Cable environment state detection method and terminal

Abstract

The invention discloses a cable environment state detection method and a terminal, and the method comprises the steps: obtaining environment measurement values obtained at each test time point to form an environment measurement value sequence, and calculating a first interpolation function according to the environment measurement value sequence; respectively acquiring standard measurement values closest to each environment measurement value from the standard measurement value range to form a standard measurement value sequence, and calculating a second interpolation function according to the standard measurement value sequence; calculating a correlation coefficient between a first coefficient column of the first interpolation function and a second coefficient of the second interpolation function; and obtaining a cable environment anomaly detection result according to the correlation coefficient. Whether the cable environment is abnormal or not can be evaluated according to the correlation reflected by the correlation coefficient, so that automatic monitoring of the cable environment is realized, the environment measurement value can be increased or decreased according to the characteristics of different environments, and targeted detection of the cable environment can be realized in environments with different characteristics.

Description

Technical Field

[0001] The present invention relates to the field of abnormality detection, and in particular to a cable environment state detection method and a terminal. Background Art

[0002] Cables are important transmission carriers for new power systems. Cables are widely used and in huge quantities, but they are generally located in harsh environments such as cable wells, cable trenches, and cable tunnels. Currently, cable operation and maintenance usually involves manual inspections with testing instruments, which is not only costly and inefficient, but also unable to monitor in real time the temperature, humidity, water level, and various gas contents of the cable environment that reflect or affect the operation of the cable. This results in the inability of operation and maintenance personnel to understand the state of the cable environment in a timely manner in order to take effective measures to prevent cable failures. In addition, it is impossible to take care of the location of each section of the deeply buried cable. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a cable environment status detection method and terminal to realize automatic and comprehensive detection of possible abnormalities in the environment where the cable is located.

[0004] In order to solve the above technical problems, a technical solution adopted by the present invention is:

[0005] A method for detecting a cable environment state comprises the following steps:

[0006] Obtaining environmental measurement values ​​obtained at each test time point to form an environmental measurement value series, and calculating a first interpolation function according to the environmental measurement value series;

[0007] Obtaining standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value series, and calculating a second interpolation function based on the standard measurement value series;

[0008] Calculating a correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function;

[0009] The cable environment abnormality detection result is obtained according to the correlation coefficient.

[0010] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0011] A cable environment status detection terminal comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0012] Acquire the environmental measurement values ​​obtained at each test time point to form an environmental measurement value series, and calculate a first interpolation function according to the environmental measurement value series;

[0013] Obtaining standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value series, and calculating a second interpolation function based on the standard measurement value series;

[0014] Calculating a correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function;

[0015] The cable environment abnormality detection result is obtained according to the correlation coefficient.

[0016] The beneficial effects of the present invention are as follows: environmental measurement values ​​are collected at fixed test time points by means of fixed sensors or the like to form an environmental measurement value series, and a first interpolation function obtained by measurement is calculated; a standard measurement value range is obtained, that is, a range in which measurement values ​​corresponding to a normal cable environment should exist, from which a standard measurement value closest to the environmental measurement value is obtained to obtain a standard measurement value series, and a second interpolation function corresponding to the standard measurement value is calculated; it can be seen that the first interpolation function is a response to the actual measured environmental measurement value status, and the second interpolation function is a response to the standard measurement value status corresponding to normal environmental data; at this time, by calculating the correlation coefficient between the first coefficient of the first interpolation function and the second coefficient of the second interpolation function, the correlation between the first interpolation function and the second interpolation function can be objectively obtained, and because the second interpolation function corresponds to a normal environmental measurement value, the correlation reflected by the correlation coefficient can be used to evaluate whether the cable environment is abnormal, thereby realizing automatic monitoring of the cable environment, and the environmental measurement value can be increased or decreased according to the characteristics of different environments, thereby realizing targeted detection of the cable environment in environments with different characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart of a method for detecting a cable environment state according to an embodiment of the present invention;

[0018] Figure 2 A block diagram of a cable environment status detection implementation module according to an embodiment of the present invention;

[0019] Figure 3 Another step flow chart of a cable environment status detection method according to an embodiment of the present invention;

[0020] Figure 4 A schematic diagram of the structure of a cable environment status detection terminal according to an embodiment of the present invention;

[0021] Description of labels:

[0022] 1. A cable environment status detection terminal; 2. A processor; 3. A memory. DETAILED DESCRIPTION

[0023] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0024] Please refer to Figure 1 , a cable environment status detection method, comprising the steps of:

[0025] Acquire the environmental measurement values ​​obtained at each test time point to form an environmental measurement value series, and calculate a first interpolation function according to the environmental measurement value series;

[0026] Obtaining standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value series, and calculating a second interpolation function based on the standard measurement value series;

[0027] Calculating a correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function;

[0028] The cable environment abnormality detection result is obtained according to the correlation coefficient.

