JP2022125119A - Deterioration diagnostic system, deterioration diagnostic device, deterioration diagnostic method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a deterioration diagnostic system and the like, which are able to accurately estimate a resistance value by frequently measuring a factor that may significantly affect a change in an insulation resistance characteristic.

SOLUTION: A deterioration diagnostic system according to an embodiment comprises a measurement unit, an estimation formula storage unit, and a resistance value estimation unit. The measurement unit measures at least a sticking degree of an ionic contaminant of a material factor relating to an insulation material for insulation resistance used in a target apparatus or an environmental factor in a place where the insulation resistance is installed. The estimation formula storage unit stores information about an estimation formula for estimating a resistance value of the insulation resistance on the basis of the measurement result obtained by the measurement unit. The resistance value estimation unit estimates the resistance value of the insulation resistance, using the measurement result by the measurement unit and the estimation formula stored in the estimation formula storage unit.

SELECTED DRAWING: Figure 1

COPYRIGHT: (C)2022,JPO&INPIT

Description

TECHNICAL FIELD Embodiments of the present invention relate to a deterioration diagnosis system, a deterioration diagnosis device, a deterioration diagnosis method, and a program.

Electric power facilities are important facilities that support social infrastructure, and are required to operate stably for a long period of time. For stable operation, it is necessary to understand the state of deterioration of electric power equipment and to implement maintenance and renewal in a planned manner. Insulating materials used for supporting conductors or barriers in electric power equipment deteriorate over time, and their insulating properties deteriorate due to the adhesion of dust or gas floating in the installation environment. If the insulation characteristics are degraded, discharge or tracking may occur, which may lead to equipment stoppage. Therefore, the condition of the insulating material becomes a barometer for diagnosing deterioration of power equipment.

The influence of the installation environment on the deterioration of insulating materials is not limited to contamination due to adhesion of dust and gas. In environments where there are environmental factors that chemically react with the constituents of the insulating material, the insulating material may degrade at a rate that exceeds normal aging. Calcium carbonate, for example, is often used as an inorganic filler in insulating materials. When calcium carbonate reacts with chlorine-based gas, nitrogen oxide gas, etc., calcium chloride or calcium nitrate is formed on the surface of the insulating material. Even at low humidity of 40% RH (relative humidity) or less, these substances absorb water in the atmosphere and deliquesce. Leakage currents may flow across the surface. If this becomes serious, the insulation will be destroyed, and in the worst case, the equipment will be stopped.

It is possible to directly measure the insulation resistance of insulating materials used in electrical installations in the field. However, the measured value is greatly affected by the atmosphere of the place of measurement, specifically humidity. For example, in a dry environment, measured insulation resistance values are often higher than they actually are, and this can lead to overlooked deterioration of insulation materials. In addition, most electrical equipment stops due to poor insulation during periods of high temperature and humidity, such as the rainy season. Such direct measurement of the resistance value of the insulating material is not suitable for practical use.

Therefore, a method of estimating the insulation resistance value of an insulating material by numerical calculation using multivariate analysis or the like has been proposed. In other words, it is a method of measuring a plurality of items that are correlated with the insulation resistance and are not affected by the atmosphere of the measurement location, and calculating the insulation resistance value based on the values of the items. In this method, data correlated with insulation resistance is obtained for insulation materials used in the field and forcibly degraded insulation materials, and an estimation formula for insulation resistance, which is a diagnostic index, is formulated by multivariate analysis. In the insulation diagnosis, the items for which the estimation formula is formulated are measured, and the insulation resistance at any temperature and humidity is estimated from the insulation resistance estimation formula.

A deterioration diagnosis device according to the prior art estimates an insulation resistance value based on an actual measurement value of a predetermined evaluation item and an estimation formula stored in advance. Further, the deterioration diagnosis device according to the prior art judges the validity of the above estimation formula based on the estimated insulation resistance value and the actually measured value of the resistance value. Further, the conventional deterioration diagnosis device calculates the effective period of the insulating material based on the estimated insulation resistance value and the period of use of the insulating material.
Further, in the prior art, a DC voltage is applied to an insulating material to be diagnosed, and changes in insulation resistance over time are measured. Also, the contamination state of the insulating material is diagnosed based on the constant of the exponential approximation curve when the relationship between the insulation resistance and the measurement time is approximated by an exponential equation. Also, the deterioration state of the insulating material is diagnosed based on the constants of the power approximation curve when the relationship between the insulation resistance and the measurement time is approximated by a power equation.
In addition, in the conventional technology, multivariate analysis is performed based on the relationship between the change in the insulation resistance of the insulating material, which is the criterion for judging insulation deterioration, the material characteristics of the insulating material, and the atmospheric environment factor in which the insulating material is installed, and the insulation resistance An estimation formula for is created in advance. In addition, the insulation resistance of the insulating material at the maximum temperature and humidity assumed in the installation environment of the insulating material is calculated by the estimation formula. Also, based on the calculated insulation resistance of the insulating material at the maximum temperature and humidity, the time until the life threshold value is reached is determined.

In order to evaluate the influence of environmental factors on insulation properties, it is necessary to measure the contamination status of the surface (insulating material) of equipment used in the field. Specifically, we evaluate the degree of influence of contamination caused by dust, sea salt particles, and gas adhesion, as well as deliquescent substances that absorb moisture at low humidity, which are chemical reactions between these external contamination factors and the components of the insulating material. As a measurement method for that purpose, there is a method of wiping a certain area of the contaminated material on the surface of the object with wet gauze, extracting the contaminated liquid with a certain amount of pure water, measuring the conductivity, and analyzing the concentration of ions contained. Used. In implementing this measurement method, it is necessary for an inspector to actually perform sampling work from the target equipment. However, it is practically difficult for an inspector to continuously perform sampling work near the target equipment at all times.

If there are no major changes in the surrounding environment of the target equipment, regular monitoring of the contamination status can sufficiently fulfill the function of preventive maintenance. It becomes difficult to predict the decrease in insulation resistance in advance. For example, due to the effects of new construction, renovation, construction of surrounding structures, abnormal weather such as typhoons, etc., the flying condition of foreign contaminants changes, or the reaction between foreign contaminant components and insulating materials occurs and rapidly If insulation deterioration progresses, it is difficult to predict the deterioration of insulation resistance in advance.

Japanese Patent No. 5951299 Japanese Patent No. 5836904 Japanese Patent No. 5872643

A problem to be solved by the present invention is a deterioration diagnosis system, a deterioration diagnosis device, and a deterioration diagnosis method that can accurately predict a resistance value by frequently measuring factors that greatly affect changes in insulation resistance characteristics. , and to provide programs.

