A cable channel monitoring system based on the Internet of Things

Abstract

The present invention relates to the field of facility monitoring technology, specifically a cable channel monitoring system based on the Internet of Things, the system includes an abnormal threshold adjustment module, a water seepage real-time monitoring module, a water seepage impact assessment module and a water seepage abnormal notification module. The present invention can dynamically monitor humidity and conductivity by adjusting the abnormal warning threshold in real time, thereby improving the monitoring accuracy, and the dynamic threshold can more accurately reflect the actual situation of the internal environment of the cable channel, reduce the risk of false alarms and missed alarms, and monitor humidity and conductivity in real time and compare the data with the dynamic threshold, so as to accurately identify the water seepage area and its degree. By evaluating the channel connectivity and node type of the water seepage area, the potential impact range and importance of the water seepage can be evaluated, and differentiated warning levels can be formulated according to the difficulty of maintenance, thereby reducing the impact of emergencies caused by water seepage on cable services and operations.

Description

Technical Field

[0001] The present invention relates to the technical field of facility monitoring, and in particular to a cable channel monitoring system based on the Internet of Things. Background Art

[0002] The field of facility monitoring technology focuses on real-time detection and evaluation of the structural health of infrastructure to ensure its operational safety and extend its service life. This field includes monitoring of key facilities such as bridges, tunnels, buildings, pipelines and cable channels. By deploying sensor networks to collect data about the status of facilities, and then using analytical software to process the data, early identification of structural defects, damage or performance degradation can be achieved. In addition, facility monitoring technology also involves data transmission and communication technology to ensure that monitoring data can be transmitted to the monitoring center in real time and effectively.

[0003] Among them, the cable channel monitoring system is a technical solution specifically used to monitor the interior of the cable channel. The system is usually composed of multiple sensors, which are arranged in key parts of the cable channel and can monitor the internal conditions of the cable channel in real time. The purpose of the system is mainly to monitor the internal status of the cable channel in real time, including preventing moisture from invading the cable channel and causing cable damage, insulation degradation or electrical failure, and ensuring the reliability and safety of infrastructure such as power and communications. By monitoring the conditions of the cable channel in real time and promptly discovering and handling abnormal conditions, it helps to extend the service life of the cable, reduce maintenance costs, and prevent larger-scale service interruptions caused by cable failures.

[0004] Traditional monitoring systems rely on fixed thresholds and simple monitoring mechanisms, and show obvious limitations when dealing with complex or changing environments. For example, fixed thresholds can lead to frequent false alarms or missed alarms, especially when the environmental conditions of the cable channel vary greatly. Traditional systems lack consideration of the importance of the structure and function of the cable channel, resulting in the monitoring system being unable to effectively distinguish between critical and non-critical areas, affecting the priority and resource allocation of emergency response measures. For example, once water seepage occurs, traditional systems may not be able to accurately determine its specific impact on the function of the cable channel, making it difficult for the maintenance team to prioritize key problem areas, resulting in unnecessary service interruptions or higher maintenance costs. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a cable channel monitoring system based on the Internet of Things.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a cable channel monitoring system based on the Internet of Things, the system comprising:

[0007] The abnormal threshold adjustment module analyzes the changes in humidity and conductivity in the cable channel during different time periods based on the historical monitoring data of the cable channel, identifies the change trend of the data in combination with the normal fluctuation range of the data, adjusts the abnormal warning thresholds of humidity and conductivity during different time periods, and obtains dynamic threshold information;

[0008] Based on the dynamic threshold information, the water seepage real-time monitoring module monitors the humidity and conductivity of the target area of ​​the cable channel in real time through the Internet of Things sensor, compares the humidity and conductivity of the target area with the adjusted abnormal warning threshold, identifies the abnormal state, and evaluates the water seepage degree of the water seepage area according to the current humidity and conductivity to obtain water seepage degree information;

[0009] The water seepage impact assessment module assesses the water seepage impact range based on the water seepage degree information and the channel connectivity of the cable channel water seepage area, and assesses the importance of the water seepage area in combination with the channel node type of the water seepage area to obtain an importance assessment result;

[0010] The water seepage abnormality notification module evaluates the severity of the water seepage based on the importance assessment result and the water seepage degree information, calculates the water seepage warning level according to the maintenance difficulty of the water seepage area, issues a water seepage warning of the corresponding level to the management personnel, and obtains water seepage warning notification information.