[0029] From the above description, it can be seen that the beneficial effects of the present invention are: collecting environmental measurement values ​​at fixed test time points by means of fixed sensors or the like to form an environmental measurement value series, and calculating the measured first interpolation function; obtaining a standard measurement value range, that is, a range in which the measurement values ​​corresponding to a normal cable environment should exist, obtaining the standard measurement value closest to the environmental measurement value, obtaining the standard measurement value series, and calculating the second interpolation function corresponding to the standard measurement value; it can be seen that the first interpolation function is a response to the actual measured environmental measurement value status, and the second interpolation function is a response to the standard measurement value status corresponding to the normal environmental data; at this time, by calculating the correlation coefficient between the first coefficient of the first interpolation function and the second coefficient of the second interpolation function, the correlation between the first interpolation function and the second interpolation function can be objectively obtained. Since the second interpolation function corresponds to the normal environmental measurement value, the correlation reflected by the correlation coefficient can be used to evaluate whether the cable environment is abnormal, thereby realizing automatic monitoring of the cable environment, and the environmental measurement value can be increased or decreased according to the characteristics of different environments, thereby realizing targeted detection of the cable environment in environments with different characteristics.

[0030] Furthermore, the environmental measurement value series also includes a first test time point corresponding to each environmental measurement value;

[0031] Calculating the first interpolation function according to the environmental measurement value series includes:

[0032] A first interpolation function is calculated with the first test time point as an independent variable and the environmental measurement value as a dependent variable.

[0033] From the above description, it can be seen that the first interpolation function of the environmental measurement value with respect to time is generated, that is, the measurement value of the time point where no detection is performed is predicted based on the existing environmental measurement value. The first interpolation function can reflect the relationship between the environmental measurement value and time. Then, the first coefficient obtained by the first interpolation function in the fitting process can reflect the overall situation of the environmental measurement value.

[0034] Furthermore, the step of obtaining the standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value series includes:

[0035] Traversing the environmental measurement value sequence, when traversing to the target environmental measurement value, matching the standard measurement value closest to the target environmental measurement value from the standard measurement value range, and obtaining the first test time point corresponding to the target environmental measurement value as the second test time point corresponding to the standard measurement value;

[0036] The standard measurement value and the second test time point are stored in association with each other to obtain a standard measurement value series;

[0037] The calculating the second interpolation function according to the standard measurement value series comprises:

[0038] A second interpolation function is calculated with the second test time point as an independent variable and the standard measurement value as a dependent variable.

[0039] From the above description, it can be seen that the environmental measurement value series is traversed, the standard measurement values ​​closest to the environmental measurement values ​​are obtained one by one, and the first measurement time of the environmental measurement value is obtained and recorded as the second measurement time corresponding to the standard measurement value; the standard measurement value series is constructed according to the second measurement time and the standard measurement value, then the structure of the standard measurement value series corresponds to the structure of the environmental measurement value series, and the construction method of the second interpolation function also corresponds to the first interpolation function, which reduces the corresponding variables in the subsequent calculation of the correlation, so that the calculated correlation can better reflect the correlation between the environmental measurement value and the standard measurement value.

[0040] Further, the calculating the first interpolation function according to the environmental measurement value series includes:

[0041] Acquire a standard measurement value range, and acquire environmental measurement values ​​in the environmental measurement value series that exceed the standard measurement value range to form an abnormal measurement value series;

[0042] A first interpolation function is calculated according to the abnormal measurement value series.

[0043] It can be seen from the above description that when calculating the first interpolation function, the abnormal measurement values ​​in the environmental measurement value series are taken out, the abnormal measurement value series is constructed, and the first interpolation function is calculated for the abnormal measurement value series. By obtaining the abnormal measurement values ​​and then analyzing the abnormal measurement values, the values ​​that have a greater impact on the correlation are taken out in advance before the subsequent calculation steps are performed, which reduces the number of data to be calculated and thus reduces the amount of calculation. In addition, the abnormal measurement values ​​are values ​​that have a great impact on the judgment results. Taking them out for analysis separately improves the accuracy of the final analysis results and avoids interference from irrelevant quantities.

[0044] Furthermore, the first interpolation function and the second interpolation function are calculated by Newton interpolation method or Lagrange interpolation method.

[0045] From the above description, it can be seen that the first interpolation function and the second interpolation function are calculated by Newton interpolation method or Lagrange interpolation method. Both interpolation methods can realize the prediction function when the original data is provided, and can reflect the status of the environmental measurement value series or the standard measurement value series; and the Newton interpolation method has a smaller amount of calculation.

[0046] Further, the environmental measurement values ​​include temperature measurement values, humidity measurement values, water level measurement values ​​and gas content measurement values;

[0047] The step of acquiring the environmental measurement values ​​obtained at each test time point to form an environmental measurement value series, and calculating the first interpolation function according to the environmental measurement value series includes:

[0048] Obtaining the temperature measurement values ​​obtained at each test time point to form a temperature measurement value series, and calculating a first temperature interpolation function according to the temperature measurement value series;

[0049] Obtaining humidity measurement values ​​obtained at each test time point to form a humidity measurement value series, and calculating a first humidity interpolation function according to the humidity measurement value series;

[0050] Obtaining the water level measurement values ​​obtained at each test time point to form a water level measurement value series, and calculating a first water level interpolation function according to the water level measurement value series;

[0051] The gas content measurement values ​​obtained at each test time point are obtained to form a gas content measurement value series, and a first gas content interpolation function is calculated according to the gas content measurement value series.