A deterioration diagnosis system according to an embodiment includes a measurement unit, an estimation formula storage unit, a resistance value estimation unit, an estimation formula creation unit, an analysis data storage unit for creation of an estimation formula, and an analysis data collection unit. The measurement unit measures at least one of the material factor related to the insulation material of the insulation resistance used in the target device, and the amount of ionic contaminants adhered among the environmental factors at the location where the insulation resistance is installed. do. The estimation formula storage unit stores information on an estimation formula for estimating the resistance value of the insulation resistance based on the measurement result by the measurement unit. The resistance value estimating section estimates the resistance value of the insulation resistance using the measurement result obtained by the measuring section and the estimation formula stored in the estimation formula storage section. The estimation formula is a formula for estimating the resistance value based also on temperature and humidity. The estimation formula creation unit performs the estimation formula by multivariate analysis using the Taguchi method or the Taguchi-Schmidt method based on a set of the measured value of the measurement item measured by the measurement unit and the measured value of the resistance value of the insulation resistance. to create The analysis data storage unit for creating an estimation formula is analysis data from which the estimation formula creation unit obtains the estimation formula, and includes a set of the measured value of the measurement item and the measured value of the resistance value. memorize The analysis data collection unit collects the analysis data measured by the measurement unit and writes the analysis data into the estimation formula generation analysis data storage unit. The estimation formula creation unit performs analysis including the analysis data collected by the analysis data collection unit when creating an estimation formula with reference to the analysis data storage unit for creating the estimation formula, thereby obtaining a resistance value Learn about the estimation formula for

1 is a block diagram showing a schematic functional configuration of a deterioration diagnosis device according to a first embodiment; FIG. FIG. 2 is a schematic diagram showing a first arrangement example when providing a deterioration diagnosis device near a diagnosis target device in the first embodiment; FIG. 5 is a schematic diagram showing a second arrangement example when providing a deterioration diagnosis device near a diagnosis target device in the first embodiment; A cross-sectional view showing a sensor, which is one configuration example of the environmental factor measurement unit of the first embodiment. A plan view showing a sensor, which is one configuration example of the environmental factor measurement unit of the first embodiment. FIG. 4 is a schematic diagram showing a sensor, which is an example of an environmental factor measurement unit configured using the crystal oscillator method of the first embodiment; Schematic diagram showing a configuration example of an ion component analyzer for analyzing and measuring ion components in the first embodiment. FIG. 5 is a block diagram showing a schematic functional configuration of a degradation diagnosis system according to a second embodiment; FIG. The block diagram which shows the schematic functional structure of the degradation diagnostic system by 3rd Embodiment.

A deterioration diagnosis system, a deterioration diagnosis device, a deterioration diagnosis method, and a program according to embodiments will be described below with reference to the drawings.

(First embodiment)
A deterioration diagnosis apparatus (also referred to as a deterioration diagnosis system) according to this embodiment measures material factors and environmental factors, and estimates a resistance value based on these measured values. The material factor is a factor related to insulation resistance materials in electrical equipment and the like. Environmental factors are factors related to the environment in which electrical equipment and the like are installed (in particular, the environment to which insulating materials are exposed). The deterioration diagnosis device according to this embodiment is configured to automatically and continuously measure these material factors and environmental factors.

In this embodiment, among the environmental factors, attention is paid to ionic pollutant components in the atmosphere. In other words, the degradation diagnosis device continuously measures the amount of adhered ionic fouling components, etc., so that, for example, even if the influence of external environmental factors suddenly changes, before the characteristic deterioration of the absolute resistance actually occurs. Detect the signs. In addition, since the deterioration diagnosis device operates automatically, there is no need to dispatch an inspector to the site periodically, and labor can be saved.

FIG. 1 is a block diagram showing a schematic functional configuration of a deterioration diagnosis device according to this embodiment. As illustrated, the deterioration diagnosis device 1 includes a measurement unit 2, a resistance value estimation unit 3, a validity determination unit 4, a diagnosis unit 5, a diagnosis result display unit 6, an estimation formula storage unit 7, a model It includes an alternative material name storage unit 8 , an estimation formula creation analysis data storage unit 11 , and an estimation formula creation unit 12 . The measurement unit 2 also has a material factor measurement unit 21 and an environmental factor measurement unit 22 .
Each of these functional units is implemented using electronic circuits, for example. In addition, each functional unit may be internally provided with storage means such as a semiconductor memory or a magnetic hard disk device, if necessary. Also, each function may be realized by a computer and software.

The measurement unit 2 measures various factors related to the deterioration of the insulation resistance (diagnostic object) used in the target equipment (electrical products and electrical equipment). The measuring unit 2 passes data of the measurement result to the resistance value estimating unit 3 . Specifically, it is as follows.
A material factor measuring unit 21 in the measuring unit 2 measures items related to material deterioration of the insulating material.
Items to be measured by the material factor measuring unit 21 are, for example, the color of the surface of the insulation resistance (for example, expressed in a color space of L*, a*, b*; it may be a color image), and blue reflection. index, red reflectance, glossiness (when incident angle is 20 degrees), glossiness (when incident angle is 60 degrees), glossiness (when incident angle is 85 degrees), surface roughness, wettability (contact angle), It is a spectral reflectance spectrum. The properties measured by these items are properties that change as the resistive material ages.
An environmental factor measurement unit 22 in the measurement unit 2 measures items related to the environment surrounding the insulation resistance. The items measured by the environmental factor measurement unit 22 are, for example, the amount of ionic substances (adhesion amount, etc.), the temperature and humidity in the installation environment, and the like. Here, specific examples of ionic substances are chloride ions, nitrate ions, sulfate ions, sodium ions, ammonium ions, and the like.

At least one of the material factor measuring section 21 and the environmental factor measuring section 22 may be configured to perform automatic and continuous measurement. As a result, even if there is a drop in insulation resistance due to a sudden change in circumstances (environment, etc.), it is possible to detect the sign with high accuracy. When material factors and environmental factors are compared, environmental factors are more likely to cause changes in resistance characteristics due to sudden changes in conditions. In other words, continuous measurement of environmental factors makes it possible to more effectively predict changes in resistance characteristics due to sudden changes in conditions. However, continuous measurement itself is also effective for material factors.

In other words, the measurement unit 2 measures at least one of the material factors related to the insulating material used in the target device and the amount of ionic contaminants attached among the environmental factors at the location where the insulation resistor is installed. .

The resistance value estimating unit 3 receives measurement result data from the measuring unit 2 . The resistance value estimator 3 also associates the model identification information of the device to be diagnosed with the measurement result data. The model identification information may be received from the measurement unit 2, or may be stored as preset data or the like in the resistance value estimation unit 3. FIG. Then, the resistance value estimator 3 performs calculations for estimating the resistance value of the insulation resistance based on the measurement result data.

