-time humidity value with the corresponding preset temperature threshold value and preset humidity threshold value; the preset temperature threshold value is set in advance.

[0091] In this embodiment, the absolute temperature difference refers to the absolute value of the temperature difference between the current temperature value of the MC4 joint and the preset temperature threshold; the set temperature difference value is set in advance; the pre-warning data refers to the real-time temperature data and humidity data of the MC4 joint judged as possibly abnormal; and the temperature warning information includes the current temperature value, the warning time, and the temperature warning joint, etc.

[0092] In this embodiment, the real-time humidity value refers to the real-time detection by the humidity sensor; the preset humidity threshold is set in advance; the absolute humidity difference refers to the absolute value of the humidity difference between the real-time humidity value of the MC4 joint and the preset humidity threshold; the set humidity difference value is set in advance; and the humidity warning information includes the real-time humidity value, the warning time, and the humidity warning joint, etc.

[0093] In this embodiment, the first judgment result refers to the initial abnormality judgment result of the target monitoring data, including the pre-warning data and the normal state data, wherein the pre-warning data refers to the real-time temperature data and humidity data of the MC4 joint judged as possibly abnormal, and the normal state data refers to the real-time temperature data and humidity data of the MC4 joint in normal state.

[0094] The above technical solution has the beneficial effects that the target monitoring data is transmitted to the monitoring device, the real-time temperature value is analyzed to obtain the current temperature of the MC4 joint, and the state of the MC4 joint is initially judged based on the set threshold to ensure the accuracy of the monitoring system and provide data support for state prediction.

[0095] The embodiment of the application provides a monitoring method for an MC4 joint, which analyzes and processes the real-time temperature value in the target monitoring data to determine the current temperature value of the MC4 joint, including:

[0096] The real-time temperature value in the target monitoring data is processed by using an integrated empirical mode decomposition method to obtain a plurality of sub-sequences;

[0097] A long short-term memory model is introduced to predict the sub-sequences obtained by decomposition to obtain a first result;

[0098] The first result is integrated, and the current temperature value of the MC4 joint is calculated by combining the analysis of the external environment temperature, wherein the calculation formula of the current temperature value is as follows:

[0099] In the formula, T d represents the current temperature value of the MC4 joint; T iThe first result predicted by the long short-term memory model for the i-th subsequence, wherein i is an integer in 1, 2, 3,..., n; I represents current; R represents resistance; and t represents the current use time of the MC4 joint. The temperature difference between the current external environment temperature and the real-time temperature value; T w The external environment temperature; alpha1 represents the influence weight of the external environment temperature on the temperature of the MC4 joint; alpha2 represents the influence weight of the energy generated by the current flowing through the joint on the temperature of the MC4 joint; epsilon represents a loss factor for calculating the current temperature value of the MC4 joint; and W w The standard power.

[0100] In this embodiment, the integrated empirical mode decomposition method is a typical noise auxiliary signal decomposition method, and the purpose is to solve the problems of mode aliasing and the like; the subsequence is a sequence obtained by decomposing the real-time temperature value; the long short-term memory model is a time recurrent neural network, which is used for temperature prediction of the decomposed subsequence to obtain the first result; and the external environment temperature refers to the temperature value outside the protective shell of the MC4 joint.

[0101] The above technical scheme has the beneficial effects that: by combining the integrated empirical mode decomposition and the long short-term memory model to analyze and calculate the real-time temperature value, the temperature value of the MC4 joint is obtained, and the effective prediction of the surface temperature of the MC4 joint is realized.

[0102] The embodiment of the present application provides a monitoring method for an MC4 joint, based on the characteristic analysis of historical alarm data, the first judgment result is modified and predicted, and the result is transmitted to a control center, comprising:

[0103] Based on principal component analysis, all parameters of the MC4 joint are screened to obtain key parameters;

[0104] A preset amount of historical alarm data is extracted from a monitoring alarm database as a training sample, and then the key parameters are used as input training models to obtain an abnormal prediction model;

[0105] According to the first judgment result, the current key parameters of the MC4 joint marked as normal are combined with normal state data and input into the abnormal prediction model for abnormal prediction to obtain an abnormal prediction time, and then transmitted to the control center;

[0106] The target monitoring element matched with the MC4 joint marked as possibly abnormal is analyzed to determine a correction coefficient;

[0107] After the pre-alarm data is corrected by using the correction coefficient to obtain corrected alarm data, the corrected alarm data is transmitted to the control center.