[0011] The present invention is improved in that the method for identifying the change trend of data is:

[0012] Based on the historical monitoring data of the cable channel, the humidity and conductivity data of the cable channel in the differentiated time period are extracted, and the data are sorted according to the timestamp to obtain the humidity and conductivity historical data;

[0013] Based on the humidity and conductivity historical data, the formula:

[0014] ;

[0015] Calculate the trend coefficient , through the trend coefficient The size of the data is used to evaluate the changing trend of the data, where is the trend coefficient, is the total number of data points, For time point data points, For data points The corresponding time point, is the average value of the data points, is the average value at the time point, , and is the weight coefficient, is the index.

[0016] The present invention is improved in that the step of obtaining the dynamic threshold information is:

[0017] Based on the historical monitoring data of the cable channel, the basic abnormal warning threshold is set according to the normal fluctuation range of the data;

[0018] Based on the basic abnormal warning threshold and trend coefficient , through the formula:

[0019] ;

[0020] Calculate the adjusted abnormal warning threshold to obtain dynamic threshold information, where: is the basic abnormal warning threshold, is the trend coefficient, is the exponential enhancement factor, is the stability adjustment factor, is the adjusted abnormal warning threshold, is the base of natural logarithms.

[0021] The present invention is improved in that the step of obtaining the water seepage degree information is:

[0022] Based on the dynamic threshold information, the humidity and conductivity of the target area of ​​the cable channel are monitored in real time by an IoT sensor to obtain real-time humidity and conductivity information;

[0023] Based on the real-time humidity and conductivity information, the formula:

[0024] ;

[0025] Calculate the water penetration index , and according to the water penetration index The size of the water seepage area is evaluated to obtain the water seepage degree information, where: is the humidity data, is the conductivity data, is the average humidity value, The average conductivity, is the adjusted abnormal warning threshold, is a constant, It is the water penetration index.

[0026] The present invention is improved in that the method for evaluating the water seepage impact range is:

[0027] According to the structural information of the cable channel, the connectivity data of the channel in the water seepage area is obtained, the key nodes and connection paths are identified, and the connectivity information is obtained;

[0028] Based on the connectivity information, by the formula:

[0029] ;

[0030] Calculate the water seepage impact score , score according to the scope of water seepage impact The value is used to evaluate the scope of water seepage, among which, is the total number of nodes in the cable channel, For the The water seepage impact on each node is From the seepage point to the The distance between nodes, is the distance attenuation factor, is the exponential decay rate of distance, is the normalization constant, Score the scope of water seepage impact. is the base of natural logarithms.

[0031] The present invention is improved in that the step of obtaining the importance evaluation result is:

[0032] According to the structural information of the cable channel, the channel node type of the water seepage area is obtained, including the function and strategic position of the water seepage area in the cable channel network, and a corresponding importance coefficient is assigned to each node, and the importance coefficient is preset based on the type of the node;

[0033] Scoring based on the importance factor and water seepage impact area , through the formula:

[0034] ;

[0035] Calculate importance score for water seepage areas , according to the importance of the water seepage area The importance of the seepage area is evaluated by the size of the value, and the importance evaluation result is obtained, among which, For the The water seepage impact score of each node, For the The importance coefficient of each node is is the total number of affected nodes, is the strategic enhancement factor of the node, is the normalization factor, Assign a score to the importance of the infiltration area.

[0036] The present invention is improved in that the method for evaluating the severity of water seepage is:

[0037] Based on the importance assessment results and water seepage information, extract the importance score of the water seepage area and water penetration index ;

[0038] Based on the importance score of the water infiltration area and water penetration index , through the formula:

[0039] ;

[0040] Calculating the Water Infiltration Severity Score , and score according to the severity of water seepage The value is used to evaluate the severity of water seepage, among which, Score the importance of the infiltration area, is the water penetration index, is the water seepage severity threshold, is the water seepage severity score, is the base of natural logarithms.