[0052] From the above description, it can be known that for each measurement value type, the first interpolation function is calculated separately, and each measurement value type can be compared separately. If an abnormality occurs, the abnormal measurement value type can be quickly located, so that corresponding preparations can be made before going to the field.

[0053] Furthermore, the step of respectively obtaining standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value series, and calculating the second interpolation function according to the standard measurement value series includes:

[0054] For each measurement value type, respectively obtain the standard measurement value closest to each of the environmental measurement values ​​from the standard measurement value range corresponding to the measurement value type to form a standard measurement value series, and calculate the second interpolation function according to the standard measurement value series;

[0055] The measurement value types include temperature measurement values, humidity measurement values, water level measurement values, and gas content measurement values.

[0056] From the above description, it can be seen that for each measurement value type, the standard measurement value series is obtained and the corresponding second interpolation function is calculated. For the same measurement value type, the corresponding first interpolation function and the second interpolation function are constructed, which can perform a separate comparison for each measurement value type to improve accuracy.

[0057] Further, the calculating a correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function comprises:

[0058] Calculating a type correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function corresponding to each of the measurement value types;

[0059] Weighting the type correlation coefficient of each measurement value type to obtain a total correlation coefficient;

[0060] The obtaining of the cable environment abnormality detection result according to the correlation coefficient comprises:

[0061] The cable environment abnormality detection result is obtained according to the total correlation coefficient.

[0062] From the above description, it can be seen that after calculating the type correlation coefficient for each measurement value type separately, the type correlation coefficient is weighted according to the weights of different measurement value types to obtain the total correlation coefficient, and the total correlation coefficient is used to judge whether the overall environment is abnormal, that is, different measurement value type weights are set for different environments and different cables to adapt to different usage scenarios.

[0063] Further, obtaining the cable environment abnormality detection result according to the correlation coefficient includes:

[0064] When the correlation coefficient indicates correlation, the output cable environment is normal;

[0065] When the correlation coefficient indicates no correlation, there is an abnormality in the output cable environment.

[0066] From the above description, it can be seen that the second interpolation function is obtained based on the standard measurement value, reflecting the change of the standard measurement value over time. The correlation between the first interpolation function and the second interpolation function can be obtained by calculating the correlation between the first coefficient and the second coefficient, which can reflect the correlation between the measured environmental measurement value and the normal standard measurement value. Since the standard measurement value is the set normal value, the correlation with the standard measurement value is strong, indicating that the environmental measurement value is normal. If there is no correlation, it means that the environmental measurement value is abnormal and an early warning of cable environmental abnormality is required; thereby converting environmental abnormalities from manual judgment to automatic judgment.

[0067] Please refer to Figure 4 A cable environment status detection terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step in the above-mentioned cable environment status detection method is implemented.

[0068] The above-mentioned cable environment status detection method and terminal of the present invention can be applied to the automatic monitoring of cable anomalies; at present, promoting the clean and low-carbon transformation of energy, accelerating the creation of new power systems, vigorously serving the high-quality development of new energy, and promoting the intelligent transformation of power grid infrastructure are the trends of the times, and timely detection of important carrier cables for power transmission is an important link. In the present invention, the temperature, humidity, water level, various gas contents and other parameters of the cable environment can be monitored in real time and an alarm signal can be sent for abnormal phenomena, so as to notify the operation and maintenance personnel to handle and eliminate the faults as soon as possible, and realize intelligent operation and maintenance of cables. The following is an explanation through specific implementation methods.

[0069] Please refer to Figure 1-3 , Embodiment 1 of the present invention is:

[0070] A method for detecting a cable environment state comprises the following steps:

[0071] S1, obtaining the environmental measurement values ​​obtained at each test time point to form an environmental measurement value series; the environmental measurement value series also includes a first test time point corresponding to each environmental measurement value; the first test time point is the test time point at which the environmental measurement value is obtained;

[0072] In an optional embodiment, it includes:

[0073] S11. Select X equally spaced test time points in the time period t1-tX, where X is a positive integer, for example, the value of X can be 100; the i-th test time point is denoted as ti, i∈[1,X], and ti is denoted as t1, t2, t3, ..., ti, ..., tX in sequence;

[0074] S12, measuring the environmental measurement value at the i-th test time point and recording it as Ai, and obtaining A1, A2, A3, ..., Ai, ..., AX, X groups of (ti, Ai) data corresponding to each test time point to form an environmental measurement value sequence;

[0075] In an optional implementation, the environmental measurement values ​​include several different measurement value types, including temperature measurement values, humidity measurement values, water level measurement values, and gas content measurement values. In actual configuration, the types of environmental measurement values ​​may be increased or decreased for different cable types or environments. For example, water level detection may not be performed for cables laid in desert areas, so as to adapt to different environments and avoid redundant calculations.

