JP2010038838A - System for diagnosing degradation in controller - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a system for diagnosing deterioration which accurately estimates future corrosion in a conductive member. <P>SOLUTION: The system 1 for diagnosing deterioration includes: a diagnosis processor 4 for recording environmental data in a controller 3 measured by sensors and corrosion data of the conductive member 9 for a preset period, estimating the future corrosion of the conductive member 9 based on the recorded environmental data in a housing and the corrosion data, and diagnosing the deterioration; and an external environment database 6 for recording external air environmental data including the previous temperature and humidity outside the controller 3. The diagnosis processor 4 obtains a correlation relationship between the environmental data in the controller 3 and the corrosion data recorded for the preset period, obtains a correspondence relationship between the external air environmental data and the environmental data in the controller 3 at the same time as the preset period, estimates future environmental data within the controller 3 from the correspondence relationship and the previous external air environmental data, and estimates the future corrosion of the conductive member 9 from the estimated environmental data in the controller 3 and the correlation relationship. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a deterioration diagnosis system for a control device.

  As a cause of failure of a control device that controls an elevator, a plant, or the like, corrosion of wiring on a printed circuit board that is housed in the control device and on which electronic components or the like are mounted and connection terminals of electronic components (hereinafter collectively referred to as conductive members). Deterioration due to Therefore, it is desirable to perform a deterioration diagnosis of the conductive member in advance to estimate the degree of progress of the future deterioration so that the deteriorated portion can be replaced before failure due to deterioration occurs.

  As a conventional deterioration diagnosis, the same metal material as the conductive member is used as a test piece, exposed to the control device for a certain period, the corrosion thickness is measured, the average corrosion progress is obtained from the corrosion thickness and the exposure period, and the obtained average corrosion is obtained. There is a method to estimate the future corrosion amount from the degree of progress. Further, as disclosed in Patent Document 1, there is a method of measuring temperature, humidity, and the like, which are factors of corrosion amount, giving an evaluation point to a range of measured values, and obtaining a future corrosion amount from a function of the evaluation point. .

JP 2001-215187 A

  By the way, the temperature and humidity, which are factors of the amount of corrosion, vary greatly depending on the season to which the test piece is exposed, and the temperature and humidity in the control device also vary depending on the operating state of the control device. The degree of corrosion progression is not constant. In the conventional method, fluctuations in temperature and humidity are not taken into consideration, and it is difficult to accurately estimate the corrosion amount.

  The problem to be solved by the present invention is to provide a deterioration diagnosis system that accurately estimates the amount of corrosion of a conductive member in the future.

  In order to solve the above problems, a deterioration diagnosis system according to the present invention includes a temperature sensor that measures the temperature in a casing in which a printed circuit board on which an electronic or electrical component including a conductive member to be diagnosed is mounted, a casing, and a casing. A humidity sensor that measures the humidity inside the body, a corrosion sensor that measures the amount of corrosion to be diagnosed, and the internal environment data consisting of the temperature and humidity inside the housing measured by each sensor and the corrosion data to be diagnosed A diagnostic processing device that records and diagnoses deterioration by estimating the future amount of corrosion to be diagnosed based on the recorded environmental data and corrosion data in the enclosure, and the outside air environment consisting of past temperature and humidity outside the enclosure An outside air environment database in which data is recorded, and the diagnostic processing device obtains a correlation between the in-chassis environment data recorded in the set period and the corrosion data, and the outside air environment in the set period The future environment data is estimated based on the correspondence and past outside air environment data, and the diagnosis is based on the estimated environment data and its correlation. It is characterized by estimating the future corrosion amount of the object.