[0041] The present invention is improved in that the step of obtaining the water seepage warning notification information is as follows:

[0042] According to the structural information of the cable channel and the maintenance difficulty of each area, a maintenance difficulty coefficient is preset for each area, and the maintenance difficulty coefficient of the water seepage area is extracted;

[0043] Based on the maintenance difficulty coefficient and water seepage severity score of the water seepage area , through the formula:

[0044] ;

[0045] Calculate the water seepage warning level value ,in, is the water infiltration severity score, is the maintenance difficulty coefficient of the seepage area, is the threshold of the warning level, To adjust the parameters, is the exponential decay rate coefficient, is the water seepage warning level value, is the base of natural logarithms;

[0046] Based on the water seepage warning level value , compared with the preset water seepage warning level, a water seepage warning of the corresponding level is issued to the management personnel, and the water seepage warning notification information is obtained.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, by adjusting the abnormal warning threshold in real time, the humidity and conductivity can be dynamically monitored, thereby improving the monitoring accuracy. The dynamic threshold can more accurately reflect the actual situation of the internal environment of the cable channel, reducing the risk of false alarms and missed alarms. By monitoring the humidity and conductivity in real time and comparing the data with the dynamic threshold, the water seepage area and its degree can be accurately identified. By evaluating the channel connectivity and node type in the water seepage area, the potential impact scope and importance of the water seepage can be evaluated, and differentiated warning levels can be formulated according to the difficulty of maintenance, thereby optimizing the operation and maintenance efficiency of the cable channel and the ability to prevent faults, and reducing the impact of emergencies caused by water seepage on cable services and operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a system flow chart of the present invention;

[0050] Figure 2 A flow chart for identifying the changing trend of data for the present invention;

[0051] Figure 3 A flow chart of obtaining dynamic threshold information of the present invention;

[0052] Figure 4 A flow chart of obtaining water seepage degree information of the present invention;

[0053] Figure 5 A flow chart for evaluating the scope of water seepage impact in the present invention;

[0054] Figure 6 A flow chart for obtaining the significance assessment results for the present invention;

[0055] Figure 7 A flow chart for evaluating the severity of water infiltration for the present invention;

[0056] Figure 8 The present invention is a flow chart for obtaining water seepage warning notification information. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0059] Example: See Figure 1 The present invention provides a technical solution: a cable channel monitoring system based on the Internet of Things, the system comprising:

[0060] The abnormal threshold adjustment module analyzes the changes in humidity and conductivity in the cable channel during different time periods based on the historical monitoring data of the cable channel, identifies the change trend of the data in combination with the normal fluctuation range of the data, adjusts the abnormal warning thresholds of humidity and conductivity during different time periods, and obtains dynamic threshold information;

[0061] The water seepage real-time monitoring module monitors the humidity and conductivity of the target area of ​​the cable channel in real time through the IoT sensor based on the dynamic threshold information, compares the humidity and conductivity of the target area with the adjusted abnormal warning threshold, identifies the abnormal state, and evaluates the water seepage degree of the water seepage area based on the current humidity and conductivity to obtain the water seepage degree information;

[0062] The water seepage impact assessment module evaluates the water seepage impact range based on the water seepage degree information and the channel connectivity of the cable channel water seepage area, and evaluates the importance of the water seepage area in combination with the channel node type of the water seepage area to obtain the importance assessment result;

[0063] The water seepage abnormality notification module evaluates the severity of water seepage based on the importance assessment results and water seepage degree information, and calculates the water seepage warning level according to the maintenance difficulty of the water seepage area, and issues a water seepage warning of the corresponding level to the management personnel to obtain water seepage warning notification information;

[0064] Dynamic threshold information includes adjusted humidity threshold, conductivity threshold and data fluctuation rate; water seepage degree information includes water seepage rate, water seepage location and current humidity level; importance assessment results include priority of water seepage area, maintenance urgency and potential risk level; water seepage warning notification information includes warning level and warning time.