[0108] In the embodiment, principal component analysis is used for data mining, and key parameters can be screened; the MC4 connector is a special connector for a photovoltaic power station, and is mainly used for circuit connection of an outdoor cell panel to an inverter / converging box; the key parameters refer to connector output current, output power, temperature and humidity.

[0109] In the embodiment, the monitoring alarm database is used for storing alarm information and alarm data; the preset amount is set in advance; the historical alarm data refer to historical temperature data and historical humidity data of the MC4 connector; the abnormality prediction model is used for real-time prediction of the time when the MC4 connector in a normal state becomes abnormal; the first judgment result refers to an initial abnormality judgment result of target monitoring data, including pre-alarm data and normal state data; the abnormality prediction time refers to the time when the MC4 connector in a normal state becomes abnormal, which is obtained by using the abnormality prediction model for real-time prediction.

[0110] In the embodiment, the target monitoring element refers to a temperature sensor and a humidity sensor arranged on the cavity wall of the MC4 connector protection shell; the data correction coefficient is a correction coefficient obtained based on performance loss analysis of the target detection element, and is used for adjusting the pre-alarm data, wherein the pre-alarm data refer to real-time temperature data and humidity data of the MC4 connector that is judged to be possibly abnormal; the corrected alarm data is data obtained by correcting the pre-alarm data by using the data correction coefficient.

[0111] The above technical scheme has the beneficial effects that: by combining the normal state data with the historical alarm data to construct the abnormality prediction model to predict the abnormal time of the MC4 connector in a normal state, the effective prediction of the remaining life of the MC4 connector can be realized, so as to prompt the staff to carry out targeted maintenance; the pre-alarm data is corrected according to the monitoring data and the running signal of the monitoring element, the real monitoring data of the MC4 connector that is possibly abnormal is obtained, and the accuracy of the monitoring system is ensured.

[0112] The embodiment of the present application provides a monitoring method for an MC4 connector, which performs influence degree analysis on a target monitoring element matched with an MC4 connector marked as possibly abnormal, and determines a data correction coefficient, including:

[0113] Selecting, from an element monitoring database, a reference monitoring element having the same service life as the MC4 connector marked as abnormal and being currently in a normal state;

[0114] Obtaining monitoring data and a signal value of the reference monitoring element at the current time, and outputting the monitoring data and the signal value as reference data and a reference signal value, respectively;

[0115] Filtering, from the monitoring data of the reference monitoring element, observation data by using a set data change amplitude;

[0116] data fitting is performed on the observation data to obtain a first correlation coefficient;

[0117] Based on the first correlation coefficient, the reference data and the reference signal are combined to construct a data correction coefficient to correct the pre-warning data;

[0118] The calculation formula of the data correction coefficient is as follows:

[0119] In the formula, F represents the data correction coefficient; g represents the first correlation coefficient; x d represents the signal value of the target monitoring element matched with the MC4 joint marked as abnormal at the current time; Δx represents the average value of the reference signal values of all reference monitoring elements; s d represents the pre-warning data; Δs represents the average value of the reference monitoring data of all reference monitoring elements; f c represents the slope of the data fitting; σ represents the monitoring element detection error estimation factor; δ represents the loss factor for calculating the data correction coefficient.

[0120] In this embodiment, the element monitoring database is mainly composed of monitoring MC4 joint environmental data of the monitoring element; the reference monitoring element refers to a monitoring element whose current monitored MC4 joint state is normal and whose service life is the same as that of the target monitoring element matched with the MC4 joint marked as abnormal.

[0121] In this embodiment, the monitoring data refers to the temperature value and the real-time humidity value of the MC4 joint monitored by the reference monitoring element, and is output as the reference data; the reference signal value refers to the current signal value of the reference monitoring element, including the voltage value and the resistance value; the set data variation range is set in advance, including the preset temperature variation range and the preset humidity variation range; the observation data is obtained by screening the set data variation range from the monitoring data; and the first correlation coefficient is obtained after data fitting analysis on the observation data.