  According to the present invention, since future environmental data in the housing can be estimated according to the actual situation, the future corrosion amount of the diagnosis target can be accurately estimated. That is, from the correspondence relationship between the outside air environment data and the housing environment data at the same time as the set period, for example, the temperature difference, the humidity difference, and the periodic change between the outside air environment data and the housing environment data are obtained. By applying to the outside air environment data, it is possible to estimate the future inside environment data in consideration of the periodic change of the inside environment data and the influence of the outside air environment data. Since the amount of corrosion depends on temperature and humidity, if the future environmental data in the housing can be accurately estimated according to the actual situation, the future corrosion amount can be accurately estimated. The set period is 1 to 3 months as a guide, but 3 months or more is desirable for high-precision estimation. For simple estimation, it may be about one week. In this case, it is preferable to use an electric resistance type corrosion sensor which is a highly accurate corrosion sensor. The outside air environment database can use, for example, weather statistics information of the Japan Meteorological Agency.

  Here, when the installation environment of the control device is controlled by air conditioning, the temperature and humidity outside the housing are the set temperature and humidity of the air conditioning.

  In this case, the deterioration diagnosis system includes a temperature sensor that measures the temperature in the housing in an air-conditioned atmosphere in which a printed circuit board on which an electronic or electrical component including a conductive member to be diagnosed is mounted, and a humidity in the housing. Record the humidity sensor to be measured, the corrosion sensor to measure the amount of corrosion to be diagnosed, the environmental data in the housing consisting of the temperature and humidity in the housing measured by each sensor, and the corrosion data to be diagnosed for a set period of time. A diagnostic processing device that performs deterioration diagnosis by estimating the future amount of corrosion to be diagnosed based on the recorded environmental data and corrosion data in the casing, and an air conditioning database in which air conditioning data including the set temperature and humidity of the air conditioning is recorded The diagnostic processing apparatus obtains a correlation between the environmental data in the enclosure recorded during the set period and the corrosion data, and is based on the correspondence between the environmental data in the enclosure and the air conditioning data. There are estimates of future enclosure environmental data, it is desirable to configure to estimate future corrosion of the diagnostic object from its estimated enclosure environment data and the correlation.

  Thereby, similarly to the case of the outside air environment data, it is possible to accurately estimate future changes in the temperature and humidity in the casing in accordance with the set temperature and humidity of the air conditioning, and it is possible to accurately estimate the amount of corrosion. .

  By the way, as a further factor of failure of the control device, there is an insulation deterioration between conductive members on the printed circuit board. Therefore, it is necessary to estimate the insulation deterioration as well as the estimation of the corrosion amount.

  In this case, the deterioration diagnosis system includes a temperature sensor that measures the temperature in the housing in which the printed circuit board on which the electronic or electrical component including the conductive member to be diagnosed is mounted, and the humidity that measures the humidity in the housing. The sensor, the dust sensor for measuring the amount of dust attached to the object to be diagnosed, the in-chassis environment data and the dust data including the temperature and humidity in the housing measured by each sensor are recorded for a set period, and the recorded housing A diagnostic processing device for diagnosing insulation deterioration of a diagnosis target based on in-vivo environmental data and dust data, and an outdoor air environment database in which outdoor air environment data consisting of past temperature and humidity outside the housing is recorded. The device obtains the correlation between the environmental data in the enclosure recorded during the set period and the progress of insulation deterioration, and the correspondence between the outside air environmental data and the environmental data in the enclosure during the set period. The future environmental data in the enclosure is estimated based on the correspondence and the past outdoor air environment data, and the degree of progress of the future insulation deterioration of the diagnosis target is determined from the estimated environmental data in the enclosure and the correlation between the estimated environmental data. It is desirable to configure to estimate.

  As a result, as in the estimation of the corrosion amount, the future environmental data in the housing can be accurately estimated. The main cause of insulation degradation is ion migration, and the factors of ion migration are temperature, humidity, and dust amount. Therefore, the estimated environmental data in the enclosure, the environmental data in the enclosure recorded during the set period, and the progress of insulation degradation. The degree of progress of insulation deterioration can be accurately estimated from the amount of dust estimated from the correlation with.

  Moreover, when the installation environment of a control apparatus is air-conditioning-controlled, it is desirable to provide an air-conditioning database similarly to the said corrosion amount estimation.

  ADVANTAGE OF THE INVENTION According to this invention, the deterioration diagnostic system which estimates the future corrosion amount accurately can be provided.

  A first embodiment of the present invention will be described below with reference to the drawings.

