JP2015163878A - Deterioration diagnosis device of insulation material, deterioration diagnosis method, and deterioration diagnosis program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To diagnose deterioration of insulation material.SOLUTION: A deterioration diagnosis device 1 includes a document output tool 23. The document output tool 23 estimates an insulation resistance value of insulating material on the basis of an actual value 14 of an evaluation item previously set for insulating material, a type (A, B) of an instrument including the insulating material, and unit space information (21A, 21B) corresponding to that type. The document output tool 23 obtains a remaining lifetime of the insulating material on the basis of the estimated insulation resistance value.

Description

  Embodiments described herein relate generally to a deterioration diagnosis apparatus, a deterioration diagnosis method, and a deterioration diagnosis program for diagnosing a deterioration state of a used insulating material.

  Electric power facilities are important facilities that support social infrastructure, and long-term stable operation is required. In order to ensure stable operation, it is necessary to grasp the state of deterioration of power facilities and to carry out maintenance and renewal systematically. Insulating materials used for conductor support or barriers of electric power facilities may deteriorate in insulation properties due to aging of the materials themselves, adhesion of dust or gas floating in the installation environment, and the like. When the insulating property of the insulating material is lowered, discharge or tracking is generated. Therefore, the lowered insulating property of the insulating material causes the facility to stop. Therefore, insulating materials tend to be targeted for degradation diagnosis.

  The deterioration of the insulating material based on the installation environment is affected not only by the above-mentioned contamination due to the adhesion of dust or gas, but also by environmental factors that react with the components of the insulating material. In an environment where there are environmental factors that react with the components of the insulating material, the insulating material may deteriorate at a rate that exceeds normal aging. For example, in an insulating material using calcium carbonate as an inorganic filler, when the calcium carbonate reacts with a chlorine-based gas or a nitrogen oxide gas, calcium chloride or calcium nitrate is formed on the surface of the insulating material. These substances such as calcium chloride or calcium nitrate deliquesce by inhaling moisture even at a low humidity of 40% RH or less. Therefore, when calcium chloride or calcium nitrate is formed on the surface of the insulating material, the surface of the insulating material may condense, leakage current will flow, insulation may be destroyed, and the equipment may be shut down even under low humidity conditions. it is conceivable that.

Japanese Patent No. 4112430

Standardization and quality control Vol. 58 No. 8 Pages 68-74

  An embodiment of the present invention aims to provide a deterioration diagnosis device, a deterioration diagnosis method, and a deterioration diagnosis program for diagnosing a deterioration state of an insulating material.

  According to the first embodiment, the deterioration diagnosis apparatus includes an estimation unit and a diagnosis unit. The estimation means is based on an actual measurement value of an evaluation item set in advance for the insulating material, a model of a device including the insulating material, and unit space information corresponding to the model, and an insulation resistance of the insulating material. Estimate the value. The diagnosis means obtains the remaining life of the insulating material based on the insulation resistance value estimated by the estimation means.

  According to the second embodiment, the deterioration diagnosis method is a method in which the processing apparatus has an actual measurement value of an evaluation item set in advance for an insulating material, a model of a device including the insulating material, and a unit corresponding to the model. Estimating the insulation resistance value of the insulating material based on the spatial information, and determining the remaining life of the insulating material based on the estimated insulation resistance value.

  According to the third embodiment, the deterioration diagnosis program is stored in the computer in the measured value of the evaluation items set in advance for the insulating material, the model of the device including the insulating material, and the storage device. Based on the unit space information corresponding to the model, the insulation resistance value of the insulating material is estimated, and the estimation result is stored in the storage device. In addition, the deterioration diagnosis program causes the computer to obtain the remaining life of the insulating material based on the estimation result stored in the storage device and to store the remaining life in the storage device.