[0122] The above technical solution has the beneficial effects that: the pre-warning data is corrected by establishing the data correction coefficient through analysis on the monitoring data and the operating signal of the monitoring element, the real monitoring data of the possible abnormal MC4 joint is obtained, and the accuracy of the monitoring system can be effectively ensured.

[0123] The embodiment of the application provides a monitoring method for an MC4 joint, a control center makes a corresponding response according to received corrected warning data, and stores the warning information into a monitoring warning database, which comprises the following steps:

[0124] The control center makes a response to the corresponding MC4 joint according to the received temperature warning information and humidity warning information, and stores the information into the monitoring warning database;

[0125] analyzing the received modified alarm data, marking the modified alarm data greater than the preset alarm threshold as a possible abnormal MC4 joint, determining that there is an abnormality, generating corresponding alarm information, storing the corresponding alarm information into the monitoring alarm database, and making a corresponding response;

[0126] marking the modified alarm data not greater than the preset alarm threshold as a possible abnormal MC4 joint as a risk MC4 joint, and marking the early warning level as a priority level;

[0127] filling the risk MC4 joint into the early warning table of the priority level in order according to the modified alarm data from large to small;

[0128] determining a time difference from the received abnormal prediction time and the current prediction time, and marking the early warning level of the MC4 joint as a first level, a second level or a third level based on the set time difference;

[0129] filling the MC4 joint with the marked early warning level into the early warning table of the corresponding level in order from small to large based on the time difference;

[0130] The staff sequentially maintains and repairs the MC4 joints in the priority, first level, second level and third level early warning tables.

[0131] In this embodiment, the temperature alarm information includes a current temperature value, an alarm time and a temperature alarm joint; the humidity alarm information includes a real-time humidity value, an alarm time and a humidity alarm joint; and the monitoring alarm database is used to store the alarm information and the alarm data.

[0132] In this embodiment, the modified alarm data is obtained by modifying the pre-alarm data using a data correction coefficient, wherein the pre-alarm data refers to real-time temperature data and humidity data of the MC4 joint determined as a possible abnormal joint; and the preset alarm threshold is set in advance.

[0133] In this embodiment, the risk MC4 joint refers to the MC4 joint marked as possible abnormal with the modified alarm data not greater than the preset alarm threshold; the early warning level is used to indicate the emergency degree of future abnormality of the MC4 joint; the set time difference is set in advance; and the early warning table is used to store the MC4 joints in order.

[0134] The beneficial effects of the above technical solution are: the control center responds to the corresponding MC4 joint according to the received alarm information; the early warning level of the corresponding matched MC4 joint is marked based on the received modified data and prediction data, and the MC4 joint is processed in order, thereby improving the early warning work efficiency.

[0135] The embodiment of the application provides a monitoring system for an MC4 joint, as shown in Figure 2 , comprising:

[0136] Data acquisition module: for real-time acquisition of environmental data of MC4 joint by using preset target detection element, to obtain target monitoring data;

[0137] Data preliminary judgment module: for transmitting the target monitoring data to the monitoring device for initial abnormality judgment, to obtain the first judgment result;

[0138] Prediction and correction module: for modifying and predicting the first judgment result based on the characteristic analysis of historical alarm data, and transmitting the result to the control center;

[0139] Response module: for the control center to make corresponding response to the MC4 joint according to the received data, and to store the generated alarm information into the monitoring alarm database.

[0140] The beneficial effects of the above technical solution are: through the preliminary judgment of the environmental data obtained by monitoring the MC4 joint, the state of the MC4 joint is determined, and the alarm information in the abnormal state is generated; based on the characteristic analysis of the historical alarm data, the MC4 joint in the normal state and the possible abnormal state is modified and predicted; the control center makes targeted response according to the received correction and prediction results and alarm information, effectively ensures the safe operation of the MC4, and further improves the working efficiency of the photovoltaic system.