  FIG. 1A is a configuration diagram of the deterioration diagnosis system 1, and FIG. 1B is a plan view of the printed circuit board 10 accommodated in the control device 3. The degradation diagnosis system 1 includes an environment measurement device 2, a diagnosis processing device 4, an outside air environment database 6, and a diagnosis result output device 8.

  The environment measuring device 2 is installed in a control device 3 that controls an elevator or the like, and a printed circuit board 10 including a conductive member 9 to be diagnosed is accommodated in the control device 3. The environment measuring device 2 includes a temperature sensor 12 that measures the temperature in the control device 3 (hereinafter referred to as internal temperature) and a humidity sensor 14 that measures the relative humidity in the control device 3 (hereinafter referred to as internal relative humidity). And a corrosion sensor 16 for measuring the amount of corrosion of the conductive member 9, a dust sensor 18 for measuring the amount of dust adhering to the conductive member 9, and a database 22 for recording data of each sensor. The temperature sensor 12 and the relative humidity sensor 14 are configured to measure the internal temperature and the internal relative humidity at regular intervals and send data to the database 22.

  Here, the corrosion sensor 16 and the dust sensor 18 will be described with reference to FIG. The corrosion sensor 16 is an electrical resistance type corrosion sensor, and is composed of a substrate 23 such as glass, an electrode pad 24, and a silver electrode 25, and is mounted on the printed board 10. The corrosion sensor 16 is configured to measure the amount of corrosion at regular intervals and send the data to the database 22 by utilizing the increase in electrical resistance when the cross-sectional area of the silver electrode 25 decreases due to corrosion. The dust sensor 18 includes a substrate 26 such as glass, an electrode pad 27 and a comb electrode 28, and is mounted on the printed board 10. The dust sensor 18 is configured to measure the amount of dust at regular intervals from the leakage current between the electrodes due to attached dust and send the data to the database 22. Examples of the types of dust include aerosols in addition to dust and lint. The substrates 23 and 26 can also be used as the printed circuit board 10.

  The measurement result obtained by the environment measuring device 2 is processed by the diagnostic processing device 4. The diagnostic processing device 4 is incorporated in an information processing terminal such as a personal computer (not shown). A history of the temperature outside the control device 3 (hereinafter referred to as “external temperature”) and a history of the absolute humidity outside the control device 3 (hereinafter referred to as “external absolute humidity”) are stored in the outside air environment database 6. Yes. The outdoor air environment database 6 may use information on the measurement point closest to the control device 3 among the weather statistical information published by the Japan Meteorological Agency.

  As shown in FIG. 1A, the diagnosis processing device 4 includes an environment estimation unit 30, a damage estimation unit 32, and a life diagnosis unit 34. The environment estimation unit 30 estimates the internal temperature and the relative humidity inside the control device 3 (hereinafter referred to as “internal relative humidity”) from the measurement result by the environment measurement device 2 and the data in the outside air environment database 6, and the estimation result. Is output to the damage estimation unit 32. The damage estimation unit 32 is configured to estimate the corrosion amount and the insulation deterioration based on the estimation result of the environment estimation unit 30 and to output the estimation result to the life diagnosis unit 34. The life diagnosis unit 34 is configured to diagnose the life based on the estimation result of the damage estimation unit 32 and to output the diagnosis result to the diagnosis result output device 8. The diagnosis result output device 8 is configured to output the diagnosis result to a display screen of an information processing terminal (not shown).

  The operation of the deterioration diagnosis system 1 configured as described above will be described with reference to FIG. FIG. 2 is a processing flow of the deterioration diagnosis system 1. In step 1, the temperature sensor 12 and the humidity sensor 14 of the environment measuring device 2 are installed in the control device 3, and the corrosion sensor 16 and the dust sensor 18 are placed near the printed circuit board 10 or the printed circuit board 10 as shown in FIG. Install. Measurement is performed for 1 to 3 months by each installed sensor. Three months or more may be used for high-precision measurement, and one week may be used for simple measurement. The measurement period is preferably a period of high relative humidity that greatly affects corrosion and insulation deterioration. In this embodiment, as an example, measurement is performed for three months from August to October in 2007. In general, the conductive member 9 is copper, but here, the corrosion is estimated using a silver electrode 25 which is a metal different from the conductive member 9. The reason for this is that silver is more easily corroded than copper and corrosion proceeds in a short period of time. Therefore, by estimating the corrosion of silver, the corrosion of the conductive member 9 which is copper can be dealt with early. Of course, corrosion may be estimated using copper.