[0065] See also Figure 2 , the method to identify the changing trend of data is:

[0066] Based on the historical monitoring data of the cable channel, the humidity and conductivity data of the cable channel in the differentiated time period are extracted, and the data are sorted according to the timestamp to obtain the humidity and conductivity historical data;

[0067] Based on historical humidity and conductivity data, the formula:

[0068] ;

[0069] Calculate the trend coefficient , through the trend coefficient The size of the data is used to evaluate the changing trend of the data, where is the trend coefficient, is the total number of data points, For time point data points, For data points The corresponding time point, is the average value of the data points, is the average value at the time point, , and is the weight coefficient, is the index.

[0070] formula:

[0071] ;

[0072] The meaning and acquisition method of parameters:

[0073] : Trend coefficient, which indicates the trend strength and direction of data changing over time, is calculated by statistical methods, combining the covariance of time series data and the standard deviation of the variable.

[0074] : The total number of data points. The parameters are obtained from the actual monitored data set, such as the number of sampling points within a certain time window.

[0075] : At time point The data points are humidity or conductivity measurements taken directly from actual monitoring data.

[0076] : Data points The corresponding time points are obtained from the monitoring data, and the sampling time of each data point is recorded.

[0077] :all The average value of the data points, obtained by taking the arithmetic mean of all the observations.

[0078] :all The average value of a time point is obtained by taking the arithmetic mean of all time points.

[0079] , and : Weight coefficient, set according to data analysis requirements and previous research experience, used to adjust the influence of deviations in data values ​​and time points in trend analysis. Weights are usually determined by optimization algorithms to optimize the accuracy of trend analysis.

[0080] Calculation example:

[0081] Assume there is a simplified data set where , data points , the corresponding time point Assuming weights .

[0082] calculate and :

[0083] ;

[0084] Step-by-step calculation:

[0085] molecular:

[0086] ;

[0087] Denominator:

[0088] ;

[0089] Final calculation:

[0090] ;

[0091] Calculation example results Indicates that, over a given time period, the data points have a positive trend over time, with a medium strength trend.

[0092] See also Figure 3 , the steps for obtaining dynamic threshold information are:

[0093] Based on the historical monitoring data of the cable channel, the basic abnormal warning threshold is set according to the normal fluctuation range of the data;

[0094] Based on basic abnormal warning threshold and trend coefficient , through the formula:

[0095] ;

[0096] Calculate the adjusted abnormal warning threshold to obtain dynamic threshold information, where: is the basic abnormal warning threshold, is the trend coefficient, is the exponential enhancement factor, is the stability adjustment factor, is the adjusted abnormal warning threshold, is the base of natural logarithms.

[0097] formula:

[0098] ;

[0099] Detailed explanation and acquisition method of parameters:

[0100] Baseline Threshold : Obtained through statistical analysis of the normal fluctuation range of historical monitoring data. The mean and standard deviation of past data can be calculated, and then the threshold is set to the mean plus or minus several times the standard deviation to cover most data points.

[0101] Trend coefficient : The trend coefficient is calculated by the previous step.

[0102] Exponential Enhancement Factor : It is a preset parameter, which is set according to the sensitivity and change rate of the data and is used to adjust the influence of the trend coefficient. In actual settings, It can be determined based on historical sensitivity to changes in data.

[0103] Stability Adjustment Factor : It is a factor that mitigates the impact of the absolute value of the trend coefficient according to the need for threshold adjustment, and is usually set based on the frequency and severity of anomalies in historical data.

[0104] Calculation example:

[0105] Assuming a baseline threshold (Units can be %RH for humidity, or mS / cm for conductivity), trend coefficient (indicating a small upward trend), the exponential enhancement factor , stability adjustment factor .

[0106] Calculate the exponential part:

[0107] use To enhance the influence of the trend coefficient, the calculation result is:

[0108] .

[0109] Calculate the adjustment part in the denominator:

[0110] use To increase the stability of the adjustment process, the calculation result is:

[0111] ;

[0112] Calculate adjustment threshold :

[0113] ;

[0114] Calculation example results Indicates that based on current data trends, the threshold has been adjusted slightly higher to reflect the slight upward trend observed in the data.