[0141] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A method for monitoring an MC4 connection, characterized by, The application relates to a method for monitoring an MC4 joint, and belongs to the field of monitoring and control of the MC4 joint. Step 1: collecting environment data of the MC4 joint in real time by using preset target monitoring elements to obtain target monitoring data; Step 2: transmitting the target monitoring data to a monitoring device to perform initial abnormality judgment and obtaining a first judgment result; Step 3: based on characteristic analysis of historical alarm data, the first judgment result is modified and predicted, and the result is transmitted to a control center, including: based on principal component analysis, all parameters of the MC4 joint are screened to obtain key parameters; a preset amount of historical alarm data is extracted from a monitoring alarm database as a training sample, and the key parameters are used as input to train a model to obtain an abnormality prediction model; according to the first judgment result, the current key parameters of the MC4 joint marked as normal are combined with normal state data to input into the abnormality prediction model for abnormality prediction to obtain an abnormality prediction time, and then the abnormality prediction time is transmitted to the control center; the target monitoring element matched with the MC4 joint marked as possibly abnormal is analyzed to determine a correction coefficient; the pre-alarm data is corrected by using the correction coefficient to obtain corrected alarm data, and then the corrected alarm data is transmitted to the control center; Step 4: the control center responds to the MC4 joint according to the received data, and stores generated alarm information into the monitoring alarm database.

2. A monitoring method for an MC4 connection according to claim 1, characterized in that, The target monitoring elements refer to temperature sensors and humidity sensors; the target monitoring data refer to real-time temperature values and real-time humidity values.

3. A method of monitoring an MC4 connection according to claim 1, characterized in that, The target monitoring data are transmitted to the monitoring device by using wireless communication technology to perform initial abnormality judgment and obtain a first judgment result, including: the target monitoring data are transmitted to a relay gateway by using wireless communication technology, and then the data are transmitted to the monitoring device in real time by using Ethernet; the real-time temperature values in the target monitoring data are analyzed and processed to determine the current temperature value of the MC4 joint; the current temperature value and the real-time humidity value are compared with corresponding set threshold values respectively to obtain a first comparison result; according to the first comparison result, if the current temperature value is greater than a preset temperature threshold value and an absolute temperature difference is greater than a set temperature difference value, it is judged that the current MC4 joint state is abnormal, temperature alarm information is generated and then transmitted to the control center; otherwise, it is judged that the current MC4 joint state is possibly abnormal, the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated; if the current temperature value is not greater than the preset temperature threshold value and the absolute temperature difference is greater than the set temperature difference value, it is judged that the current MC4 joint state is normal, the current MC4 joint is marked as normal, and normal state data is generated; otherwise, it is judged that the current MC4 joint state is possibly abnormal, the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated; if the real-time humidity value is greater than a preset humidity threshold value and an absolute humidity difference is greater than a set humidity difference value, it is judged that the current MC4 joint state is abnormal, humidity alarm information is generated and then transmitted to the control center; otherwise, it is judged that the current MC4 joint state is possibly abnormal, the current MC4 joint is marked as possibly abnormal, and pre-alarm data is generated; If the real-time humidity value is not greater than the preset humidity threshold value, and the absolute humidity difference is greater than the set humidity difference value, it is judged that the current MC4 joint state is normal, the current MC4 joint is marked as normal, and normal state data is generated again; Otherwise, it is judged that the current MC4 joint state may be abnormal, and the current MC4 joint is marked as possibly abnormal, and pre-warning data is generated again; The pre-warning data and normal state data are output as the first judgment result.

4. A monitoring method for an MC4 connection according to claim 3, characterized in that, The real-time temperature value in the target monitoring data is analyzed and processed to determine the current temperature value of the MC4 joint, including: The real-time temperature value in the target monitoring data is decomposed by using an integrated empirical mode decomposition method to obtain a plurality of sub-sequences; A long short-term memory model is introduced to predict the sub-sequences obtained by decomposition to obtain a first result; The first result is integrated, and the current temperature value of the MC4 joint is calculated by combining the analysis of the external environment temperature, wherein the calculation formula of the current temperature value is as follows: ; wherein, represents the current temperature value of the MC4 joint; represents the first result predicted by the long short-term memory model for the i-th sub-sequence, wherein ; represents the current; represents the resistance; t represents the current usage time of the MC4 joint; represents the temperature difference between the current external environment temperature and the real-time temperature value; represents the external environment temperature; represents the influence weight of the external environment temperature on the temperature of the MC4 joint; represents the influence weight of the energy generated by the current flowing through the joint on the temperature of the MC4 joint; represents the loss factor for calculating the current temperature value of the MC4 joint; represents the standard power.