  Step 2 will be described with reference to FIGS. 3A and 3B are processing steps of the environment estimation unit 30 of the diagnostic processing apparatus 4. FIG. 4A is a graph of the internal temperature and the external temperature, and FIG. 4B is a frequency characteristic of the internal temperature and the external temperature. FIG. 5 is a graph of the absolute humidity inside the control device 3 (hereinafter referred to as internal absolute humidity) and the external absolute humidity. The environment estimation unit 30 includes the internal temperature and internal relative humidity from August to October measured in Step 1 and the external temperature and external absolute humidity from August to October stored in the outdoor air environment database 6. Entered.

  First, as for the temperature, as shown in FIG. 4, a temperature difference ΔT between the internal temperature and the external temperature is calculated. The temperature difference ΔT is obtained from the average temperature during the three months from August to October. Further, the frequency characteristic of the internal temperature is extracted by discrete Fourier analysis. The internal temperature is affected by the external temperature and heat generated by the operation of the control device 3. For example, the internal temperature of the control device 3 that operates and stops every day has a characteristic of a one-day cycle due to operation and stop as well as fluctuations in the external temperature. In addition, the control device 3 that operates / stops on weekdays and stops on weekends has a feature of a one-week cycle as well as a feature of a one-day cycle. Normally, the control device 3 rarely has a characteristic of a period of one week or more, but can acquire frequency characteristics of any period by Fourier analysis. FIG. 4B shows periodic characteristics of the internal temperature and the external temperature. Both the internal temperature and the external temperature are characterized by a one-day cycle. However, the internal temperature has a remarkable feature of a one-week cycle corresponding to the frequency of use of the control device 3.

  The calculated frequency characteristics are taken into account in the past external temperatures from the measurement period stored in the outside air environment database 6, for example, the external temperatures from January to December of 2006, with the temperature difference ΔT and the frequency characteristics calculated above. By doing so, the internal temperature in the future, for example, from January to December of 2009 can be estimated.

  Next, estimation of internal relative humidity will be described. Since the moisture outside the control device 3 immediately moves into the control device 3, the external absolute humidity and the internal absolute humidity are almost the same. Therefore, if the external absolute humidity obtained from the external air environment database 6 and the internal absolute humidity calculated using the measured internal temperature and the internal relative humidity can be compared and confirmed to be equivalent, the past external absolute humidity can be confirmed. For example, using the conversion formula of absolute humidity-temperature-relative humidity from external absolute humidity from January to December in 2006, estimation of internal relative humidity in the future, for example, January to December, 2009 Can do.

  As described above, the environment measurement unit 30 obtains a correspondence relationship between the external temperature and external absolute humidity, the internal temperature and the internal relative humidity at the same time as the measurement period, and the correspondence relationship with the past external temperature and external absolute humidity. Based on this, the future internal temperature and internal relative humidity can be estimated.

  The processing relating to the corrosion of the damage estimation unit 32 in step 3 will be described with reference to FIG. FIG. 6 shows processing steps of the environment estimation unit 30. The environment estimation unit 30 receives the amount of corrosion measured in step 1, the internal temperature estimated in step 2, and the internal relative humidity.