The block diagram which shows an example of a structure of the deterioration diagnostic apparatus which concerns on 1st Embodiment. The graph which shows an example of the relationship between the insulation resistance value of an insulating material, and temperature and humidity conditions at the time of measurement. The graph which shows an example of the diagnostic content of the degradation diagnostic apparatus which concerns on 1st Embodiment. The flowchart which shows the 1st example of operation | movement of the deterioration diagnostic apparatus which concerns on 1st Embodiment. The flowchart which shows the 2nd example of operation | movement of the deterioration diagnostic apparatus which concerns on 1st Embodiment. 9 is a flowchart showing a third example of the operation of the deterioration diagnosis apparatus according to the first embodiment. The factor effect figure which shows an example of the characteristic factor for producing | generating the estimation formula of T method. The graph which shows an example of correlation with the measured insulation resistance value and the insulation resistance value estimated by the T method. The table | surface which shows an example of the comparison of the insulation resistance value estimated based on the measured insulation resistance value of the insulation material, the insulation resistance value estimated based on the measured evaluation item value, and the evaluation item value of bad environment. The table which shows an example of the constant of an estimation formula, and switching of a coefficient. The graph which shows an example of the function L _i (X _i ) included in a part of the estimation formula. The block diagram which shows an example of a structure of the deterioration diagnostic apparatus in consideration of the model of an apparatus provided with an insulating material.

  Embodiments of the present invention will be described below with reference to the drawings. In the following description, substantially the same or substantially the same functions and components are denoted by the same reference numerals, and will be described as necessary.

(First embodiment)
In the present embodiment, a deterioration diagnosis apparatus for estimating and diagnosing the deterioration state of insulating materials used in various types of power equipment or power equipment such as power receiving equipment, substation equipment, and switch gear will be described. In this embodiment, the remaining life of an insulating material is calculated | required as an example of a diagnosis.

  In this embodiment, in addition to the deterioration of the insulating material over time, the deterioration diagnosis is performed including the deterioration of the insulating material affected by the installation environment of the insulating material.

  FIG. 1 is a block diagram showing an example of the configuration of the deterioration diagnosis apparatus according to the present embodiment.

  The degradation diagnosis apparatus 1 includes an input unit 2, a storage device 3, estimation units 4 and 5, a diagnosis unit 5, estimation units 6 to 8, and an output unit 9.

  In the present embodiment, for example, an insulating material such as a polyester resin, an epoxy resin, or a phenol resin is a diagnosis target. In the present embodiment, as the insulation resistance value of the insulating material, for example, the surface insulation resistance value and the log insulation resistance value of the insulating material are used for deterioration diagnosis.

  FIG. 2 is a graph showing an example of the relationship between the insulation resistance value of the insulating material and the temperature / humidity conditions at the time of measurement. In the example of FIG. 2, 50% RH, 60% RH, and 70% with respect to new insulating materials of 20 ° C., 40 ° C., and 60 ° C. and deteriorated insulating materials of 20 ° C., 40 ° C., and 60 ° C., respectively. Insulation resistance values (Ω) at humidity of% RH, 80% RH, and 95% RH are shown.

  As shown in FIG. 2, in the case of a new insulating material, the insulation resistance value is almost constant regardless of temperature and humidity. In the case of a deteriorated insulating material, the insulation resistance value tends to decrease as the temperature during measurement increases. Further, the insulation resistance value of the insulating material tends to decrease as the humidity at the time of measurement increases. Even with the same insulating material, a measurement error of several digits occurs if the humidity is different.

  Thus, the insulation resistance value of the insulating material is affected by external environmental noise such as temperature and humidity.

  Therefore, the degradation diagnosis apparatus 1 according to the present embodiment has an evaluation item (material) that has a high correlation or an inverse correlation with the insulation resistance value in order to estimate the insulation resistance value with high accuracy even under the influence of noise from the external environment. Value).

  As described above, the insulation resistance value of the insulation resistance that is used for a long time in a high temperature and high humidity environment such as during a rainy season may rapidly decrease.

  Therefore, the degradation diagnosis apparatus 1 according to the present embodiment estimates an insulation resistance value in an assumed adverse environment in addition to the insulation resistance value in the actual environment.

  Thereby, the degradation diagnosis apparatus 1 according to the present embodiment estimates how much the insulation resistance value decreases in an environment that adversely affects the maintenance of the insulation resistance value, and predicts the remaining life of the insulating material in a bad environment. be able to. For example, the user 1U such as a maintenance person can replace the parts or the equipment before the equipment or the equipment is stopped based on the decrease in the insulation resistance value.

  Below, each component of the deterioration diagnostic apparatus 1 shown in FIG. 1 is demonstrated.