Specifically, the resistance value estimator 3 performs estimation according to the following procedure. First, the resistance value estimator 3 identifies the model and manufacturing date of the target device. Then, the resistance value estimating unit 3 reads the material name of the insulating material corresponding to the combination of the model and the manufacturing date from the model-specific material name storage unit 8 . This identifies the insulating material used in the target device. Next, the resistance value estimating unit 3 reads out the resistance value estimating formula for the specified insulating material from the estimating formula storage unit 7 . Next, the resistance value estimation unit 3 applies the measured value data received from the measurement unit 2 to the estimation formula read from the estimation formula storage unit 7 . Then, the resistance value estimator 3 calculates the resistance value (estimated value) of the insulation resistance of the target device by calculating the estimation formula. That is, the resistance value estimating unit 3 calls the insulation resistance estimation formula of the insulating material specified by referring to the model-specific material name storage unit 8 from the estimation formula storage unit 7, and uses this estimation formula to calculate the insulation resistance value of the insulating material. presume.

That is, the resistance value estimator 3 estimates the resistance value of the insulation resistance using the measurement result of the measurement unit 2 and the estimation formula stored in the estimation formula storage unit 7 .

The validity determination unit 4 determines the validity of the insulation resistance value estimated by the resistance value estimation unit 3 . The validity determination unit 4 determines the validity of the estimated insulation resistance value, for example, based on comparison with a predetermined upper limit value for the resistance value. Alternatively, the validity determination unit 4 may determine the validity of the estimated insulation resistance value, for example, based on a comparison with the measured value of the insulation resistance value.
That is, the validity determination unit 4 can determine the validity of the estimation formula by comparing the resistance value estimated by the resistance value estimation unit 3 and the actually measured resistance value of the insulation resistance.

Based on the insulation resistance value estimated by the resistance value estimating unit 3 and the usage period of the insulating material of the target device, the diagnosis unit 5 calculates the effective period of the insulating material used in the target device.
Therefore, the diagnostic unit 5 obtains, for example, an estimated curve representing temporal changes in the relationship between the period of use and the insulation resistance value, and the insulating material is effective until the estimated curve becomes equal to or less than a preset threshold value. and calculate the validity period. A diagnosis result obtained by the processing of the diagnosis unit 5 is passed to the diagnosis result display unit 6 .
That is, the diagnostic unit 5 determines the relationship between the period of use and the resistance value based on the resistance value estimated using the estimation formula assuming the predetermined temperature and humidity assumed in the environment in which the target device is installed. Find an estimated curve that represents the change in Thereby, the diagnostic unit 5 estimates the time (effective period) until the resistance value of the insulation resistance falls below a predetermined threshold value.
As an example, when the target equipment was installed on May 30, 1993 and the diagnosis by the deterioration diagnosis device 1 was performed on March 15, 2018, the estimated curve becomes equal to or less than the threshold. is July 30, 2029. At this time, the diagnostic unit 5 outputs the date "July 30, 2029" as the validity period. Further, the diagnosis unit 5 may output data of a graph of an estimated curve (a time series of pairs of dates and insulation resistance values (estimated values)) as appropriate.
The diagnosis result display section 6 displays the diagnosis result passed from the diagnosis section 5 . As a result, the user of the deterioration diagnosis device 1 can know the estimated value of the effective period of the resistance used in the target equipment.

The estimation formula storage unit 7 stores an estimation formula for each insulating material. The estimation formula stored in the estimation formula storage unit 7 covers a plurality of deterioration modes, and is created in advance by the T method based on the analysis data. These estimation formulas are generalized to the formula (1) below.
_R = f ( _m , d1, d2, ..., dN) ( ₁ )
In equation (1), R is the estimated resistance value and f() is a predetermined function to output the estimated resistance value. Also, m is a value (for example, an integer value) that indicates the type (substance) of the insulating material. Also, _{d 1} , d ₂ , . These parameters include data on the shape and size (eg, cross-sectional area, length, etc.) of the insulating material. These parameters also include measurement result data measured by the measurement unit 2 .
It should be noted that the more the number of deterioration modes is covered and the more the estimation formula is created, the higher the accuracy of the estimated resistance value, and the less misdiagnosis.

The estimation formula storage unit 7 stores this function f( ). Specifically, the estimation formula storage unit 7 may store, for example, a formula representing the function f( ) as data in the form of a syntax tree. The estimation formula storage unit 7 may also store, for example, a computer program module (a source program, an executable program, or the like) that implements the function f(). Further, instead of storing the function f( ), the estimation formula storage unit 7 may store a function f _m ( ) defined individually for each type m of insulating material (for example, m=1, 2 , …). The function f _m ( ) is represented by Equation (2) below.
_{R = fm} (d1,d2,...,dN) ( ₂ )

In other words, the estimation formula storage unit 7 stores information about the estimation formula for estimating the resistance value of the insulation resistance based on the measurement result by the measurement unit 2 .

The model-by-model material name storage unit 8 stores the model, the date of manufacture, and the type of insulating material of the device to be diagnosed in association with each other. That is, by specifying the model and manufacturing date of the target device and referring to the model-specific material name storage unit 8, the type of insulating material used can be specified.

The estimation formula creation analysis data storage unit 11 stores analysis data used to create the estimation formula. The data stored in the estimation formula generation analysis data storage unit 11 is a set of pairs of values of m, _{d 1} , d ₂ , .
The estimation formula creation unit 12 performs multivariate analysis by the T method (Taguchi method) based on the analysis data stored in the estimation formula creation analysis data storage unit 11 to obtain an estimation formula. The estimation formula obtained by the estimation formula generating unit 12 is represented by the above formula (1) or formula (2). Note that the estimation formula creating unit 12 may use the MT method (Mahalanobis-Taguchi method) instead of the T method. Note that the T method and the MT method themselves are existing techniques.
In other words, the estimation formula creation unit 12 estimates by multivariate analysis using the Taguchi method or the Taguchi-Schmidt method based on a set of the measured value of the measurement item measured by the measurement unit 2 and the measured value of the resistance value of the insulation resistance. Create an expression in advance.

The deterioration diagnosis device 1 may be configured without the estimation formula creation analysis data storage unit 11 and the estimation formula creation unit 12 . Even in this case, the estimation formula estimated by the estimation formula creating unit 12 of the device other than the deterioration diagnostic device 1 is stored in the estimation formula storage unit 7 in advance. Therefore, the resistance value estimator 3 can estimate the resistance value using the estimation formula.