Next, the correlation between the internal temperature and internal relative humidity and the amount of corrosion is obtained. The amount of corrosion X of silver is mainly produced by silver sulfide. For example, Furukawa Electric Times Vol. 79, page 93 (1986) shows Equation (1) as an empirical formula.
X = X ₀ * [H2S] ^1.0 * [RH] ⁿ * exp (-E / kT) * t (1)
Where _{X 0} is a coefficient, [H2 S] is the concentration of hydrogen sulfide, [RH] is the relative humidity, E is the activation energy, k is the Boltzmann constant, T is the absolute temperature, t represents time. Here, when X ₀ · [H 2 S] ^1.0 is defined as the corrosive gas coefficient C ₀ , the corrosion amount X is given by the equation (2).
^{_{X = C 0 · [RH]}} n · exp (-E / kT) · t (2)
Here, the corrosion amount X _UT in the unit time t _UT of the measurement of each sensor of the environment measuring device 2 is given by the equation (3) in the environment of the temperature T and the relative humidity RH.
X _UT = C ₀ · [RH] ⁿ · exp (−E / kT) · t _UT (3)
Here, since the corrosion amount X of silver is proportional to time, the corrosion amount X _CS during the measurement period t _CS of the corrosion sensor 16 is given by the equation (4) as an integrated value of the corrosion amount X _UT of the unit time t _UT. It is done.
X _CS = ΣX _UT = C ₀ · Σ {[RH] ⁿ · exp (−E / kT) · t _UT } (4)
C ₀ is given as equation (5) from equation (4).
C ₀ = X _CS / Σ {[RH] ⁿ · exp (−E / kT) · t _UT } (5)
As described above, the corrosive gas coefficient _C0 is a value specific to each installation environment of the control device, and can be determined by substituting the measured internal temperature, internal relative humidity, corrosion amount, and measurement period into the equation (5). . If estimated using actually a calculator, as previously corroded amount X _CS of the measurement period t _CS of the integrated amount of corrosion of the corrosive gas coefficient was estimated by assuming a temporary corrosion sensor 16 are equal, corrosive You may employ | adopt the method of setting a gas coefficient. Here does not take into account seasonal variations in the corrosive gas coefficient C _0, but considering the measured at certain intervals Seasonal variation of corrosive gases coefficients C _0, it is more accurate estimation. The internal temperature and the value of the internal relative humidity estimated by the determined corrosive gases coefficients C ₀ and Step 2 can be estimated accumulated amount of corrosion by substituting the equation (4). FIG. 7A shows actual measured values and estimated values of the amount of silver corrosion. Both agree well, and this estimation method is appropriate.

Here, a case where the metal to be diagnosed is copper will be described. Since the corrosion amount of copper is proportional to the 1/2 power of time, the corrosion amount per unit time cannot be simply integrated. Copper corrosion amount _XCu is given by equation (6).
^{_{X = C 0 · [RH]}} n · exp (-E / kT) · t 0.5 (6)
When the temperature at the first unit time t = t ₁ is T ₀ , the relative humidity is RH ₀ , and the film thickness is X ₀ , the amount of corrosion is given by Equation (7).
^{_{X 0 = C 0 · [RH}} 0] n · exp (-E / kT 0) · t 1 0.5 (7)
The temperature at the next unit time t = (t ₂ −t ₁ ) is T ₁ , the relative humidity is RH ₁ , and the film thickness is X ₁ . Corrosion coating of thickness X ₀ is formed on the surface of the copper. Here, it is assumed that the corrosion resistance of the copper corrosion film does not depend on temperature and relative humidity. The conversion time t _2c during which the film thickness X ₀ is formed in the environment of the temperature T ₁ and the relative humidity RH ₁ is given by Expression (8).
t _2c = [X ₀ / {C ₀ · [RH ₁ ] ⁿ · exp (−E / kT ₁ )}] ² (8)
Therefore, the corrosion amount X ₁ in the next unit time t = (t ₂ −t ₁ ) is given by equation (9).
^{_{X 1 = C 0 · [RH}} 1] n · exp (-E / kT 1) · (t 2c + t 1) 0.5 (9)
By correcting the elapsed time in this way and obtaining the equivalent elapsed time, the amount of corrosion can be accurately estimated even in the case of a metal such as copper where the amount of corrosion is not proportional to time.

  In step 4, the life diagnosis unit 34 receives the amount of corrosion estimated in step 3 and the ratio of the corrosion tolerance stored in the corrosion database 36. The life diagnosis unit 34 obtains the corrosion integrated damage rate from these, and obtains the time when the corrosion integrated damage rate reaches 1 as the corrosion life as shown in FIG.