  In the first operation, the degradation diagnosis apparatus 1 according to the present embodiment compares the insulation resistance value, which is an actually measured value, with the insulation resistance value estimated based on the actually measured evaluation item value, and increases the accuracy of the estimation method. Diagnose.

  In the second operation, the deterioration diagnosis apparatus 1 diagnoses the remaining life of the insulating material based on the insulation resistance value estimated based on the actually measured evaluation item value.

  Further, in the third operation, the deterioration diagnosis apparatus 1 estimates an insulation resistance value based on an evaluation item value of a bad environment where deterioration is assumed to progress, and diagnoses the remaining life of the insulating material in the bad environment.

  Whether or not the input unit 2 is within a range in which the estimation accuracy of the estimation method used in the deterioration diagnosis device 1 is allowed from the user 1U or various external devices (for example, sensors, terminals, other systems, etc.) 1A. An allowable range 10 for determining whether or not the insulation material is not normal, a threshold value 11 indicating an insulation resistance value, a parameter 12 including a coefficient and a constant of an estimation formula of the insulation resistance value, and an insulation of actually measured insulation material Measured insulation resistance data 13 including the resistance value and its time information, Measured evaluation item data 14 including the measured evaluation item value and its measurement time information, and an evaluation item value of the adverse environment and corresponding time information Various information such as the evaluation item data 15 for bad environment is input, and the input information is stored in the storage device 3. The input unit 2 may receive various information via a network. The permissible range 10 and the threshold value 11 can be obtained through experiments or the like.

  In the following, the time information will be described using a usage period, but other time information such as date and time may be used.

  The storage device 3 stores various types of information received by the input unit 2 and various types of information obtained by the estimation unit 4, the diagnosis unit 5, the estimation unit 6, and the diagnosis unit 7.

  The estimation unit 4 estimates the insulation resistance value in the actual measurement environment using multivariate analysis (for example, T method) based on the parameter 12 and the actual evaluation item data 14 stored in the storage device 3.

  In the following, a case where the T method is used as an estimation method will be described as an example, but another estimation method may be used.

  The estimation unit 4 stores an estimation result 16 including the insulation resistance value estimated based on the actually measured evaluation item value and the corresponding usage period in the storage device 3. For example, the parameter 12 includes polynomial coefficients and constants used in the T method. The evaluation item value has a high correlation or inverse correlation with the insulation resistance value of the insulating material.

  The diagnosis unit 6 diagnoses whether or not the T method used in the deterioration diagnosis device 1 is appropriate based on the allowable range 10, the actually measured insulation resistance data 13, and the estimation result 16 stored in the storage device 3. To do. For example, the diagnosis unit 6 compares the measured insulation resistance value with the insulation resistance value estimated based on the actually measured evaluation item value, and if the difference exceeds the allowable range 10, the parameter 12 and the T method Diagnose that at least one of is not appropriate.

  Then, the diagnosis unit 6 stores a diagnosis result 17 indicating whether or not the estimation method is appropriate in the storage device 3.

  The diagnosis unit 7 obtains an estimated curve indicating a change in the insulation resistance value corresponding to the use period based on the insulation resistance value estimated based on the actually measured evaluation item value and the corresponding use period. For example, the diagnosis unit 7 obtains the amount of change in the insulation resistance value based on the insulation resistance value when not in use, the insulation resistance value estimated based on the actually measured evaluation item value, and the usage period. In addition, the diagnosis unit 7 does not use the insulation resistance value when not in use, and based on the plurality of insulation resistance values estimated based on the actually measured evaluation item values in different use periods and the respective use periods, An estimated curve may be obtained.

  Further, the diagnosis unit 7 obtains a time point at which the estimated curve becomes equal to or less than the threshold value 11 based on the estimated curve and the threshold value 11, and obtains the remaining life (remaining effective period) of the insulating material in the actually measured environment.

  Then, the diagnosis unit 7 stores the diagnosis result 18 including the remaining life in the measured environment of the insulating material in the storage device 3.

  The estimation unit 5 estimates the insulation resistance value in the adverse environment using the multivariate analysis similar to that of the estimation unit 4 based on the parameter 12 and the evaluation item value 15 of the adverse environment stored in the storage device 3. And the estimation part 5 memorize | stores the estimation result 19 containing the use period which opposes the insulation resistance value estimated based on the evaluation item value of bad environment in the memory | storage device 3. FIG.