FIG. 2 is a schematic diagram showing an arrangement example (first arrangement example) when the deterioration diagnosis device according to the present embodiment is provided in the vicinity of the equipment to be diagnosed. As illustrated, in this example, target devices 312 and 313 are installed inside a housing 311 . Target devices 312 and 313 are electrical devices that use high voltage and are internally provided with insulating material for insulation. The housing 311 has an intake port 316 and an exhaust port 317 . For example, a fan or the like (not shown) is provided in or near the housing 311 at a predetermined location, so that the air outside the housing 311 flows into the housing 311 through the intake port 316 . Similarly, the air inside the housing 311 flows out of the housing 311 through the exhaust port 317 . The thick arrows shown at the positions of the intake port 316 and the exhaust port 317 respectively indicate the direction of air flow. In this example, the air inside and outside the housing 311 is basically exchanged only by these air inlet 316 and air outlet 317 . Measurement units 314 and 315 are installed near the target devices 312 and 313, respectively. The measurement units 314 and 315 measure pollutants at the location. In other words, the measuring unit 314 measures the environmental factors that affect the target device 312 . The measurement unit 315 also measures environmental factors that affect the target device 313 . That is, the measuring units 314 and 315 correspond to the environmental factor measuring unit 22 in FIG. Note that each of the target device 312 and the target device 313 may be provided with a measurement unit (not shown) for measuring the material factor (corresponding to the material factor measurement unit 21 in FIG. 1). In the example shown in FIG. 2, measurement units 314 and 315 are connected to the outside of housing 311 via communication lines. Then, functions other than the measurement unit 2 of the deterioration diagnosis device 1 (that is, the resistance value estimation unit 3, the validity determination unit 4, the diagnosis unit 5, the diagnosis result display unit 6, the estimation formula storage unit 7, A function including the model-specific material name storage unit 8 , the estimation formula creation analysis data storage unit 11 , and the estimation formula creation unit 12 ) exists outside the housing 311 . Then, each of measuring units 314 and 315 transmits the measurement result data to resistance value estimating unit 3 via the above communication line.

In the arrangement shown in FIG. 2 , pollutants (ionic substances, etc.) in the air are distributed within the housing 311 according to the flow of the airflow within the housing 311 . By providing a measuring unit near each target device, the contamination status (environmental factor) for each target device can be measured.
That is, the means for measuring the amount of adhered ionic contaminants in the measuring unit 2 is installed near the insulation resistance of the target device. This makes it possible to more accurately measure factors affecting the insulation resistance from the environment.

Also, if the flow of the airflow in the housing 311 is clear, for example, only the most easily soiled locations can be monitored and measured. For example, in the arrangement of FIG. 2, only measurement units 314 corresponding to target devices 312 located upstream of the airflow (generally indicated by thick arrows) may be provided.

FIG. 3 is a schematic diagram showing a second arrangement example when the deterioration diagnosis device according to the present embodiment is provided near the equipment to be diagnosed. In the example shown in this figure, target devices 312 and 313 are installed inside a housing 311 as in the case shown in FIG. Further, the housing 311 has an air inlet 316 and an air outlet 317 . That is, as in the case shown in FIG. 2, the air outside the housing 311 flows into the housing 311 through the intake port 316 . Also, the air inside the housing 311 flows out of the housing 311 through the exhaust port 317 . A measurement unit 318 is installed near the intake port 316 in the housing 311 . The measurement unit 318 measures the pollutants at that location. The air flowing into the housing 311 from the intake port 316 passes through the surroundings of the measurement unit 318 , circulates within the housing 311 , passes through the exhaust port 317 , and flows out of the housing 311 . In other words, the measuring unit 318 measures environmental factors that affect the target devices 312 and 313 . That is, the measuring section 318 corresponds to the environmental factor measuring section 22 in FIG. Note that each of the target device 312 and the target device 313 may be provided with a measurement unit (not shown) for measuring the material factor (corresponding to the material factor measurement unit 21 in FIG. 1). In the example shown in FIG. 3 as well, the measuring section 318 is connected to the outside of the housing 311 via a communication line. Then, functions other than the measurement unit 2 of the deterioration diagnosis device 1 (that is, the resistance value estimation unit 3, the validity determination unit 4, the diagnosis unit 5, the diagnosis result display unit 6, the estimation formula storage unit 7, A function including the model-specific material name storage unit 8 , the estimation formula creation analysis data storage unit 11 , and the estimation formula creation unit 12 ) exists outside the housing 311 . Then, the measuring section 318 transmits the measurement result data to the resistance value estimating section 3 via the above communication line.

In the arrangement shown in FIG. 3 , a measurement unit 318 provided near the intake port 316 measures the amount of pollutants (ionic substances, etc.) flowing into the housing 311 . At each location of target devices 312 and 313 that are actually monitored, the amount of contaminants is estimated to be less than near air inlet 316 . In other words, the arrangement shown in the figure is effective in detecting a sign of deterioration in the insulation resistance value of the target devices 312 and 313 in advance.
When a sign of a decrease in insulation resistance value is detected, it is possible to carry out a visual inspection by manual work, conventional measurement of the degree of contamination, etc. for each target device. As a result, preventive maintenance can be achieved while suppressing the number of installed measuring means.

That is, in this example, the means for measuring the amount of adhered ionic contaminants in the measuring unit 2 is installed in the vicinity of the intake port of the housing containing the insulation resistance in the target device.
Furthermore, the means for measuring the amount of adhered ionic pollutants may be installed in the vicinity of the exhaust port of the housing.

Next, an implementation example of the environmental factor measurement unit 22 will be described.
4 and 5 are a cross-sectional view and a plan view showing a sensor, which is one structural example of the environmental factor measuring unit 22. FIG. FIG. 4 is a cross-sectional view. FIG. 5 is a plan view. The cross-sectional view of FIG. 4 shows a cross-section cut along the dashed-dotted line CC' in FIG.
As shown in FIGS. 4 and 5, the environmental factor measurement unit 22 according to this example has an insulating plate 31, a first electrode 32, and a second electrode 33. As shown in FIGS. The first electrode 32 and the second electrode 33 are arranged in a predetermined pattern on the insulating plate 31 with a predetermined distance from each other. For pattern formation of the first electrode 32 and the second electrode 33, for example, a printing technique is used. As shown in FIG. 5, the first electrode 32 and the second electrode 33 are connected to a voltage source (“V” in the figure) and an ammeter (“A” in the figure), respectively. A voltage source applies an AC voltage or a DC voltage between the first electrode 32 and the second electrode 33 . The ammeter measures the current flowing from the first electrode 32 to the second electrode 33 . In FIG. 4, reference numeral 34 denotes fouling matter or water film. The deposition of the foulant/water film 34 causes a leakage current to flow from the first electrode 32 to the second electrode 33 . The ammeter described above measures this leakage current.
That is, the ammeter described above measures the ionic conductivity of the contaminant/water film 34 attached on the electrode patterns (the first electrode 32 and the second electrode 33). The measured current varies depending on the amount of attached fouling matter or water film.