[0076] In an optional embodiment, environmental measurement values ​​are obtained for each measurement value type, including: obtaining the temperature measurement value obtained at each test time point to form a temperature measurement value series; obtaining the humidity measurement value obtained at each test time point to form a humidity measurement value series; obtaining the water level measurement value obtained at each test time point to form a water level measurement value series; obtaining the gas content measurement value obtained at each test time point to form a gas content measurement value series;

[0077] S2. Calculate a first interpolation function according to the environmental measurement value series; specifically, calculate the first interpolation function with the first test time point as an independent variable and the environmental measurement value as a dependent variable;

[0078] In an optional implementation, the method includes calculating a first interpolation function according to a series of environmental measurement values ​​using Newton interpolation method:

[0079] The first interpolation function G1(t) is calculated by Newton interpolation method with the first test time point as the independent variable and the environmental measurement value as the dependent variable:

[0080] G1(t)=α11+α12(t-t1)+α13(t-t1)(t-t2)+α14(t-t1)(t-t2)(t-t3)+…+α1i(t-t1)(t-t2)…(t-(ti-1));

[0081] Where α1i is the i-th coefficient of the mathematical model G1(t), where:

[0082] α11=A1;

[0083]

[0084] …

[0085]

[0086] f11[t1,t2,t3,…,ti-1,ti] represents the difference quotient;

[0087] In an optional implementation, the method includes calculating the first interpolation function G2(t) according to the environmental measurement value series using the Lagrange interpolation method:

[0088] G2(t)=

[0089] α21·(t-t2)(t-t3)(t-t4)…(t-ti)…(t-tX)+

[0090] α22·(t-t1)(t-t3)(t-t4)…(t-ti)…(t-tX)+

[0091] α23·(t-t1)(t-t2)(t-t4)…(t-ti)…(t-tX)+

[0092] …+

[0093] α2i·(t-t1)(t-t2)(t-t3)…(t-(ti-1))(t-(ti+1))…(t-tX)+

[0094] …+

[0095] α2X·(t-t1)(t-t2)(t-t3)…(t-ti)…(tt(X-1)),

[0096] Where α2i is the i-th coefficient of the mathematical model G2(t), and X is the total number of environmental measurement values ​​in the environmental measurement value series;

[0097]

[0098] …

[0099]

[0100] …

[0101]

[0102] In an optional embodiment, generating a first interpolation function for each measurement value type includes: calculating a first temperature interpolation function according to the temperature measurement value series; calculating a first humidity interpolation function according to the humidity measurement value series; calculating a first water level interpolation function according to the water level measurement value series; calculating a first gas content interpolation function according to the gas content measurement value series;

[0103] S3, respectively obtaining the standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value series, including:

[0104] S31, traversing the environmental measurement value series, when traversing to the target environmental measurement value, matching the standard measurement value closest to the target environmental measurement value from the standard measurement value range, and obtaining the first test time point corresponding to the target environmental measurement value as the second test time point corresponding to the standard measurement value;

[0105] In an optional implementation, a standard measurement range BL to BH is obtained, and when the i-th environmental measurement value Ai is traversed, the closest standard measurement value Bi is matched within the range BL to BH; if the provided range value is a continuous range, then when Ai is within the range BL to BH, the closest Bi is Ai itself; when Ai is outside the range BL to BH, the closest Bi is the endpoint value of BL or BH closest to Ai; if the range BL to BH consists of multiple discontinuous values, then each value in the range BL to BH is compared one by one with the temperature signal value Ai, and the value with the smallest absolute value of the difference between the two is the standard value Bi closest to the temperature signal value Ai;

[0106] S32, associatively storing the standard measurement value and the second test time point to obtain a standard measurement value series; that is, for the environmental measurement value obtained at the test time point, the test time point is marked as the first test time point in the environmental measurement value series, and the test time point is marked as the second test time point in the standard measurement value series; that is, the corresponding environmental measurement value and standard measurement value can be obtained by obtaining the same first test time point and second test time point; that is, finally obtaining a standard measurement value series B1, B2, B3, ..., Bi, ..., B98, B99, BX corresponding to the environmental measurement value series, a total of X groups of (ti, Bi) data, forming a standard measurement value series;

[0107] In an optional implementation, for each measurement value type, the standard measurement value closest to each of the environmental measurement values ​​is obtained from the standard measurement value range corresponding to the measurement value type to form a standard measurement value series, that is, for each measurement value type, S31 and S32 are executed to obtain a temperature standard measurement value series, a humidity standard measurement value series, a water level standard measurement value series, and a gas content standard measurement value series;

[0108] S4, calculating a second interpolation function according to the standard measurement value series; specifically, calculating the second interpolation function with the second test time point as an independent variable and the standard measurement value as a dependent variable;

[0109] In an optional implementation, the second interpolation function is calculated according to the standard measurement value series using Newton interpolation method:

[0110] The second interpolation function H1(t) is calculated by Newton interpolation method with the second test time point as the independent variable and the standard measurement value as the dependent variable:

[0111] H1(t)=β11+β12(t-t1)+β13(t-t1)(t-t2)+β14(t-t1)(t-t2)(t-t3)+…+β1i(t-t1)(t-t2)…(t-(ti-1));

[0112] Where β1i is the i-th coefficient of the mathematical model H1(t), where:

[0113] β11=B1;

[0114]

[0115]

[0116] …

[0117]

[0118] F11[t1,t2,t3,…,ti-1,ti] represents the difference quotient;

[0119] In an optional implementation, the second interpolation function H2(t) is calculated according to the standard measurement value series using the Lagrange interpolation method:

[0120] H2(t)=

[0121] β21·(t-t2)(t-t3)(t-t4)…(t-tj)…(t-tX)+

[0122] β22·(t-t1)(t-t3)(t-t4)…(t-tj)…(t-tX)+

[0123] β23·(t-t1)(t-t2)(t-t4)…(t-tj)…(t-tX)+

[0124] …+

[0125] β2i·(t-t1)(t-t2)(t-t3)…(t-(tj-1))(t-(ti+1))…(t-tX)+

[0126] …+

[0127] β2X·(t-t1)(t-t2)(t-t3)…(t-ti)…(tt(X-1)),

[0128] Where β2i is the i-th coefficient of the mathematical model H2(t), X is the total number of standard measurement values ​​in the standard measurement value series, which is the same as the total number of environmental measurement values ​​in the corresponding environmental measurement value series; where:

[0129]

[0130] …

[0131]

[0132] …

[0133]

[0134] In an optional implementation, for each measurement value type, a second interpolation function is calculated according to a standard measurement value series to obtain a second temperature interpolation function, a second humidity interpolation function, a second water level interpolation function, and a second gas content interpolation function;

[0135] S5. Calculating a correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function, comprising:

[0136] S51, calculating a type correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function corresponding to each measurement value type;

[0137] (1) Obtain the first coefficient of the first interpolation function as vector C1:

[0138] C11={α11,α12,α13,α14,…,α1i}; where α1i is the i-th coefficient of the mathematical model G1(t), i∈[1,X], an integer;

[0139] If the first interpolation function is calculated by the Lagrange interpolation method, the corresponding first coefficient is obtained as a vector C12 = {α21, α22, α23, α24, ..., α2i};

[0140] (2) Obtain the second coefficient of the second interpolation function as vector C2:

[0141] C21={β11,β12,β13,β14,…,β1i}; where β1i is the i-th coefficient of the mathematical model H1(t), i∈[1,X];

[0142] If the second interpolation function is calculated by the Lagrange interpolation method, the corresponding second coefficient is obtained as a vector C22 = {β21, β22, β23, β24, ..., β2i};

[0143] (3) Calculate the type correlation coefficient R between the first coefficient and the second coefficient:

[0144] Where C1·C2 represents the inner product of vectors C1 and C2; |C1| is the modulus of vector C1, and |C2| is the modulus of vector C2;

[0145] S52. Weight the type correlation coefficients of each of the said measurement value types to obtain a total correlation coefficient; mark the type correlation coefficient between the first coefficient and the second coefficient corresponding to different measurement value types in S51 as Ri, and obtain the weight λi corresponding to Ri; then the total correlation coefficient RN is:

[0146] RN = λi × Ri; where the sum of λi is 1;

[0147] S6. Obtain the cable environment anomaly detection result according to the said correlation coefficient, including: when the said correlation coefficient indicates correlation, output that the cable environment is normal; when the said correlation coefficient indicates non - correlation, output that there is an anomaly in the cable environment;

[0148] In an alternative embodiment, refine the situation of there being an anomaly:

[0149] When RN ≤ k1, the cable environment state is seriously unsatisfactory,

[0150] When k1 < RN ≤ k2, the cable environment state is moderately unsatisfactory,

[0151] When k2 < RN ≤ k3, the cable environment state is slightly unsatisfactory,

[0152] When k3 < RN ≤ 1, the cable environment state is in a normal state,

[0153] where 0 < k1 < k2 < k3 < 1.

[0154] The second implementation of the present invention is:

[0155] A method for detecting the cable environment state, which is different from the first embodiment in that:

[0156] In step S2, the standard measurement value range is obtained, and the environmental measurement values ​​exceeding the standard measurement value range in the environmental measurement value series are obtained to form an abnormal measurement value series. In the abnormal measurement value series, the time t is re-numbered as t1, t2, t3…, tj,…, tk to avoid the problem of discontinuity of time t after obtaining abnormal measurement values ​​from the environmental measurement value series, j∈[1,k], k represents the total number of abnormal measurement values ​​in the abnormal measurement value series; a first interpolation function is calculated according to the abnormal measurement value series; that is, the first interpolation function is calculated for the environmental measurement value series after the normal values ​​are removed, and the abnormal part is analyzed in detail to reduce the amount of calculation; if the abnormal measurement value series is empty, that is, there are no environmental measurement values ​​exceeding the standard measurement range, then the normal cable environment is directly output; that is, if there are abnormal environmental measurement values, it is necessary to further verify whether the cable environment is abnormal by comparing the correlation between the abnormal environmental measurement values ​​and the standard measurement values; and if the detected environmental detection values ​​have all fallen into the standard measurement value range, there is no need to verify again, and the cable environment can be directly determined to be normal, thereby further reducing the amount of calculation;

[0157] Then S2, calculating a first interpolation function according to the abnormal measurement value series; specifically, calculating the first interpolation function with the first test time point as an independent variable and the abnormal measurement value as a dependent variable;

[0158] In an optional implementation, the method includes calculating a first interpolation function according to the abnormal measurement value series using Newton interpolation method:

[0159] The first test time point is used as the independent variable and the abnormal measurement value is used as the dependent variable to calculate the first interpolation function G3(t) by Newton interpolation method:

[0160] G3(t)=α31+α32(t-t1)+α33(t-t1)(t-t2)+α34(t-t1)(t-t2)(t-t3)+…+α3j(t-t1)(t-t2)…(t-(tj-1));

[0161] Where α3j is the jth coefficient of the mathematical model G3(t), where:

[0162] α31=A1;

[0163]

[0164] …

[0165]

[0166] f31[t1,t2,t3,…,tj-1,tj] represents the difference quotient;

[0167] In an optional implementation, the method includes calculating the first interpolation function G4(t) according to the environmental measurement value series using the Lagrange interpolation method:

[0168] G4(t)=

[0169] α41·(t-t2)(t-t3)(t-t4)…(t-tj)…(t-tk)+

[0170] α42·(t-t1)(t-t3)(t-t4)…(t-tj)…(t-tk)+

[0171] α43·(t-t1)(t-t2)(t-t4)…(t-tj)…(t-tk)+

[0172] …+

[0173] α4j·(t-t1)(t-t2)(t-t3)…(t-(tj-1))(t-(tj+1))…(t-tk)+

[0174] …+

[0175] α4k·(t-t1)(t-t2)(t-t3)…(t-tj)…(tt(k-1)),

[0176] Where α4j is the jth coefficient of the mathematical model G4(t), and k is the total number of abnormal measurement values ​​in the abnormal measurement value series;

[0177]

[0178] …

[0179]

[0180] …

[0181]

[0182] In an optional embodiment, a first interpolation function is generated for each measurement value type, including: calculating a first temperature interpolation function according to the temperature abnormality measurement value series; calculating a first humidity interpolation function according to the humidity abnormality measurement value series; calculating a first water level interpolation function according to the water level abnormality measurement value series; calculating a first gas content interpolation function according to the gas content abnormality measurement value series;

[0183] S3, respectively obtaining the standard measurement values ​​closest to each of the abnormal measurement values ​​from the standard measurement value range to form a standard measurement value series, including:

[0184] S31, traversing the abnormal measurement value sequence, when traversing to the target abnormal measurement value, matching the standard measurement value closest to the target abnormal measurement value from the standard measurement value range, and obtaining the first test time point tj corresponding to the target abnormal measurement value as the second test time point corresponding to the standard measurement value;

[0185] In an optional implementation, a standard measurement range BL to BH is obtained, and when the jth abnormal measurement value Aj is traversed, the closest standard measurement value Bj is matched within the range BL to BH; if the provided range value is a continuous range, when Aj is within the range BL to BH, the closest Bj is Aj itself; when Aj is outside the range BL to BH, the closest Bj is the endpoint value of BL or BH closest to Aj; if the range BL to BH consists of multiple discontinuous values, each value in the range BL to BH is compared with the temperature signal value Aj one by one, and the value with the smallest absolute value of the difference between the two is the standard value Bj closest to the temperature signal value Aj;

[0186] S32, associatively storing the standard measurement value and the second test time point to obtain a standard measurement value series; that is, for the abnormal measurement value obtained at the test time point, the test time point is marked as the first test time point in the abnormal measurement value series, and the test time point is marked as the second test time point in the standard measurement value series; that is, by obtaining the same first test time point and second test time point, the corresponding abnormal measurement value and standard measurement value can be obtained; that is, finally, a standard measurement value series B1, B2, B3, ..., Bi, ..., B98, B99, Bk corresponding to the abnormal measurement value series is obtained, with a total of k groups (ti, Bi) of data, constituting a standard measurement value series;

[0187] In an optional implementation, for each measurement value type, the standard measurement value closest to each abnormal measurement value is obtained from the standard measurement value range corresponding to the measurement type to form a standard measurement value series, that is, for each measurement value type, S31 and S32 are executed to obtain a temperature standard measurement value series, a humidity standard measurement value series, a water level standard measurement value series, and a gas content standard measurement value series;

[0188] S4, calculating a second interpolation function according to the standard measurement value series; specifically, calculating the second interpolation function with the second test time point as an independent variable and the standard measurement value as a dependent variable;

[0189] In an optional implementation, the second interpolation function is calculated according to the standard measurement value series using Newton interpolation method:

[0190] The second interpolation function H3(t) is calculated by Newton interpolation method with the second test time point as the independent variable and the standard measurement value as the dependent variable:

[0191] H3(t)=β31+β32(t-t1)+β33(t-t1)(t-t2)+β34(t-t1)(t-t2)(t-t3)+…+β3j(t-t1)(t-t2)…(t-(tj-1));

[0192] Where β3j is the jth coefficient of the mathematical model H3(t), where:

[0193] β31 = B1;

[0194]

[0195] …

[0196]

[0197] F31[t1,t2,t3,…,tj-1,tj] represents the difference quotient;

[0198] In an optional implementation, the second interpolation function H4(t) is calculated according to the standard measurement value series using the Lagrange interpolation method:

[0199] H4(t)=

[0200] β41·(t-t2)(t-t3)(t-t4)…(t-tj)…(t-tk)+

[0201] β42·(t-t1)(t-t3)(t-t4)…(t-tj)…(t-tk)+

[0202] β43·(t-t1)(t-t2)(t-t4)…(t-tj)…(t-tk)+

[0203] …+

[0204] β4j·(t-t1)(t-t2)(t-t3)…(t-(tj-1))(t-(tj+1))…(t-tk)+

[0205] …+

[0206] β4k·(t-t1)(t-t2)(t-t3)…(t-tj)…(tt(k-1)),

[0207] Where β4j is the jth coefficient of the mathematical model H4(t), k is the total number of standard measurements in the standard measurement series, which is the same as the total number of abnormal measurements in the corresponding abnormal measurement series; where:

[0208]

[0209] …

[0210]

[0211] …

[0212]

[0213] In an optional implementation, for each measurement value type, a second interpolation function is calculated according to a standard measurement value series to obtain a second temperature interpolation function, a second humidity interpolation function, a second water level interpolation function, and a second gas content interpolation function;

[0214] S5. Calculating a correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function, comprising:

[0215] S51, calculating a type correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function corresponding to each measurement value type;

[0216] (1) Obtain the first coefficient of the first interpolation function as vector C1:

[0217] C13={α31,α32,α33,α34,…,α3j};where α3j is the j-th coefficient of the mathematical model G3(t), and j∈[1,k] is an integer;

[0218] If the first interpolation function is calculated by the Lagrange interpolation method, the corresponding first coefficient is obtained as a vector C14={α41, α42, α43, α44, ..., α4j};

[0219] (2) Obtain the second coefficient of the second interpolation function as vector C2:

[0220] C23={β31,β32,β33,β34,…,β3j};where β3j is the jth coefficient of the mathematical model H3(t), and j∈[1,k] is an integer;

[0221] If the second interpolation function is calculated by the Lagrange interpolation method, the corresponding second coefficient is obtained as a vector C24={β41, β42, β43, β44, ..., β4j};

[0222] (3) Calculate the type correlation coefficient R between the first coefficient and the second coefficient:

[0223] where C1·C2 represents the inner product of vectors C1 and C2; |C1| is the modulus of vector C1, and |C2| is the modulus of vector C2; since the proportion of abnormal measurement values in the initially obtained environmental measurement values is also an important factor affecting the judgment result of whether the environment is normal, in addition to calculating the correlation degree between abnormal measurement values and standard measurement values, it is also necessary to multiply by the proportion of normal measurement values excluding abnormal measurement values as an adjustment value; for example, there are two sequences of abnormal measurement values, and the directly calculated correlation coefficients are both 0.9, but the proportion of one sequence of abnormal measurement values in the sequence of environmental measurement values is 50%, and the proportion of the other sequence of abnormal measurement values in the sequence of environmental measurement values is 20%, indicating that the proportions of normal measurement values are 50% and 80% respectively. It can be seen that the cable environment corresponding to the sequence of environmental measurement values with 80% of normal measurement values is healthier. Adding a proportionality coefficient can distinguish the influence of the proportion of abnormal measurement values on the final result;

[0224] S52. Weight the type correlation coefficient of each of the measurement value types to obtain a total correlation coefficient; mark the type correlation coefficient between the first coefficient and the second coefficient corresponding to different measurement value types in S51 as Rj, and obtain the weight λj corresponding to Rj; then the total correlation coefficient RN is:

[0225] RN = λj × Rj; where the sum of λi is 1;

[0226] S6. Obtain the cable environment anomaly detection result according to the correlation coefficient, including: when the correlation coefficient indicates correlation, output that the cable environment is normal; when the correlation coefficient indicates non - correlation, output that there is an anomaly in the cable environment;

[0227] In an alternative embodiment, the situation of existing anomalies is refined:

[0228] When RN ≤ k1, the cable environment state is seriously unsatisfactory,

[0229] When k1 < RN ≤ k2, the cable environment state is moderately unsatisfactory,

[0230] When k2 < RN ≤ k3, the cable environment state is slightly unsatisfactory,

[0231] When k3 < RN ≤ 1, the cable environment state is in a normal state,

[0232] where 0 < k1 < k2 < k3 < 1.

[0233] Please refer to Figure 4 , Embodiment 3 of the present invention is:

[0234] A cable environment status detection terminal 1, comprising a processor 2, a memory 3, and a computer program stored in the memory 3 and executable on the processor 2, wherein the processor 2 implements each step of a cable environment status detection method in Embodiment 1 or Embodiment 2 when executing the computer program;

[0235] In an optional embodiment, environmental measurement values ​​are received through a data sending module; the environmental measurement values ​​are collected by a signal acquisition module and sent to the data sending module, and the signal acquisition module includes a temperature signal acquisition module, a humidity signal acquisition module, a water level signal acquisition module and various gas content signal acquisition modules; the data sending module sends the environmental measurement values ​​to a processor module, and after the processor module executes S1-S6, the execution results are sent to a computer display interface and a mobile phone display interface for operation and maintenance personnel to view; the temperature measurement values, humidity measurement values, water level measurement values ​​and gas content measurement values ​​of the measurement points can also be directly displayed on the computer display interface and the mobile phone display interface.