  The diagnosis unit 8 estimates the bad environment indicating a change in the insulation resistance value corresponding to the use period in the bad environment based on the insulation resistance value estimated based on the evaluation item value of the bad environment and the corresponding use period. Find a curve.

  Further, the diagnosis unit 8 obtains a point in time when the estimation curve of the adverse environment becomes equal to or less than the threshold value 11 based on the estimation curve of the adverse environment and the threshold value 11, and the remaining life in the adverse environment of the insulating material (the remaining (Effective period).

  Then, the diagnosis unit 8 stores the diagnosis result 20 including the remaining life in the adverse environment of the insulating material in the storage device 3.

  The output unit 9 outputs various types of information such as diagnostic results 17, 18, and 20 stored in the storage device 3 to the user 1U or various external devices 1A. For example, the output unit 9 may display or transmit the diagnostic results 17, 18, and 20.

  FIG. 3 is a graph showing an example of diagnosis contents of the deterioration diagnosis apparatus 1 according to the present embodiment.

  In FIG. 3, the horizontal axis represents the period of use of the insulating material that is the object of diagnosis. The vertical axis represents the log insulation resistance value of the insulating material.

  For example, when the difference between the insulation resistance value estimated based on the evaluation item value measured by the T method and the measured insulation resistance value exceeds the allowable range 10, the accuracy of the estimation method by the T method is low. Diagnosed.

  The insulation resistance value of the insulating material decreases as the usage period becomes longer. For example, based on the insulation resistance value of a new insulation material (may be the estimated insulation resistance value in another actual measurement environment), the insulation resistance value in the actual measurement environment estimated based on the actual evaluation item value, and the period of use From the estimated curve obtained in this way, the time point at which the insulation resistance value becomes the threshold value 11 or less is estimated. Then, the remaining life of the insulating material in the measured environment is determined from the difference between the time when the insulation resistance value becomes the threshold value 11 or less and the current time.

  In addition, the insulation resistance value of a new insulation material (may be an estimated insulation resistance value in another adverse environment), the insulation resistance value in an adverse environment estimated based on the evaluation item value of the adverse environment, and the period of use From the estimated curve obtained based on this, the time point at which the insulation resistance value in the adverse environment becomes the threshold value 11 or less is estimated. And the remaining life in the bad environment of an insulating material is calculated | required from the difference between the time when the insulation resistance value in bad environment becomes the threshold value 11 or less, and the present time.

  FIG. 4 is a flowchart showing a first example of the operation of the deterioration diagnosis apparatus 1 according to the present embodiment.

  In step S1, the estimation unit 4 of the degradation diagnosis apparatus 1 performs analysis by the T method based on the evaluation item data 14 including, for example, the parameter 12 used in the T method, the actually evaluated evaluation item value, and the usage period. An estimation result 16 including the insulation resistance value estimated based on the evaluation item value and the trial period is obtained.

  In step S <b> 2, the diagnosis unit 6 of the deterioration diagnosis apparatus 1 performs the measured insulation resistance data 13 including the measured insulation resistance value and the usage period, and the insulation resistance value and the usage period estimated based on the measured evaluation item value. The difference between the actually measured insulation resistance value and the estimated insulation resistance value based on the actually measured evaluation item value is obtained.

  In step S <b> 3, the diagnosis unit 6 determines whether this difference is larger than the allowable range 10.

  When the difference is larger than the allowable range 10, in step S4A, the diagnosis unit 6 generates a diagnosis result 17 including a warning regarding the accuracy of at least one of the estimation method and the parameter 11, and stores the diagnosis result 17 in the storage device 3.

  When the difference is equal to or smaller than the allowable range 10, in step S4B, the diagnosis unit 6 generates a diagnosis result 17 including information indicating that the estimation method and the parameter 11 are normal (estimation accuracy is sufficient), and the storage device 3 is stored.

  In step S <b> 5, the output unit 9 outputs the diagnosis result 17 stored in the storage device 3.

  FIG. 5 is a flowchart showing a second example of the operation of the deterioration diagnosis apparatus 1 according to this embodiment.