As described above, in this example, the means for measuring the amount of ionic pollutants attached in the measurement unit 2 measures the conductivity of the water film containing the ionic pollutants attached to the sensor having electrodes. be.

Alternatively, different metals may be used for the first electrode 32 and the second electrode 33, and the galvanic current flowing between the electrodes may be measured. In this case, the galvanic current will vary depending on the amount of deposited moisture and the amount of deposited ionic foulant. That is, by measuring the galvanic current, it is possible to estimate the adhesion amount of the ionic contaminants between the electrodes.

Note that the temperature and humidity at the time of measurement affect the water content between the electrodes. In other words, the value measured by the ammeter also changes depending on the temperature and humidity. Therefore, the correlation between the contamination degree of the adhering matter, the temperature, the humidity, and the sensor measurement value (current) is obtained in advance. This makes it possible to correct the contribution due to moisture from the measured current value. Then, the environmental factor measurement unit 22 measures the temperature, humidity, and current, and estimates the contamination level of the adhering matter from these measured values. As described above, the environmental factor measurement unit 22 measures the degree of adherence of contaminants that cause a decrease in the insulation resistance value.
In this case, the estimation formula calculates the estimated resistance value based on the temperature and humidity as well.

Another implementation example of the environmental factor measurement unit 22 will also be described.
A quartz crystal oscillator (QCM) method or a surface acoustic wave (SAW) method can be applied to capture the mass change due to the attachment of contaminants. In this way, the method of determining the amount of adhered contaminants by measuring changes in vibration characteristics accompanying minute changes in weight is relatively easy, and the amount of adhered contaminants can be detected and quantified with high sensitivity. can do.

FIG. 6 is a schematic diagram showing a sensor, which is one configuration example of the environmental factor measurement unit 22 using the crystal oscillator method. As illustrated, the sensor according to this example is configured by sandwiching a crystal oscillator 40 between electrodes 43 and 44 . A voltage can be applied between the electrodes 43 and 44 from the outside. When a voltage is applied between these electrodes, the crystal oscillator 40 vibrates at its own frequency (resonant frequency). Also, the deposits 41 and 42 are fouling substances. Since the mass changes depending on whether the deposits 41 and 42 are attached or not, the resonance frequency of the crystal oscillator 40 is changed. Also, the resonance frequency of the crystal oscillator 40 changes according to the amount of deposits. The sensor according to this example can measure the mass of the deposit based on the change in this resonance frequency. As a measurement accuracy, it is possible to measure a mass change on the order of 0.1 ng (nanogram).

That is, the means for measuring the adhesion amount of ionic contaminants in the measuring unit 2 measures the change in the mass of the sensor caused by the adhesion of contaminants including ionic contaminants to the sensor.

As with the configuration examples shown in FIGS. 4 and 5, also in the configuration example of FIG. 6, the temperature and humidity at the time of measurement affect the amount of water adhering to the crystal oscillator. In other words, the measured value of the change in mass varies depending on the temperature and humidity. Therefore, the correlation between the contamination degree of the adhering matter, the temperature, the humidity, and the sensor measurement value (current) is obtained in advance. This makes it possible to correct the contribution due to moisture from the measured mass change value. Then, the environmental factor measurement unit 22 measures the temperature, humidity, and mass change, and estimates the contamination degree of the adhering matter from these measured values.

An ion chromatography method, a method using an ion-selective electrode, or the like is used to measure the ion components contained in the adhering fouling substances. In order to use these methods, it is necessary to develop the ionic components of the contaminants that have flown in water, and then supply the water to an analytical instrument.

FIG. 7 is a schematic diagram showing a configuration example of an ion component analyzer for analyzing and measuring ion components. As illustrated, the ion component analyzer 50 includes a pure water supply unit 51, a pure water supply pipe 52, a contaminant collection tank 53, a sampling pipe 54, a three-way valve 56, a cleaning drainage pipe 57, a component and a measurement unit 58 . This ion component analyzer 50 functions as follows.

A pure water supply unit 51 supplies pure water through a pure water supply pipe 52 when necessary.
The pure water supply pipe 52 supplies the pure water supplied from the pure water supply unit 51 to the contaminant collection tank 53 when necessary.
The contaminant collection tank 53 collects contaminants flying from the outside. While the ion component analyzer 50 is left unattended, contaminants from the outside accumulate in the contaminant collection tank 53 . After the fouling substances are deposited during the standing period, the ionic substances contained in the fouling substances are dissolved in the pure water supplied from the pure water supply pipe 52 during the dissolution period. The water in which the ionic substance is dissolved flows from the contaminant collection tank 53 to the sampling pipe 54 side.
The sampling pipe 54 has a function of supplying water containing ionic substances collected in the contaminant collection tank 53 to the component measuring section 58 via the three-way valve 56 .
A pump is provided between the contaminant collection tank 53 and the three-way valve 56 . This pump creates water pressure in the sampling line 54 . The action of this pump causes water to flow from the left side of the drawing to the right side in the sampling pipe 54 .
The three-way valve 56 is a valve having inlets and outlets in three directions. In the ion component analyzer 50 , the three-way valve 56 can switch whether the water from the contaminant collection tank 53 is led to the component measurement section 58 side or to the cleaning drainage pipe 57 side. That is, when performing measurement by the component measuring unit 58, the water from the contaminant collection tank 53 is supplied to the component measuring unit 58 side. Further, when the measurement by the component measuring unit 58 is completed, the water from the contaminant collection tank 53 flows to the cleaning drainage pipe 57 side and is drained.
The cleaning drain pipe 57 is a pipe for draining unnecessary water (water stored in the contaminant collection tank 53).
The component measurement unit 58 measures the types and amounts of ion components contained in the supplied water by ion chromatography, a method using an ion-selective electrode, or the like. The component measurement unit 58 outputs measurement result data.

By using the ion component analyzer 50 configured as described above, (1) deposition of contaminants from the outside → (2) analysis and measurement of ion components → (3) not used for measurement of ion components The measurement can be repeated with the process of draining water as one cycle. Note that the cycle of measurement is set as appropriate.

That is, the means for measuring the amount of adhered ionic contaminants in the measurement unit 2 includes an ionic component analyzer 50 for analyzing the composition of the ionic contaminants. The ionic component analyzer 50 qualitatively and quantitatively analyzes the composition of ionic fouling components.