[0115] See also Figure 4 , the steps for obtaining water seepage information are:

[0116] Based on dynamic threshold information, the humidity and conductivity of the target area of ​​the cable channel are monitored in real time through IoT sensors to obtain real-time humidity and conductivity information;

[0117] Based on real-time humidity and conductivity information, the formula:

[0118] ;

[0119] Calculate the water penetration index , and according to the water penetration index The size of the water seepage area is evaluated to obtain the water seepage degree information, where: is the humidity data, is the conductivity data, is the average humidity value, The average conductivity, is the adjusted abnormal warning threshold, is a constant, It is the water penetration index.

[0120] formula:

[0121] ;

[0122] Detailed explanation and acquisition method of parameters:

[0123] and :It is the real-time collection of humidity and conductivity data, which is obtained through real-time monitoring by sensors installed in the target area of ​​the cable channel to ensure that the data reflects the current environmental conditions.

[0124] and : The parameter represents the average value of humidity and conductivity calculated based on historical data. It is obtained by calculating the average value of data over a certain period of time in the past and is used to standardize and compare the current data point.

[0125] : The adjusted abnormal warning threshold, calculated in the previous step.

[0126] : is a constant used to adjust the smoothness of the logarithmic function to prevent numerical problems when the value is close to zero.

[0127] Calculation example:

[0128] Assumptions:

[0129] Real-time humidity data and conductivity , historical average humidity and conductivity , the adjusted threshold , adjustment factor , critical value .

[0130] Calculation steps:

[0131] Compute the sum of squared distance differences:

[0132] ;

[0133] Compute the logarithmic part:

[0134] ;

[0135] calculate :

[0136] ;

[0137] Calculation results The score indicates the current water seepage level. A larger value indicates a higher water seepage level. This result helps to take necessary maintenance measures in a timely manner to prevent further equipment damage or safety accidents.

[0138] See also Figure 5 , the method for evaluating the scope of water seepage is:

[0139] According to the structural information of the cable channel, the connectivity data of the channel in the water seepage area is obtained, the key nodes and connection paths are identified, and the connectivity information is obtained;

[0140] Based on the connectivity information, the formula is:

[0141] ;

[0142] Calculate the water seepage impact score , score according to the scope of water seepage impact The value is used to evaluate the scope of water seepage, among which, is the total number of nodes in the cable channel, For the The water seepage impact on each node is From the seepage point to the The distance between nodes, is the distance attenuation factor, is the exponential decay rate of distance, is the normalization constant, Score the scope of water seepage impact. is the base of natural logarithms.

[0143] formula:

[0144] ;

[0145] Detailed explanation and acquisition method of parameters:

[0146] : Represents the total number of nodes in the cable channel. The parameter is directly obtained from the design documents or system database of the cable channel, indicating how many monitoring points or nodes need to be considered in the entire network.

[0147] :Indicates the The degree of water seepage impact on each node can be evaluated and preset by experts based on the degree of water seepage.

[0148] :From the seepage point to the The distance between nodes is determined based on the physical layout of the cable channel and the actual line distance between nodes.

[0149] : Distance attenuation factor, used to adjust the weight of distance in impact assessment. It is an empirical value, set based on previous data analysis or simulation tests to reflect the actual impact of distance on impact propagation.

[0150] : exponential decay rate of distance, adjusting the influence of distance. The parameters are also set based on the fitting results of historical data and the seepage influence model.

[0151] : Normalization constant to ensure the calculation results The parameters are set according to the sum of the influence values ​​of all nodes to ensure The calculation result is the normalized score.

[0152] Calculation example:

[0153] Consider a simplified cable channel network with 5 nodes. Evaluate the impact of a specific water infiltration event on these nodes:

[0154] Number of nodes , the degree of impact , indicating the degree of water seepage influence on different nodes, and the distance Meters, distance attenuation factor , exponential decay rate , the normalization constant , assuming that all The sum of the values.

[0155] Calculate the influence weight of each node:

[0156] ;

[0157] For Node 1:

[0158] ;

[0159] For Node 2:

[0160] ;

[0161] For Node 3:

[0162] ;

[0163] For Node 4:

[0164] ;

[0165] For Node 5:

[0166] ;

[0167] Calculating the total impact score :

[0168] ;

[0169] Calculation results It means that based on the currently set model and parameters, the overall scope score of the water seepage impact is low, which means that the impact of the current water seepage event is limited or the impact is relatively light.