  Step T1 is the same as step S1 described above, and the estimation unit 4 of the deterioration diagnosis apparatus 1 performs analysis based on the parameter 12 and the actually measured evaluation item data 14, and the insulation estimated based on the actually measured evaluation item value. An estimation result 16 including the resistance value and the use period is generated.

  In step T2, the diagnosis unit 7 of the deterioration diagnosis apparatus 1 determines the insulation resistance value of the new insulation material (other insulation resistance values and their usage periods may be used) and the insulation resistance value estimated based on the actually evaluated evaluation item values. The diagnostic result 17 including the remaining life of the insulating material in the actual measurement environment is generated based on the usage period and the threshold value 11, and the diagnostic result 18 is stored in the storage device 3. The remaining life in the actual measurement environment is, for example, an estimated curve generated from a new insulation resistance value, a period of use up to the present time, and an insulation resistance value estimated by the T method. It is calculated by subtracting the period of use from the determined time point to the present time.

  In step T <b> 3, the output unit 9 outputs the diagnosis result 18 stored in the storage device 3.

  FIG. 6 is a flowchart showing a third example of the operation of the deterioration diagnosis apparatus 1 according to this embodiment.

  In step U1, the estimation unit 5 of the degradation diagnosis apparatus 1 performs analysis based on the parameter 12 and the evaluation item data 15 of the bad environment, and the insulation resistance value estimated based on the evaluation item value of the bad environment, the use period, and the like. The estimation result 19 including is generated. The evaluation item data 15 for the bad environment includes, for example, measuring temperature and humidity over an arbitrary period (for example, annually) for each place where equipment / equipment including an insulating material is installed, and out of the measured temperature and humidity The highest temperature and humidity may be included.

  In step U2, the diagnosis unit 8 of the deterioration diagnosis apparatus 1 estimates based on the insulation resistance value of the new insulation material (the insulation resistance value in another adverse environment and its use period) and the evaluation item value of the adverse environment. Based on the insulation resistance value, the period of use thereof, and the threshold value 11, a diagnostic result 20 including the remaining life in an adverse environment of the insulating material is generated, and the diagnostic result 20 is stored in the storage device 3. The remaining life in a bad environment is, for example, by generating an estimated curve in a bad environment from a new insulation resistance value, the period of use up to the present time, and the insulation resistance value in a bad environment estimated by the T method. Is calculated by subtracting the period of use from the determined time point to the current time point.

  In step U <b> 3, the output unit 9 outputs the diagnosis result 20 stored in the storage device 3.

  Even if the insulation material is diagnosed as having good insulation under a normal environment, the insulation resistance value may suddenly decrease in an environment that is bad for the insulation material, such as during a rainy season. However, by estimating the remaining life in a bad environment as in the present embodiment, the user can grasp the tendency for the insulation to decrease in the bad environment.

  FIG. 7 is a factor effect diagram showing an example of a characteristic factor for generating an estimation formula of the T method.

  In FIG. 7, the vertical axis (Y) represents the log insulation resistance value, and the horizontal axis (X) represents each evaluation item. FIG. 7 represents how the value of Y changes when the value of X changes in each evaluation item. The greater the rate of change of Y with respect to X in FIG. 7 (the greater the slope), the greater the effect on Y.

  The T method according to the present embodiment uses a forward / reverse orthogonal table in order to improve the reliability of item selection.

  FIG. 8 is a graph showing an example of the correlation between the actually measured insulation resistance value (true value) and the insulation resistance value (estimated value) estimated by the T method.

  In FIG. 8, the horizontal axis represents the actually measured insulation resistance value, and the vertical axis represents the estimated insulation resistance value (estimated value). The closer the measured insulation resistance value is to the estimated insulation resistance value, the higher the estimation accuracy.

  FIG. 9 is a comparison of the measured log insulation resistance value of the insulating material, the log insulation resistance value estimated in the actual measurement environment (using the actually measured evaluation item value), and the log insulation resistance value estimated in the adverse environment. It is a table which shows an example.

  In FIG. 9, for each row, the difference between the measured log insulation resistance value and the log insulation resistance value estimated in the actual measurement environment is preferably within the allowable range 10.