As described above, according to the present embodiment, among the material factors related to the insulating material of the insulation resistance used in the target equipment, or the environmental factors at the place where the insulation resistance is installed, the adhesion of ionic contaminants , and a resistance value estimating unit for estimating the resistance value of the insulation resistance using the measurement result, the resistance value can be accurately predicted.

Also, depending on the structure of the electrical equipment, the degree of contamination may differ depending on the location in the equipment due to the influence of air currents.
In the present embodiment, the means for measuring the adhesion amount of the ionic fouling component may be installed near the insulating material to be diagnosed, so that it is possible to more accurately grasp the fouling state of the target material. Become.

In addition, if a means for measuring the amount of adhered ionic fouling components can be installed for each insulating material to be diagnosed, it will be possible to predict the insulation deterioration of each material with high accuracy, but all insulating materials are used. It is difficult to install the measuring means individually in each part.
In the present embodiment, it is also possible to use a method of measuring the state of contamination of the portion of the insulating material that is most susceptible to contamination due to air currents.
It is also possible to install means for measuring the amount of adhered ionic contaminants in the vicinity of the intake port of the housing containing the insulating material to be diagnosed. In this case, although it is not possible to obtain information about the local contamination status within the housing, it is possible to comprehensively grasp the contamination level within the housing.
When it is detected that the overall level of contamination inside the housing has increased, preventive maintenance can be achieved while reducing the number of measurement means to be installed by performing visual inspection or the like manually.
Moreover, the means for measuring the amount of adhered ionic fouling components may be installed not only in the intake port of the housing containing the insulating material to be diagnosed but also in the vicinity of the exhaust port of the same housing. In this case, the amount of ionic contaminant components discharged from the housing can be grasped from the result of the measuring means near the discharge port. Therefore, it is possible to more accurately grasp the amount of the ionic contaminant remaining inside the housing.

Further, in this embodiment, in order to measure the adhesion amount of the ionic fouling components, means for measuring the ionic conductivity in the water film in which the ionic fouling components are dissolved may be provided. The fouling component of the ionic component causes a decrease in insulation resistance by increasing the conductivity of the water film on the surface of the insulating material. Therefore, by measuring the conductivity, it is possible to directly evaluate the degree of influence on insulation deterioration.

In order to measure the adhesion amount of the ionic fouling component, it is also possible to provide means for measuring the change in mass caused by the adhesion of fouling substances. As described above, sea salt particles, gases, and the like cause a decrease in insulation resistance, but the mass increases as the amount of these ionic fouling components increases. When measuring mass, non-ionic dust is also measured, but the non-ionic dust is carried by the air currents as well as the ionic pollution components. Therefore, when ionic fouling components increase, nonionic dust tends to increase at the same time. Therefore, by measuring the change in mass, it becomes possible to predict the increase in ionic fouling components.

Furthermore, by providing means for qualitatively and quantitatively analyzing the composition of the ionic fouling components, it becomes possible to evaluate the degree of influence on insulation degradation with even higher accuracy.

Nitrate ions are also an ionic component that greatly affects the insulating properties. When the insulation resistance decreases and discharge begins to occur, nitric acid is generated using nitrogen in the air as a raw material. This nitric acid melts into the water film and reacts with calcium carbonate, which is a filling material of the insulating material, to produce calcium nitrate that deliquesces at low humidity, resulting in a rapid decrease in insulation. Therefore, detecting the presence of nitrate ions is an effective means for predicting the tendency of insulation deterioration.

As described above, the influence of foreign contaminants was dominant until then, but at some point, the influence of nitric acid generated by discharge may change to the main factor of insulation deterioration. In that case, there is a possibility that the prediction formula for the degree of progress of insulation resistance reduction will change.
Therefore, by detecting an increase in the amount of nitrate ions, it is possible to detect the change point of the deterioration mode as described above and switch the prediction formula for the degree of progress of deterioration in insulation resistance, making it possible to diagnose the remaining life with higher accuracy. becomes.

(Second embodiment)
Next, a second embodiment will be described. In addition, description may be abbreviate|omitted below about the matter already demonstrated in the previous embodiment. Here, the description will focus on matters specific to this embodiment.

FIG. 8 is a block diagram showing a schematic functional configuration of the deterioration diagnosis system according to this embodiment.
As illustrated, the deterioration diagnosis system 100 includes a measurement device 110 and an analysis device 120. FIG. The measuring device 110 and the analyzing device 120 are interconnected via a communication network. Note that a plurality of measuring devices 110 may be included in the deterioration diagnostic system 100 .

The measuring device 110 includes a measuring section 2 and a measured value transmitting section 111 .
The analysis device 120 also includes a measured value receiving unit 121, a resistance value estimating unit 3, a validity determining unit 4, a diagnostic unit 5, a diagnostic result display unit 6, an estimation formula storage unit 7, a model-specific material It includes a name storage unit 8 , an estimation formula creation analysis data storage unit 11 , and an estimation formula creation unit 12 . The measurement device 110 is implemented using, for example, a server computer.
Among the above functional units, the measurement unit 2, the resistance value estimation unit 3, the validity determination unit 4, the diagnosis unit 5, the diagnosis result display unit 6, the estimation formula storage unit 7, and the model-specific material name The storage unit 8, the analysis data storage unit 11 for creating an estimation formula, and the estimation formula creation unit 12 have the same functions as those in the first embodiment (see FIG. 1). Therefore, detailed description of each of these functional units is omitted here.

A measurement value transmission unit 111 on the measurement device 110 side transmits data obtained as a result of measurement by the measurement unit 2 to the analysis device 120 side via a communication network.
The measurement value receiving unit 121 on the analysis device 120 side receives the measurement result data transmitted from the measurement value transmission unit 111 on the measurement device 110 side. The measured value receiving section 121 passes the received measurement result data to the resistance value estimating section 3 .
As a result, the analysis device 120 side estimates the resistance value based on the data measured by the measurement device 110 side, determines the validity of the estimated resistance value, makes a diagnosis, and displays the diagnosis result. .

According to this embodiment, the degradation diagnosis system 100 can be configured with a single or a small number of analysis devices 120 and a large number of measurement devices 110 by a so-called client-server configuration. In other words, the necessary measurements are performed at the site where the target equipment is installed, and the process of estimating the resistance value using the data of those measurement results is concentrated on a small number of server devices installed in a data center, etc. It can be carried out. As a result, the cost of the deterioration diagnosis system 100 as a whole can be reduced.

(Third embodiment)
Next, a third embodiment will be described. In addition, description may be abbreviate|omitted below about the matter already demonstrated by the previous embodiment. Here, the description will focus on matters specific to this embodiment.