  Next, the process regarding the insulation deterioration of the damage estimation part 32 of step 3 'is demonstrated with reference to FIG. FIG. 8 shows a process for insulation deterioration of the environment estimation unit 30, and the amount of dust measured in step 1, the internal temperature estimated in step 2, and the internal relative humidity are input to the environment estimation unit 30.

The main cause of insulation deterioration is ion migration. Since ion migration takes place through electrochemical elution of the anode metal, transport of metal ions, electrochemical deposition at the cathode and a three-stage reaction, its lifetime needs to be evaluated for each stage reaction. Here, the lifetime calculated by combining the three-stage reaction is used. FIG. 9A shows the relationship between the ion migration lifetime, the relative humidity, and the amount of dust when the temperature is constant and the electric field strength is constant. The ion migration lifetime L depends on the absolute temperature T, the relative humidity RH, and the dust amount D, and is given by the equation (10).
L = C * E- ^m * [RH] ^-n * D- ^p * exp (E / kT) (10)
Here, C is a constant, m, n, and p are exponents, E is an activation energy, and k is a Boltzmann constant. Since temperature and humidity fluctuate in an actual environment, a life estimation formula that takes into account temperature and humidity fluctuations is required. Therefore, we introduce the concept of linear cumulative damage law (Miner's law) used in fatigue life estimation. Let the lifetimes at relative humidity RH ₁ , RH ₂ , RH ₃ ,... Be L ₁ , L ₂ , L ₃ ,. T ₁ / L ₁ , t ₂ / L ₂ , t ₃ / L when exposed to relative humidity RH ₁ , RH ₂ , RH ₃ ,..., T ₁ , t ₂ , t ₃ ,. ₃ is considered as migration damage. Therefore, the integrated ion migration damage rate is given by equation (11).
(T ₁ / L ₁ ) + (t ₂ / L ₂ ) + (t ₃ / L ₃ ) + (11)
Migration life determination is given by equation (12).
_{(T 1 / L 1) +} (t 2 / L 2) + (t 3 / L 3) + ··· = 1 (12)
Substitute the internal temperature and internal relative humidity estimated in Step 2 into the lifetime estimation formula (12) for ion migration, and substitute the dust amount by finding the amount of dust attached per unit time from the amount of dust attached during the measurement period. To do. In this way, ion migration damage is determined per unit time, for example, every hour.

  In step 4 ′, ion migration damage per unit time obtained in step 3 ′ is input to the life diagnosis unit 34. The life diagnosis unit 34 obtains the ion migration integrated damage rate from this, and obtains the time when the ion migration integrated damage rate reaches 1 as the insulation deterioration life as shown in FIG. 9B.

  In step 5, the corrosion life and the insulation deterioration life obtained in steps 4 and 4 'are output on the display screen of the information processing terminal (not shown). Thus, the process of the deterioration diagnosis system 1 is completed.

  As described above, the temperature sensor 12 for measuring the temperature in the control device 3 in which the printed circuit board 10 having the conductive member 9 is accommodated, the humidity sensor 14 for measuring the relative humidity, and the conductive member of this embodiment. According to the deterioration diagnosis system 1 including the corrosion sensor 16 for measuring the amount of corrosion 9, the diagnostic processing device 4, and the outside air environment database 6, the outside air environment data and the control device 3 environment data at the same time as the measurement period From the correspondence relationship, the temperature difference, humidity difference, and period between the outside air environment data and the environment data in the control device 3 are obtained, and these are applied to the past outside air environment data to estimate the future environment data in the control device 3. Thereby, the amount of corrosion whose factors are temperature and relative humidity can be accurately estimated.

  Further, a dust sensor 18 is provided, and the future environmental data in the control device 3 is estimated as in the case of the amount of corrosion, and is estimated from the correlation between the environmental data in the casing recorded during the set period and the progress of insulation deterioration. The progress of insulation deterioration can be accurately estimated from the amount of dust.