  The longer the period of use, the smaller the log insulation resistance value in a bad environment than the measured log insulation resistance value and the log insulation resistance value estimated in the actual measurement environment.

  In the present embodiment, it is assumed that the evaluation item is an item that can be measured by the user 1U such as a measurer at a facility installation place or by taking back a sample. Furthermore, the evaluation items are items that can be measured without destroying and damaging the equipment and the insulating material. The evaluation item is preferably an item that can be measured during the operation of the facility. The evaluation item may be an item that can be measured at the same time when the facility is stopped, such as periodic inspection.

  For example, as evaluation items, temperature, humidity, hue (lightness L *, chromaticity a *, chromaticity b *), glossiness (incidence angles 20 °, 60 °, 85 °), reflectance (red light reflectance) , Blue light reflectance, green light reflectance), contact angle, surface roughness, fouling degree, ion content (fluorine ion, chlorine ion, nitrite ion, nitrate ion, sulfate ion, phosphate ion, sodium ion, ammonium) Ions, potassium ions, magnesium ions, calcium ions) and the like. Among these, in particular, temperature, humidity, hue, glossiness, fouling degree, and ion content are highly correlated with the insulation resistance value of the insulating material, and are preferably used as evaluation items. The reason for this is that the insulating material becomes rough due to aging, loses its gloss (gloss), and changes color. Note that the insulation resistance value of the insulating material depends on the installation environment, but it may decrease due to adhesion and accumulation of dust and ionic substances floating in the air and accumulation of conductive substances on the surface. The amount of dust floating in the air and the amount of ionic substances may be used as evaluation items.

  In the present embodiment, the log insulation resistance value is expressed by a linear expression of a constant, an evaluation item value, and a coefficient as in the following expression (1).

Y = C + n ₁ X ₁ + n ₂ X ₂ + n ₃ X ₃ +... + N _i X _i (1)
Here, Y is a log insulation resistance value, C is a constant, X _{1 to} X _i are evaluation item values (measurement values of evaluation items), and n _{1 to} n _i are coefficients of the evaluation items.

  When the insulation resistance value of the insulating material is actually measured, a value including external environmental noise may be measured. On the other hand, when Y is calculated by the equation (1), an insulation resistance value that is not affected by noise can be obtained.

  Although it is difficult to measure the insulation resistance value during the operation of the facility, by using the equation (1), the insulation resistance value of the insulating material can be obtained and the life diagnosis can be performed even during the operation of the facility. .

  Even if it is difficult to obtain the insulation resistance value in the environment where the insulation material is actually used, it is possible to respond to the actual use environment by inputting external environment conditions such as temperature and humidity into the equation (1). The insulation resistance value to be estimated can be estimated, the life of the insulating material can be grasped, and maintenance can be performed effectively.

  In this embodiment, it is possible to estimate the insulation resistance value when the insulating material is used under the conditions of high temperature and high humidity, which is a bad environment for the insulating material.

  FIG. 10 is a table showing an example of switching of constants and coefficients of the estimation formula.

  In FIG. 10, the constants and coefficients of the condition R1 are constants and coefficients used in the high humidity region. The constants and coefficients of the condition R2 are constants and coefficients used in the low humidity region. When the humidity in the installation area of the equipment including the insulating material is equal to or higher than a certain value, the log insulation resistance value is estimated using the constant and coefficient of the condition R1. When the humidity is less than a certain value, the log insulation resistance value is estimated using the constant and coefficient of the condition R2.

  Depending on the type of insulating material, the change in the log insulation resistance value may differ greatly between a high humidity environment and a low humidity environment. In such a case, as shown in FIG. 10, the accuracy of estimating the log insulation resistance value can be improved by switching the constant and coefficient of the equation (1) according to the humidity.

  In FIG. 10, the case where the constants and coefficients of the formula (1) are switched between the high humidity region and the low humidity region is described as an example. However, the constants and the coefficients of the formula (1) are switched according to other criteria. It is good.