FIG. 9 is a block diagram showing a schematic functional configuration of the deterioration diagnosis system according to this embodiment.
As illustrated, the deterioration diagnosis system 150 includes a measurement device 110 and an analysis device 160. FIG. The measuring device 110 and the analyzing device 160 are interconnected via a communication network. Note that a plurality of measuring devices 110 may be included in the deterioration diagnostic system 100 .

The measuring device 110 includes a measuring section 2 and a measured value transmitting section 111 .
The analysis device 160 also includes a measured value receiving unit 161, an analysis data collecting unit 162, a resistance value estimating unit 3, a validity determining unit 4, a diagnostic unit 5, a diagnostic result display unit 6, and an estimation formula storage. It includes a unit 7 , a model-specific material name storage unit 8 , an estimation formula creation analysis data storage unit 11 , and an estimation formula creation unit 12 . Analysis device 160 is implemented using, for example, a server computer.
Among the above functional units, the measurement unit 2, the resistance value estimation unit 3, the validity determination unit 4, the diagnosis unit 5, the diagnosis result display unit 6, the estimation formula storage unit 7, and the model-specific material name The storage unit 8, the analysis data storage unit 11 for creating an estimation formula, and the estimation formula creation unit 12 have the same functions as those in the first embodiment (see FIG. 1). Therefore, detailed description of each of these functional units is omitted here.

A measurement value transmission unit 111 on the measurement device 110 side transmits data obtained as a result of measurement by the measurement unit 2 to the analysis device 120 side via a communication network.
The measurement value receiving unit 161 on the analysis device 160 side receives the measurement result data transmitted from the measurement value transmission unit 111 on the measurement device 110 side. The measured value receiving section 161 passes the received measurement result data to the resistance value estimating section 3 .
As a result, the analysis device 160 side estimates the resistance value based on the data measured by the measurement device 110 side, determines the validity of the estimated resistance value, makes a diagnosis, and displays the diagnosis result. .

Also, the measured value receiving unit 161 on the analysis device 160 side passes the received data to the analysis data collecting unit 162 . The analysis data collection unit 162 writes the data received from the measurement value reception unit 161 into the analysis data storage unit 11 for creating an estimation formula. In other words, the estimation formula creation unit 12 performs analysis including the data collected by the analysis data collection unit 162 when creating the estimation formula with reference to the analysis data storage unit 11 for creation of the estimation formula. That is, the analysis device 160 can create an estimation formula using not only pre-stored analysis data but also data received from the measurement device 110 . Note that the analysis data used to create the estimation formula may include the actual resistance value.

According to this embodiment, the analysis data collection unit 162 of the analysis device 160 writes the measurement result data received from the measurement device 110 into the analysis data storage unit 11 for creating an estimation formula. That is, the analysis device 160 can use the measurement result data received from the measurement device 110 to create an estimation formula for estimating the resistance value. Analysis device 160 can create this estimation formula at any appropriate timing. That is, the analysis device 160 can use the measurement result data collected from the measurement device 110 to learn the resistance value estimation formula.

A modification of the embodiment will be described.
In the arrangement examples shown in FIGS. 2 and 3 of the above embodiment, functions other than the measurement unit 2 included in the deterioration diagnosis device 1 (that is, the resistance value estimation unit 3, the validity determination unit 4, the diagnosis unit 5, function including diagnosis result display unit 6, estimation formula storage unit 7, model-specific material name storage unit 8, estimation formula creation analysis data storage unit 11, and estimation formula creation unit 12) exists in However, these resistance value estimation unit 3, validity determination unit 4, diagnosis unit 5, diagnosis result display unit 6, estimation formula storage unit 7, model-specific material name storage unit 8, estimation formula creation The analysis data storage unit 11 and the estimation formula creation unit 12 may exist inside the housing 311 .
Moreover, the arrangement method of the means for measuring the adhesion amount of the ionic contaminants in the measuring unit 2 is not limited to those illustrated in FIGS. 2 and 3, and other arrangement methods may be used.

As a specific example of means for measuring the amount of adhered ionic pollutants, a sensor, which is a method for realizing the same, has been described with reference to FIGS. may be used to measure the adhesion amount of the ionic pollutants.

In addition, the ionic component analyzer 50 shown in FIG. 7 analyzes the composition of the ionic contaminants. may be used to estimate the resistance value. That is, in this case, the resistance value estimator 3 switches the insulation resistance estimation formula for use depending on the composition of the ionic pollution component. Thereby, the resistance value estimator 3 can use an estimation formula that matches the composition of the ionic contaminants. That is, it becomes possible to estimate the resistance value more accurately.

According to at least one embodiment described above, the amount of ionic contaminants adhered among the material factors related to the insulating material of the insulation resistance used in the target device or the environmental factors at the location where the insulation resistance is installed , and a resistance value estimating unit that estimates the resistance value of the insulation resistance using the measurement result, the resistance value can be accurately predicted.

It should be noted that the functions of the deterioration diagnosis device, the measurement device, and the analysis device in each of the above-described embodiments may be realized by a computer. In that case, a program for realizing this function may be recorded in a computer-readable recording medium, and the program recorded in this recording medium may be read into a computer system and executed. It should be noted that the "computer system" referred to here includes hardware such as an OS and peripheral devices. In addition, “computer-readable recording media” refers to portable media such as flexible discs, magneto-optical discs, ROMs, CD-ROMs, DVD-ROMs, USB memories, and storage devices such as hard disks built into computer systems. Say things. Furthermore, "computer-readable recording medium" refers to a medium that dynamically retains a program for a short period of time, like a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line. It may also include things that hold programs for a certain period of time, such as volatile memories inside computer systems that are servers and clients in that case. Further, the program may be for realizing part of the functions described above, or may be a program capable of realizing the functions described above in combination with a program already recorded in the computer system.

It should be noted that when the measurement unit 2 in each embodiment is realized using a computer, the program "material factors related to the insulation material of the insulation resistance used in the target device, or the environment in the place where the insulation resistance is installed The computer is caused to execute the process of "measuring process for controlling to measure at least one of the factors, ie, the amount of ionic pollutant adhered." Under computer control, the physical quantity itself is measured by the sensor or the like described in the embodiment.