[0170] See also Figure 6 , the steps to obtain the importance assessment results are:

[0171] According to the structural information of the cable channel, the channel node type of the water seepage area is obtained, including the function and strategic position of the water seepage area in the cable channel network, and a corresponding importance coefficient is assigned to each node, and the importance coefficient is preset based on the type of the node;

[0172] Scoring based on importance factor and water seepage impact area , through the formula:

[0173] ;

[0174] Calculate importance score for water seepage areas , according to the importance of the water seepage area The importance of the seepage area is evaluated by the size of the value, and the importance evaluation result is obtained, among which, For the The water seepage impact score of each node, For the The importance coefficient of each node is is the total number of affected nodes, is the strategic enhancement factor of the node, is the normalization factor, Assign a score to the importance of the infiltration area.

[0175] formula:

[0176] ;

[0177] Detailed explanation and acquisition method of parameters:

[0178] :Indicates the The water seepage impact score of each node is calculated in the previous steps.

[0179] : No. The importance coefficient of each node is preset based on the function of the node and its strategic location in the cable network. For example, a relay station or a main connection node may have a higher importance coefficient.

[0180] : The strategic enhancement factor of the node, which is used to adjust the importance score to reflect the additional influence of the node's strategic position in the network. It is usually set based on the node's connection density and traffic volume.

[0181] : Normalization factor to ensure The values ​​are on an appropriate scale, and the values ​​are usually adjusted dynamically based on the overall impact range and number of nodes to keep the score consistent.

[0182] : The total number of affected nodes, obtained directly from the system configuration of the cable channel or the network layout data.

[0183] : The importance score of the seepage area is the final result of the calculation, which is used to quantify the severity of the seepage impact and the strategic importance of the node.

[0184] Calculation example:

[0185] Assuming there are 5 nodes, the water seepage impact score and importance coefficient of each node are as follows:

[0186] ;

[0187] ;

[0188] ;

[0189] ;

[0190] ;

[0191] Calculate the weighted importance of each node:

[0192] ;

[0193] For Node 1:

[0194] ;

[0195] For Node 2:

[0196] ;

[0197] For Node 3:

[0198] ;

[0199] For Node 4:

[0200] ;

[0201] For Node 5:

[0202] ;

[0203] Calculate the total importance score :

[0204] ;

[0205] Calculation results It represents the overall importance score of the water seepage area after comprehensively considering the degree of water seepage impact, node importance and strategic location. The score helps decision makers determine which areas need priority attention so as to rationally allocate resources and take appropriate response measures.

[0206] See also Figure 7 , the method for assessing the severity of water seepage is:

[0207] Extract the importance score of the water seepage area based on the importance assessment results and water seepage degree information and water penetration index ;

[0208] Importance score based on infiltration area and water penetration index , through the formula:

[0209] ;

[0210] Calculating the Water Infiltration Severity Score , and score according to the severity of water seepage The value is used to evaluate the severity of water seepage, among which, Score the importance of the infiltration area, is the water penetration index, is the water seepage severity threshold, is the water infiltration severity score, is the base of natural logarithms.

[0211] formula:

[0212] ;

[0213] Detailed explanation and acquisition method of parameters:

[0214] : Importance score of the seepage area, calculated in the previous step.

[0215] : Water seepage index, calculated by the previous steps.

[0216] :Water infiltration severity threshold, a value pre-set based on historical events and safety requirements to distinguish different levels of water infiltration severity. Helps determine when water infiltration conditions require additional attention or emergency response.

[0217] Calculation example:

[0218] The assumed scenario parameters are as follows:

[0219] : Indicates that the seepage area has high strategic importance.

[0220] : Indicates that the level of water seepage is moderate and has exceeded the normal safety threshold.

[0221] : Indicates that water seepage incidents reaching or exceeding this value are considered highly urgent.