For example, based on the degree of pollution, the constants and coefficients of the equation (1) may be set separately for the high pollution area and the low pollution area. For example, the high pollution area is a place where the pollution classification is from super heavy pollution to light pollution, or a pollution degree greater than 0.01 (mg / cm ² ). For example, the low pollution area is a place where the pollution classification is clean, or a place where the pollution degree is 0.01 (mg / cm ² ) or less. When the surface of the insulating material is fouled and the conductive material is accumulated, the insulating property of the insulating material is lost, and the insulation resistance value tends to rapidly decrease. Therefore, the estimation accuracy is improved by classifying the surface of the insulating material into a clean state and a contaminated state, and switching the constant and coefficient of the equation (1) between the high contamination region and the low contamination region. Can do.

  In the present embodiment, a part of the expression (1) (for example, at least one of a coefficient corresponding to at least one evaluation item and an evaluation item value) may be functionalized.

  A case where at least one evaluation item value of the estimation equation (1) is expressed by a function is shown in Equation (2).

Y = C + n ₁ X ₁ + n ₂ X ₂ + n ₃ X ₃ +... + N _i-1 L _i-1 (X _i-1 ) + n _{i Li} (X _i ) (2)
In this equation (2), L (X _i-1 ) and L (X _i ) are function values obtained based on the evaluation item values.

  For example, in FIG. 10 described above, the evaluation item values X6 ′ to X9 ′ may be calculated values calculated based on actual measurement values.

FIG. 11 is a graph illustrating an example of the function L _i (X _i ) included in a part of the estimation formula.

  For example, when the evaluation item is an ion content rate or a contamination degree, it is assumed that at least one of a coefficient and an evaluation item value corresponding to the evaluation item is calculated using a function.

  In this way, for a specific evaluation item, at least one of the evaluation item value and the coefficient is converted into a function, and the insulation resistance value is estimated by the estimation formula using the value obtained from the function, thereby actually measuring the evaluation item. The estimation accuracy can be improved as compared with the case where the value is directly substituted into the equation (1).

  However, the functionalization of the coefficient or the evaluation item value is used when it is confirmed that the insulation resistance value can be explained by the function of the evaluation item.

  In the present embodiment, as the insulating material used in the power device, for example, various matrix resins and fillers are used. For example, color or gloss has characteristics for each insulating material. When the insulating material is used as a component of the device for a long period of time, each of the insulating materials exhibits a deterioration state specific to the material. Evaluation item values (characteristic values) are different for each insulating material. Therefore, in the present embodiment, the estimation formula (1), the estimation formula (2), the coefficient, and the constant may be set for each type of insulating material.

  FIG. 12 is a block diagram illustrating an example of the configuration of a deterioration diagnosis apparatus that takes into account the model of a device including an insulating material.

  In FIG. 12, the unit space information 21A, 21B for each device type A, B is information relating to the place where the device is installed.

  Data 22 is a set of measurement data and analysis data for each measurement.

  The storage device 3 stores various types of information necessary for deterioration diagnosis, but is omitted in FIG.

  The input tool 22 corresponds to the input unit 2. The form output tool 23 corresponds to the estimation units 4 and 5, the diagnosis units 6 to 8, and the output unit 9. The form 24 corresponds to the diagnosis results 17, 18, and 20.

  The user 1U selects a model of a device to be diagnosed and inputs data (various measurement data and analysis data) 22.

  The storage device 3 stores the input data 22.

  The form output tool 23 generates a diagnosis result including the remaining life based on the unit type space information of the selected type, the data 22 stored in the storage device 3 and other various information, and outputs it as a form 24. .

  In the present embodiment described above, by predicting the remaining life of the insulating material, it is possible to safely operate the power equipment and perform appropriate maintenance.

  In the present embodiment, the insulation resistance value of the insulating material can be estimated with high accuracy.

  In the present embodiment, the deterioration diagnosis device 1 is a computer, and the estimation units 4 and 5 and the diagnosis units 6 to 8 may be realized by a computer processor executing a program. For example, the input unit 2 may be a touch panel, a keyboard, or a pointing device, and the output unit may be a display.

(Second Embodiment)
In the present embodiment, the T method described in the first embodiment will be further described with reference to FIG.

  Although there are several types of T methods, the T method according to the first embodiment is a T method when the unit space is in the center.

  In the T method according to the first embodiment, a forward / reverse orthogonal table is used to improve the reliability of item selection.