  FIG. 10 shows the configuration of the deterioration diagnosis system 1 according to the second embodiment of the present invention. In the present embodiment, the installation environment of the control device 3 is air-conditioned and includes an air-conditioning database 38 instead of the outside air environment database 6 of the first embodiment, and the other configurations are the same as those of the first embodiment. is there. The air conditioning database 38 stores the set temperature and the set relative humidity of the installation environment of the control device 3. Using these set temperature and set relative humidity, the internal temperature and internal relative humidity can be estimated in the same procedure as in the first embodiment.

  As described above, according to the deterioration diagnosis system 1 provided with the air conditioning database 38 instead of the outside air environment database 6 according to the present embodiment, in accordance with the set temperature and humidity of the air conditioning as in the first embodiment. Thus, future changes in internal temperature and internal humidity can be accurately estimated, and the amount of corrosion and insulation deterioration can be accurately estimated.

  As described above, the degradation diagnosis system 1 according to the present embodiment has been described. However, the present invention is not limited to these embodiments, and can be applied by appropriately changing the configuration. For example, in this embodiment, the corrosion sensor 16 and the dust sensor 18 are mounted on the printed circuit board 10 and the measurement is performed. However, the measurement substrate including the corrosion sensor 16 and the dust sensor 18 may be used as a measurement kit. Good. The corrosion sensor 16 may be configured to measure the corrosion amount by a colorimetric method or a cathode reduction method. Further, the dust sensor 18 is measured by “measurement of environmental factors for evaluating the corrosiveness of the atmospheric environment” (JIS-Z-2382) or by collection with an exposure gauze shown in JEIDA-63-2000. You may comprise as follows.

  Further, the diagnosis target of corrosion is not limited to the conductive member, but can be a metal part in the control device 3, for example, a breaker. In that case, the measurement kit may be used.

  In addition, the periodicity between the measured internal temperature and external temperature was obtained by Fourier analysis, but not limited to the method obtained by Fourier analysis, an average feature is obtained by moving average, and the target temperature data and the average feature You may obtain | require by the method of calculating | requiring a periodic feature from a difference. In addition, it is possible to estimate with high accuracy by determining the moving average condition according to the periodic feature by Fourier analysis. Furthermore, other time series data analysis methods may be used.

  Furthermore, when dust is related to corrosion, the amount of dust may be estimated in addition to temperature and humidity, and used for estimation of the amount of corrosion.

(A) is a block diagram of the deterioration diagnostic system of the 1st Example of this invention, (b) is a top view of the printed circuit board accommodated in a control apparatus. It is a processing flow of a deterioration diagnosis system. It is a process of the environment estimation part of a diagnostic processing apparatus. (A) is a graph of internal temperature and external temperature, (b) is a frequency characteristic of internal temperature and external temperature. It is a graph of the absolute humidity inside a control device, and an external absolute humidity The process for estimating the amount of corrosion in the environment estimation unit is shown. (A) is a figure which shows the actual value and estimated value of a silver corrosion amount, (b) is a related figure of a corrosion life and elapsed years. It is a figure which shows the process process about estimation of the insulation degradation of an environment estimation part. (A) is a figure which shows the relationship between an ion migration lifetime, relative humidity, and the amount of dust, (b) is a relationship figure of an ion migration lifetime and elapsed years. It is a process of the environment estimation part of the deterioration diagnostic system concerning the 2nd Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Degradation diagnosis system 2 Environmental measurement apparatus 4 Diagnosis processing apparatus 6 Outside air environment database 9 Conductive member 10 Printed circuit board 12 Temperature sensor 14 Humidity sensor 16 Corrosion sensor 18 Dust sensor 17 Integrated corrosion damage rate 18 Ion migration integrated damage rate 30 Environment estimation part 32 Damage estimation unit 34 Life diagnosis unit 36 Corrosion database 38 Air conditioning database

Claims (5)