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

DESCRIPTION OF SYMBOLS 1... Deterioration diagnosis apparatus, 2... Measurement part, 3... Resistance value estimation part, 4... Validity determination part, 5... Diagnosis part, 6
Diagnosis result display unit 7 Estimation formula storage unit 8 Model-specific material name storage unit 11 Analysis data storage unit for creating estimation formula 12 Estimation formula creation unit 21 Material factor measurement unit 22 Environment factor measurement unit,
DESCRIPTION OF SYMBOLS 31... Insulating plate 32... First electrode 33... Second electrode 34... Contamination/water film 40... Crystal oscillator 41, 42... Deposits 43, 44... Electrode 50... Ion component analyzer , 51... Pure water supply unit, 52... Pure water supply pipe, 53... Contaminant collection tank, 54... Sampling pipe, 56... Three-way valve, 57... Cleaning drainage pipe, 58... Component measuring unit, 100... Deterioration diagnosis system, DESCRIPTION OF SYMBOLS 110... Measurement apparatus 111... Measurement value transmission part 120... Analysis apparatus 121... Measurement value reception part 150... Deterioration diagnosis system 160... Analysis apparatus 161... Measurement value reception part 162... Analysis data collection part,
311 ... housing, 312, 313 ... target device, 314, 315 ... measurement unit, 316 ... intake port,
317... Exhaust port, 318... Measurement part

Claims (11)

a measuring unit that measures at least one of a material factor related to the insulating material of the insulation resistance used in the target equipment, and an adhesion amount of ionic contaminants among the environmental factors in the place where the insulation resistance is installed; ,
an estimation formula storage unit that stores information related to an estimation formula for estimating the resistance value of the insulation resistance based on the measurement result of the measurement unit;
a resistance value estimating unit that estimates the resistance value of the insulation resistance using the measurement result obtained by the measuring unit and the estimation formula stored in the estimation formula storage unit;
and
The estimation formula is a formula for estimating the resistance value also based on temperature and humidity,
moreover,
Estimation formula creation for creating the estimation formula by multivariate analysis using the Taguchi method or the Taguchi-Schmidt method based on a set of the measured value of the measurement item measured by the measurement unit and the measured value of the resistance value of the insulation resistance Department and
Analysis data storage for estimation formula creation in which the estimation formula creation unit stores analysis data based on which the estimation formula is calculated, the analysis data including a set of the actual measurement value of the measurement item and the actual measurement value of the resistance value. Department and
an analysis data collection unit that collects analysis data measured by the measurement unit and writes the analysis data into the estimation formula creation analysis data storage unit;
with
The estimation formula creation unit performs analysis including the analysis data collected by the analysis data collection unit when creating an estimation formula with reference to the analysis data storage unit for creating the estimation formula, thereby obtaining a resistance value learn about the estimation formula for
Deterioration diagnosis system. A means for measuring the adhesion amount of the ionic contaminants in the measurement unit is installed near the insulation resistance in the target device,
The deterioration diagnosis system according to claim 1. A means for measuring the adhesion amount of the ionic contaminants in the measurement unit is installed near an intake port of a housing containing the insulation resistance in the target device,
The deterioration diagnosis system according to claim 1. In the measuring unit, the means for measuring the adhesion amount of the ionic pollutants is also installed near the exhaust port of the housing,
The deterioration diagnosis system according to claim 3. The means for measuring the amount of the ionic fouling substance attached in the measurement unit measures the conductivity of the water film containing the ionic fouling substance adhering to the sensor having electrodes.
The deterioration diagnosis system according to any one of claims 1 to 4. The means for measuring the amount of ionic contaminants attached in the measurement unit measures the change in the mass of the sensor due to the ionic contaminants adhering to the sensor.
The deterioration diagnosis system according to any one of claims 1 to 5. The means for measuring the amount of the ionic contaminants attached in the measuring unit comprises a component analyzer for analyzing the composition of the ionic contaminants.
The deterioration diagnosis system according to any one of claims 1 to 6. The resistance value estimating unit estimates the resistance value using the estimation formula according to the composition of the ionic contaminant analyzed by the component analyzer.
The deterioration diagnosis system according to claim 7. a validity determination unit that determines the validity of the estimation formula by comparing the resistance value estimated by the resistance value estimation unit and the measured value of the resistance value of the insulation resistance;
Based on the resistance value estimated using the estimation formula assuming a predetermined temperature and humidity assumed in the environment in which the target device is installed, representing the temporal change in the relationship between the usage period and the resistance value a diagnostic unit that estimates the time until the resistance value of the insulation resistance falls below a predetermined threshold by obtaining an estimated curve;
9. The deterioration diagnosis system according to any one of claims 1 to 8, further comprising: A measurement process of measuring at least one of the material factor related to the insulation material of the insulation resistance used in the target equipment, or the amount of ionic contaminants adhered among the environmental factors in the place where the insulation resistance is installed. run,
pre-storing information about an estimation formula for estimating the resistance value of the insulation resistance based on the measurement result of the measurement process;
executing a resistance value estimation process of estimating the resistance value of the insulation resistance using the measurement result obtained by the measurement process and the stored estimation formula;
A deterioration diagnosis method,
The estimation formula is a formula for estimating the resistance value also based on temperature and humidity,
moreover,
Estimation formula creation for creating the estimation formula by multivariate analysis using the Taguchi method or the Taguchi-Schmidt method based on a set of the measured value of the measurement item measured in the measurement process and the measured value of the resistance value of the insulation resistance process and
An analysis data storage unit for creating an estimation formula that stores analysis data that is a basis for obtaining the estimation formula in the process of creating the estimation formula and includes a set of the measured value of the measurement item and the measured value of the resistance value. an analysis data collection process of collecting and writing analysis data measured by the measuring unit;
and run
In the estimation formula creation process, when creating an estimation formula with reference to the analysis data storage unit for creating an estimation formula, analysis is performed including the analysis data collected in the analysis data collection process to obtain a resistance value learn about the estimation formula for
Deterioration diagnostic method. An estimation formula storage unit for storing information related to an estimation formula for estimating the resistance value of the insulation resistance based on the measurement result by the measurement unit; A computer having an analysis data storage unit for creating an estimation formula that stores analysis data including a set of measured values of measurement items and measured values of the resistance value,
Control to measure at least one of the material factor related to the insulation material of the insulation resistance used in the target equipment, or the amount of ionic contaminants adhered among the environmental factors at the location where the insulation resistance is installed a measuring process;
a resistance value estimation step of estimating the resistance value of the insulation resistance using the measurement result of the measurement step and the estimation formula stored in the estimation formula storage unit;
Estimation formula creation for creating the estimation formula by multivariate analysis using the Taguchi method or the Taguchi-Schmidt method based on a set of the measured value of the measurement item measured by the measurement unit and the measured value of the resistance value of the insulation resistance process and
an analysis data collection process of collecting analysis data measured in the measurement process and writing the analysis data into the estimation formula creation analysis data storage unit;
A program for executing
In the estimation formula creation process, when the estimation formula is created by referring to the analysis data storage unit for creating the estimation formula, analysis is performed including the analysis data collected in the analysis data collection process to obtain the resistance value learn about the estimation formula for
program.

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