[0222] Calculation process:

[0223] Application formula:

[0224] ;

[0225] Calculate the value of the exponential part:

[0226] ;

[0227] Compute the exponential function:

[0228] ;

[0229] Used in formula:

[0230] ;

[0231] Calculation results Indicates that based on the current water infiltration severity score, the water infiltration event is of low urgency, but still requires ongoing monitoring and assessment. The score can be used to notify managers of the potential risk of water infiltration and adjust response measures based on real-time data.

[0232] See also Figure 8 , the steps to obtain water seepage warning notification information are:

[0233] According to the structural information of the cable channel and the maintenance difficulty of each area, a maintenance difficulty coefficient is preset for each area, and the maintenance difficulty coefficient of the water seepage area is extracted;

[0234] Maintenance difficulty factor and water seepage severity score based on water seepage area , through the formula:

[0235] ;

[0236] Calculate the water seepage warning level value ,in, is the water infiltration severity score, is the maintenance difficulty coefficient of the seepage area, is the threshold of the warning level, To adjust the parameters, is the exponential decay rate coefficient, is the water seepage warning level value, is the base of natural logarithms;

[0237] Based on water seepage warning level value , compared with the preset water seepage warning level, a water seepage warning of the corresponding level is issued to the management personnel, and the water seepage warning notification information is obtained.

[0238] formula:

[0239] ;

[0240] Detailed explanation and acquisition method of parameters:

[0241] : Water seepage severity score, calculated by the previous step.

[0242] : The maintenance difficulty coefficient for the infiltration area is determined based on the area's geographic location, accessibility, previous maintenance history, and expected resource requirements. For example, areas that are difficult to reach or have historically had high maintenance costs will have a higher value.

[0243] : The threshold of the warning level is preset based on historical data and security requirements. This threshold helps determine under what circumstances the response level should be increased, and is usually closely related to the company's risk management strategy.

[0244] :It is a device used to adjust and A parameter that increases the sensitivity of the formula to small changes. This parameter can be adjusted based on simulations or analysis of previous events to improve the accuracy of the response.

[0245] : exponential decay rate coefficient, making the response to higher The setting of this parameter is based on an evaluation of responses to past events to optimize the warning system's reaction time and accuracy.

[0246] Calculation example:

[0247] Assume that the specific scenario parameters are as follows:

[0248] : Indicates a medium to high level of water infiltration severity.

[0249] : Indicates that the maintenance difficulty of the seepage area is relatively low.

[0250] : Indicates a lower warning level threshold.

[0251] : Increase the sensitivity of the formula.

[0252] : Strengthening response to hypertonic water severity score.

[0253] Calculation process:

[0254] Application formula:

[0255] ;

[0256] Compute the logarithmic part:

[0257] ;

[0258] Calculate the exponential function part:

[0259] ;

[0260] Used in formula:

[0261] ;

[0262] Calculation example results Indicates that based on current parameters, the water infiltration warning level is low and may not require an immediate emergency response, but continued monitoring and assessment should be carried out in case the situation deteriorates.