A temperature sensor for measuring a temperature in a casing in which a printed circuit board on which an electronic or electrical component including a conductive member to be diagnosed is mounted, a humidity sensor for measuring the humidity in the casing, and the diagnostic target Recording the corrosion sensor for measuring the corrosion amount, the environmental data in the casing composed of the temperature and humidity in the casing measured by each sensor, and the corrosion data to be diagnosed for a set period, and the recorded in the casing A diagnosis processing device that estimates a future corrosion amount of the diagnosis target based on environmental data and the corrosion data and performs a deterioration diagnosis, and an outside air in which outside air environment data including past temperature and humidity outside the housing is recorded Environmental database and
The diagnostic processing device obtains a correlation between the environmental data in the casing and the corrosion data recorded during the setting period, and obtains a correspondence between the outside air environmental data and the environmental data in the casing during the setting period, Control that estimates future environmental data in the casing based on the correspondence and the past outside air environmental data, and estimates the future corrosion amount of the diagnosis target from the estimated environmental data in the casing and the correlation Equipment deterioration diagnosis system. A temperature sensor for measuring a temperature in a housing in an air-conditioned atmosphere containing a printed circuit board on which an electronic or electrical component including a conductive member to be diagnosed is mounted; a humidity sensor for measuring the humidity in the housing; and The corrosion sensor for measuring the corrosion amount of the diagnosis target, the environmental data in the casing composed of the temperature and humidity in the casing measured by each sensor, and the corrosion data of the diagnosis target are recorded for a set period, and the recorded A diagnostic processing device that estimates a future corrosion amount of the diagnosis target based on the environmental data in the housing and the corrosion data and performs a deterioration diagnosis, and an air conditioner in which air conditioning data including the set temperature and humidity of the air conditioner is recorded With a database,
The diagnostic processing device obtains a correlation between the environmental data in the casing and the corrosion data recorded during the set period, and based on the correspondence between the environmental data in the casing and the air conditioning data, A deterioration diagnosis system for a control device that estimates environmental data and estimates a future corrosion amount of the diagnosis target from the estimated environmental data in the housing and the correlation. A temperature sensor for measuring a temperature in a housing in which a printed circuit board on which an electronic or electrical component including a conductive member to be diagnosed is mounted, a humidity sensor for measuring the humidity in the housing, and the diagnosis target A dust sensor that measures the amount of dust adhering, and internal environment data and dust data that are measured by each sensor and that includes temperature and humidity inside the housing are recorded for a set period, and the recorded internal environment data A diagnosis processing device for diagnosing insulation deterioration of the diagnosis object based on the dust data, and an outside air environment database in which outside air environment data consisting of past temperature and humidity outside the housing is recorded,
The diagnostic processing device obtains a correlation between the environmental data in the casing recorded in the setting period and the progress of the insulation deterioration, and a correspondence relationship between the outside air environmental data and the environmental data in the casing in the setting period And the future environmental data in the housing is estimated based on the correspondence and the past outside air environment data, and the future insulation deterioration of the diagnosis target is estimated from the estimated environmental data in the housing and the correlation. A deterioration diagnosis system for a control device that estimates the degree of progress. A temperature sensor for measuring a temperature in a housing in an air-conditioned atmosphere containing a printed circuit board on which an electronic or electrical component including a conductive member to be diagnosed is mounted; a humidity sensor for measuring the humidity in the housing; and A dust sensor for measuring the amount of dust adhering to the diagnosis object, and environmental data and dust data in the housing composed of the temperature and humidity in the housing measured by each sensor are recorded for a set period, and the recorded housing A diagnostic processing device for diagnosing insulation deterioration of the diagnosis target based on in-vivo environmental data and the dust data; and an air conditioning database in which air conditioning data including the set temperature and humidity of the air conditioning is recorded,
The diagnostic processing device obtains a correlation between the environmental data in the casing recorded during the set period and the progress of the insulation deterioration, and based on the correspondence between the environmental data in the casing and the air conditioning data, A deterioration diagnosis system for a control device that estimates the environmental data in the housing and estimates a progress degree of future insulation deterioration of the diagnosis target from the estimated environmental data in the housing and the correlation.   The deterioration diagnosis system for a control device according to claim 1, wherein the corrosion sensor is an electrical resistance type corrosion sensor.

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