  FIG. 7 is an example of a T-method factor effect diagram generated based on such calculation. The numbers on the horizontal axis in FIG. 7 are the numbers of the respective items. FIG. 7 shows what happens to the estimated value on the vertical axis for each item when level 1 is set low, level 2 is set medium, and level 3 is set high. Items 2, 3, 9, 11, 14, 16, and 20 indicate that the estimated value decreases as the value increases. Items 4 to 8 indicate that the estimated value increases as the value increases. It can be understood that the items 12, 15, and 19 hardly affect the estimated value.

  In the present embodiment, a characteristic obtained by converting a feature value may be input to the estimation formula instead of a simple feature value.

  As described above, the use of a forward / reverse orthogonal table for item selection improves the reliability of item selection and enables a highly accurate estimation formula to be obtained.

  In the present embodiment, for example, based on the three-level factor effect diagram of small, medium, and large, by selecting only items that affect the estimated value beyond a certain level, an estimation formula is generated, thereby generating accuracy. It is possible to reduce the number of items that need to be measured while suppressing a decrease in the number of items.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

  DESCRIPTION OF SYMBOLS 1 ... Degradation diagnostic apparatus, 2 ... Input part, 3 ... Memory | storage device, 4, 5 ... Estimation part, 6-8 ... Diagnosis part, 9 ... Output part, 10 ... Permissible range, 11 ... Threshold value, 12 ... Parameter, 13 ... Measured insulation resistance data, 14 ... Measured evaluation item data, 15 ... Evil environment evaluation item data, 16, 19 ... Estimated results, 17, 18, 20 ... Diagnostic results

Claims (8)

An insulation resistance value of the insulating material is estimated based on an actual measurement value of an evaluation item set in advance for the insulating material, a model of a device including the insulating material, and unit space information corresponding to the model. An estimation means;
A deterioration diagnosis apparatus comprising: a diagnosis unit that obtains a remaining life of the insulating material based on the insulation resistance value estimated by the estimation unit. In the deterioration diagnostic apparatus according to claim 1,
The diagnostic means obtains an estimated curve representing a change of the insulation resistance value with respect to the use period based on the insulation resistance value estimated by the estimation means and a use period of the insulating material, and the estimated curve is A deterioration diagnosis apparatus, characterized in that a remaining life of the insulating material is obtained based on a time point when a predetermined threshold value or less is reached. In the deterioration diagnostic apparatus according to claim 1,
The estimating means estimates an insulation resistance value of the adverse environment of the insulating material based on a value of the adverse environment related to the evaluation item,
The diagnostic means obtains an estimation curve of a bad environment representing a change in the bad environment of the insulation resistance value based on the insulation resistance value of the bad environment and a usage period of the insulating material, A deterioration diagnosis apparatus characterized in that an effective period of a bad environment of the insulating material is obtained based on a time point when an estimated curve becomes equal to or less than the threshold value. In the deterioration diagnostic apparatus according to claim 1,
The diagnostic means is configured such that a difference between the actually measured insulation resistance value of the insulating material and the insulation resistance value estimated based on the actually measured value of the evaluation item by the estimating means is within a preset estimation accuracy tolerance. A deterioration diagnosis apparatus characterized in that it is determined whether the difference is outside the range, and if the difference is outside the pre-allowable range, a diagnosis result indicating that is generated. In the deterioration diagnostic apparatus according to claim 1,
A plurality of the unit space information is prepared in advance in accordance with the type of equipment provided with the insulating material. In the deterioration diagnostic apparatus according to claim 1,
At least one of hue, glossiness, reflectance, contact angle, surface roughness, fouling degree, and ion content is used as the evaluation item. Based on the measured value of the evaluation item set in advance for the insulating material, the type of the equipment including the insulating material, and the unit space information corresponding to the type, the processing device Estimating the value;
The deterioration diagnosis method comprising: the processing device obtaining a remaining life of the insulating material based on the estimated insulation resistance value. On the computer, based on the actual measurement values of the evaluation items set in advance for the insulating material, the model of the device including the insulating material, and the unit space information corresponding to the model stored in the storage device, Estimating an insulation resistance value of the insulating material, and storing the estimation result in the storage device;
A degradation diagnosis program for causing the computer to obtain a remaining life of the insulating material based on the estimation result stored in the storage device and to store the remaining life in the storage device.