[0236] In summary, the present invention provides a cable environmental status detection method and terminal, which obtains an environmental measurement value series by collecting environmental measurement values ​​at the test time point, and then obtains the standard measurement value closest to the environmental measurement value for each environmental measurement value, and calculates the first interpolation function corresponding to the environmental measurement value series and the second interpolation function corresponding to the standard measurement value series, and calculates the correlation between the coefficients of the first interpolation function and the second interpolation function to judge whether the environmental measurement value is normal, thereby realizing automatic judgment. In addition, for the cable and the environment in which it is located, not only does it not require manual inspection and operation and maintenance, but it also realizes low-cost and high-efficiency operation and maintenance; it can also monitor the environmental status of the cable in real time, which is convenient for the operation and maintenance personnel to understand the environmental parameters of the cable in real time, so that the operation and maintenance personnel can take preventive and effective measures in advance to avoid the occurrence of faults, or after the cable fault occurs, the operation and maintenance personnel can handle the fault in the first time to avoid the accident from becoming more serious or spreading outward, and truly realize the intelligent operation and maintenance of the cable.

[0237] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A cable environment status detection method, characterized in that: Includes steps: Obtaining environmental measurement values ​​obtained at each test time point to form an environmental measurement value series, and calculating a first interpolation function according to the environmental measurement value series; Obtaining standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value series, and calculating a second interpolation function based on the standard measurement value series; Calculating a correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function; The cable environment abnormality detection result is obtained according to the correlation coefficient.

2. A cable environment status detection method according to claim 1, characterized in that: The environmental measurement value series also includes a first test time point corresponding to each environmental measurement value; Calculating the first interpolation function according to the environmental measurement value series includes: A first interpolation function is calculated with the first test time point as an independent variable and the environmental measurement value as a dependent variable.

3. A cable environment status detection method according to claim 2, characterized in that: The step of respectively obtaining the standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value sequence comprises: Traversing the environmental measurement value sequence, when traversing to the target environmental measurement value, matching the standard measurement value closest to the target environmental measurement value from the standard measurement value range, and obtaining the first test time point corresponding to the target environmental measurement value as the second test time point corresponding to the standard measurement value; The standard measurement value and the second test time point are stored in association with each other to obtain a standard measurement value series; The calculating the second interpolation function according to the standard measurement value series comprises: A second interpolation function is calculated with the second test time point as an independent variable and the standard measurement value as a dependent variable.

4. A cable environment status detection method according to claim 1, characterized in that: Calculating the first interpolation function according to the environmental measurement value series includes: Acquire a standard measurement value range, and acquire environmental measurement values ​​in the environmental measurement value series that exceed the standard measurement value range to form an abnormal measurement value series; A first interpolation function is calculated according to the abnormal measurement value series.

5. A cable environment status detection method according to claim 1, characterized in that: The first interpolation function and the second interpolation function are calculated by Newton interpolation method or Lagrange interpolation method.

6. A cable environment status detection method according to claim 1, characterized in that: The environmental measurements include temperature measurements, humidity measurements, water level measurements, and gas content measurements; The step of acquiring the environmental measurement values ​​obtained at each test time point to form an environmental measurement value series, and calculating the first interpolation function according to the environmental measurement value series includes: Obtaining the temperature measurement values ​​obtained at each test time point to form a temperature measurement value series, and calculating a first temperature interpolation function according to the temperature measurement value series; Obtaining humidity measurement values ​​obtained at each test time point to form a humidity measurement value series, and calculating a first humidity interpolation function according to the humidity measurement value series; Obtaining the water level measurement values ​​obtained at each test time point to form a water level measurement value series, and calculating a first water level interpolation function according to the water level measurement value series; The gas content measurement values ​​obtained at each test time point are obtained to form a gas content measurement value series, and a first gas content interpolation function is calculated according to the gas content measurement value series.

7. A cable environment status detection method according to claim 6, characterized in that: The step of respectively obtaining the standard measurement values ​​closest to each of the environmental measurement values ​​from the standard measurement value range to form a standard measurement value series, and calculating the second interpolation function according to the standard measurement value series comprises: For each measurement value type, respectively obtain the standard measurement value closest to each of the environmental measurement values ​​from the standard measurement value range corresponding to the measurement value type to form a standard measurement value series, and calculate the second interpolation function according to the standard measurement value series; The measurement value types include temperature measurement values, humidity measurement values, water level measurement values, and gas content measurement values.

8. A cable environment status detection method according to claim 7, characterized in that: The calculating the correlation coefficient between the first coefficient of the first interpolation function and the second coefficient of the second interpolation function comprises: Calculating a type correlation coefficient between a first coefficient of the first interpolation function and a second coefficient of the second interpolation function corresponding to each of the measurement value types; Weighting the type correlation coefficient of each measurement value type to obtain a total correlation coefficient; The obtaining of the cable environment abnormality detection result according to the correlation coefficient comprises: The cable environment abnormality detection result is obtained according to the total correlation coefficient.

9. A cable environment status detection method according to claim 1, characterized in that: The obtaining of the cable environment abnormality detection result according to the correlation coefficient comprises: When the correlation coefficient indicates correlation, the output cable environment is normal; When the correlation coefficient indicates no correlation, there is an abnormality in the output cable environment.

10. A cable environment status detection terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps in the cable environment status detection method described in any one of claims 1-9 are implemented.

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