5. The method of claim 1, wherein, The target monitoring elements matched with the MC4 joint marked as possibly abnormal are analyzed for influence degree to determine a data correction coefficient, including: Selecting a plurality of reference monitoring elements with the same service life as the MC4 joint marked as abnormal and with a normal state of the current matched MC4 joint from the element monitoring database; Obtaining the monitoring data and signal value of the reference monitoring element at the current time, and outputting them as reference data and reference signal value respectively; Obtaining observation data from the monitoring data of the reference monitoring element by using a set data change amplitude; Data fitting is performed on the observation data to obtain a first correlation coefficient; Based on the first correlation coefficient, the reference data and the reference signal are combined to construct a data correction coefficient to correct the pre-warning data; Wherein, the calculation formula of the data correction coefficient is as follows: ; wherein F represents a data correction coefficient; g represents a first correlation coefficient; represents a signal value of a target monitoring element matched to the MC4 joint marked as abnormal at the current time point; represents an average value of reference signal values of all reference monitoring elements; represents pre-alarm data; represents an average value of reference monitoring data of all reference monitoring elements; represents a slope of data fitting; represents a monitoring element detection error estimation factor; represents a loss factor for calculating a data correction coefficient.

6. The method of claim 1, wherein, The control center makes corresponding response according to the received correction warning data, and stores the warning information into the monitoring warning database, including: The control center responds to the corresponding MC4 joint according to the received temperature warning information and humidity warning information, and stores it into the monitoring warning database; The MC4 joint marked as possibly abnormal with the correction warning data greater than the preset warning threshold value is determined to exist abnormal, and the corresponding warning information is generated and stored into the monitoring warning database and the corresponding response is made; The MC4 joint marked as possibly abnormal with the correction warning data not greater than the preset warning threshold value is regarded as a risk MC4 joint, and the warning level is marked as a priority level; The risk MC4 joint is filled into the priority level warning table in order from large to small according to the correction warning data; Then, the time difference between the received abnormal prediction time and the current prediction time is determined, and the warning level of the MC4 joint is marked as level one, level two or level three based on the set time difference; The MC4 joint with the marked warning level is filled into the corresponding level warning table in order from small to large based on the time difference; The workers maintain and repair the MC4 joints in the priority, level one, level two and level three warning tables in order.

7. A monitoring system for an MC4 connection, characterized by Including: The data acquisition module is configured to acquire environmental data of the MC4 joint in real time by using preset target monitoring elements, and obtain target monitoring data. The data preliminary judgment module is configured to transmit the target monitoring data to a monitoring device to perform initial abnormality judgment, and obtain a first judgment result. The prediction and correction module is configured to correct and predict the first judgment result based on characteristic analysis of historical alarm data, and transmit the result to a control center. The prediction and correction module includes: screening all parameters of the MC4 joint based on principal component analysis to obtain key parameters; extracting a preset amount of historical alarm data from a monitoring alarm database as a training sample, and taking the key parameters as input to train a model to obtain an abnormality prediction model; inputting current key parameters of the MC4 joint marked as normal and normal state data into the abnormality prediction model for abnormality prediction according to the first judgment result, to obtain an abnormality prediction time, and then transmitting the abnormality prediction time to the control center; analyzing target monitoring elements matched with the MC4 joint marked as possibly abnormal to determine a correction coefficient; correcting pre-alarm data by using the correction coefficient to obtain corrected alarm data, and then transmitting the corrected alarm data to the control center. The response module is configured to make a corresponding response to the MC4 joint according to the received data by the control center, and store generated alarm information into a monitoring alarm database.

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