[0263] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A cable channel monitoring system based on the Internet of Things, characterized in that: The system comprises: The abnormal threshold adjustment module analyzes the changes in humidity and conductivity in the cable channel during different time periods based on the historical monitoring data of the cable channel, identifies the change trend of the data in combination with the normal fluctuation range of the data, adjusts the abnormal warning thresholds of humidity and conductivity during different time periods, and obtains dynamic threshold information; The method for identifying the change trend of data is: Based on the historical monitoring data of the cable channel, the humidity and conductivity data of the cable channel in the differentiated time period are extracted, and the data are sorted according to the timestamp to obtain the humidity and conductivity historical data; Based on the humidity and conductivity historical data, the formula: ； Calculate the trend coefficient , through the trend coefficient The size of the evaluation data is used to evaluate the changing trend of the data, where is the trend coefficient, is the total number of data points, For time point data points, For data points The corresponding time point, is the average value of the data points, is the average value at the time point, , and is the weight coefficient, is the index; The steps for obtaining the dynamic threshold information are: Based on the historical monitoring data of the cable channel, the basic abnormal warning threshold is set according to the normal fluctuation range of the data; Based on the basic abnormal warning threshold and trend coefficient , through the formula: ； Calculate the adjusted abnormal warning threshold to obtain dynamic threshold information, where: is the basic abnormal warning threshold, is the trend coefficient, is the exponential enhancement factor, is the stability adjustment factor, is the adjusted abnormal warning threshold, is the base of natural logarithms; Based on the dynamic threshold information, the water seepage real-time monitoring module monitors the humidity and conductivity of the target area of ​​the cable channel in real time through the Internet of Things sensor, compares the humidity and conductivity of the target area with the adjusted abnormal warning threshold, identifies the abnormal state, and evaluates the water seepage degree of the water seepage area according to the current humidity and conductivity to obtain water seepage degree information; The steps for obtaining the water seepage degree information are as follows: Based on the dynamic threshold information, the humidity and conductivity of the target area of ​​the cable channel are monitored in real time by an IoT sensor to obtain real-time humidity and conductivity information; Based on the real-time humidity and conductivity information, the formula: ； Calculate the water penetration index , and according to the water penetration index The size of the water seepage area is evaluated to obtain the water seepage degree information, where: is the humidity data, is the conductivity data, is the average humidity value, The average conductivity, is the adjusted abnormal warning threshold, is a constant, is the water seepage index; The water seepage impact assessment module assesses the water seepage impact range based on the water seepage degree information and the channel connectivity of the cable channel water seepage area, and assesses the importance of the water seepage area in combination with the channel node type of the water seepage area to obtain an importance assessment result; The method for evaluating the scope of water seepage is: According to the structural information of the cable channel, the connectivity data of the channel in the water seepage area is obtained, the key nodes and connection paths are identified, and the connectivity information is obtained; Based on the connectivity information, by the formula: ； Calculate the water seepage impact score , score according to the scope of water seepage impact The value is used to evaluate the scope of water seepage, among which, is the total number of nodes in the cable channel, For the The nodes are affected by water seepage. From the seepage point to the The distance between nodes, is the distance attenuation factor, is the exponential decay rate of distance, is the normalization constant, Score the scope of water seepage impact. is the base of natural logarithms; The steps for obtaining the importance assessment result are: According to the structural information of the cable channel, the channel node type of the water seepage area is obtained, including the function and strategic position of the water seepage area in the cable channel network, and a corresponding importance coefficient is assigned to each node, and the importance coefficient is preset based on the type of the node; Scoring based on the importance factor and water seepage impact area , through the formula: ； Calculate importance score for water seepage areas , according to the importance of the water seepage area The importance of the seepage area is evaluated by the size of the value, and the importance evaluation result is obtained, among which, For the The water seepage impact score of each node, For the The importance coefficient of each node is is the total number of affected nodes, is the strategic enhancement factor of the node, is the normalization factor, Score the importance of the infiltration area; The water seepage abnormality notification module evaluates the severity of the water seepage based on the importance assessment result and the water seepage degree information, calculates the water seepage warning level according to the maintenance difficulty of the water seepage area, issues a water seepage warning of the corresponding level to the management personnel, and obtains water seepage warning notification information; The method for assessing the severity of water seepage is: Based on the importance assessment results and water seepage information, extract the importance score of the water seepage area and water penetration index ; Based on the importance score of the water seepage area and water penetration index , through the formula: ； Calculating the Water Infiltration Severity Score , and score according to the severity of water seepage The value is used to evaluate the severity of water seepage, among which, Score the importance of the infiltration area, is the water penetration index, is the water seepage severity threshold, is the water infiltration severity score, is the base of natural logarithms; The steps for obtaining the water seepage warning notification information are as follows: According to the structural information of the cable channel and the maintenance difficulty of each area, a maintenance difficulty coefficient is preset for each area, and the maintenance difficulty coefficient of the water seepage area is extracted; Based on the maintenance difficulty coefficient and water seepage severity score of the water seepage area , through the formula: ； Calculate the water seepage warning level value ,in, is the water infiltration severity score, is the maintenance difficulty coefficient of the seepage area, is the threshold of the warning level, To adjust the parameters, is the exponential decay rate coefficient, is the water seepage warning level value, is the base of natural logarithms; Based on the water seepage warning level value , compared with the preset water seepage warning level, a water seepage warning of the corresponding level is issued to the management personnel, and the water seepage warning notification information is obtained.

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