WO2022064915A1

WO2022064915A1 - Electrostatic capacitance measurement device and electrostatic capacitance measurement program

Info

Publication number: WO2022064915A1
Application number: PCT/JP2021/030536
Authority: WO
Inventors: 不二雄黒川
Original assignee: イサハヤ電子株式会社
Priority date: 2020-09-24
Filing date: 2021-08-20
Publication date: 2022-03-31
Also published as: JP7450984B2; JPWO2022064915A1

Abstract

An electrostatic capacitance measurement device and electrostatic capacitance measurement program are provided which enable measuring at an arbitrary timing the electrostatic capacitance of an electric component with capacitance.　This electrostatic capacitance measurement device 10 of an electric component is provided with: an output instruction means 11 which changes to simple pulses the output to the electric component with capacitance; a differentiation processing means 13 which generates symbol data which, when the derivative value obtained by taking the derivative of the output once is positive, is assigned a symbol set to "1" and, when negative, is assigned a symbol set to "0"; and a calculation means 15 which, from the symbols indicated by the symbol data, calculates the total number of "1"s as the degree of fluctuation of the waveform with respect to transition change, and calculates the fluctuation value corresponding to the electrostatic capacitance value.

Description

Capacitance measuring device and capacitance measuring program

The present invention relates to a capacitance measuring device and a capacitance measuring program that measure the degree of abnormality of a capacitive electric component and predict an abnormality.

In electrical components with capacitance, for example, electrolytic capacitors, the electrolytic solution impregnated in the insulating paper permeates the sealing rubber due to aging and leaks to the outside to evaporate, so-called static capacity loss. A decrease in electric capacity occurs. The evaporation rate of this electrolytic solution doubles when the ambient temperature rises by 10 degrees. Therefore, every time the temperature rises by 10 degrees, the life is reduced by half. In addition, electrical components may suddenly break and become insulated.
Patent Document 1 describes a technique for detecting an abnormality in an electric component having such a capacitance.

When the electric vehicle power supply device described in Patent Document 1 includes a filter capacitor and a passive filter circuit, the return terminal of the passive filter circuit is connected between the current sensor and the return line of the train line. Then, the abnormality detector detects the frequency of the signal obtained by differentiating the current signal during the period when charging or discharging is performed between the train line and the filter capacitor and the capacitor of the passive filter circuit, and the frequency of the differentiated signal is the upper limit. When the threshold is not reached, a decrease in the capacitance of the capacitor is detected.

Japanese Unexamined Patent Publication No. 2010-252434

However, in the power supply device for an electric vehicle described in Patent Document 1, the presence or absence of an abnormality is detected during the period when the filter capacitor and the capacitor of the passive filter circuit are charged or discharged, so that the abnormality is found. Not only is the detection limited to that period, but it is also difficult to predict when charging or discharging will occur, so the timing and period of measurement cannot be specified.

Therefore, an object of the present invention is to provide a capacitance measuring device and a capacitance measuring program capable of measuring the capacitance of an electric component having a capacitance at an arbitrary timing.

The capacitance measuring device for an electric component of the present invention has an instruction means for instructing a transient change of an output to an electric component having a capacitive property, and the derivative when the derivative value obtained by differentiating the output a predetermined number of times is positive. A differential processing means for generating symbol data to which one or more symbols indicating a positive side corresponding to a value are assigned and one or more symbols indicating a negative side corresponding to the differential value are assigned in the case of a negative value, and the symbol data. It is characterized by having a calculation means for calculating the fluctuation value corresponding to the capacitance value by calculating the fluctuation degree of the waveform with respect to the transient change from each symbol indicated by.

Further, in the capacitance measurement program of the electric component of the present invention, the instruction means for instructing the computer to transiently change the output to the electric component having capacitance, the differential value obtained by differentiating the output a predetermined number of times is positive. A differential processing means for generating symbol data in which one or more symbols indicating the positive side corresponding to the differential value are assigned in the case and one or more symbols indicating the negative side corresponding to the differential value are assigned in the negative case. It is characterized in that it functions as a calculation means for calculating the fluctuation value corresponding to the capacitance value by calculating the fluctuation degree of the waveform with respect to the transient change from each symbol indicated by the symbol data.

According to the present invention, when the indicating means instructs the transient change of the output to the electric component having capacitance, the transient waveform appears by the electric component in the transiently changed output. This output is differentiated by the differential processing means, and when the differential value is positive, one or more symbols indicating the positive side corresponding to the differential value are assigned, and when the differential value is negative, the negative side corresponding to the differential value is indicated 1. Generate symbol data to which the above symbols are assigned. The capacitance value can be estimated by the calculation means calculating the fluctuation degree of the waveform with respect to the transient change from each symbol indicated by the symbol data as the fluctuation value corresponding to the capacitance value.
Therefore, according to the present invention, the indicating means can measure the capacitance value at an arbitrary timing by transiently changing the output to the electric component.

It is possible to provide a determination means for determining an abnormality based on the fluctuation value.
By doing so, the capacitance value can be measured at an arbitrary timing, and deterioration or failure can be detected even during operation.

The instruction means may instruct the output to be reduced in the form of a single pulse as the transient change. If the output of a single pulse increases, there is concern about damage to the electrical components, but since the output is reduced, damage to the electrical components can be suppressed.

It is possible to provide a predicting means for predicting an abnormality occurrence time from the capacitance value by accumulating the capacitance value at predetermined intervals.
In order to predict the time when an abnormality occurs from the capacitance value accumulated at predetermined intervals, it is possible to prepare for replacement of electrical parts in advance.

The calculation means indicates the degree of fluctuation of the waveform from the symbol data, either or both of the total number for each positive symbol and the total number for each negative symbol, within a predetermined time from the occurrence time of the transient change. It can be counted as a variable value.

Further, the calculation means sequentially counts the number of consecutive symbols of the same symbol from the symbol data within a predetermined time from the occurrence time of the transient change, and squares the sum of the squares of each of these symbols. Can be calculated as a fluctuation value indicating the degree of fluctuation of the waveform.

Further, the differential processing means generates symbol data as the symbol, to which 1 is assigned when the sign of the differential value is positive and 0 is assigned when the sign of the differential value is negative, and the arithmetic means is the transient change. Within a predetermined time from the time when It can be calculated as a value.

Further, the calculation means may count the number of blocks from the symbol data to the change of the symbol within a predetermined time from the occurrence time of the transient change, and calculate the total number of blocks as a variable value. can.

The symbol data generated by the differential processing means may be provided with noise removing means for removing noise shorter than a predetermined length by performing shrinkage processing and expansion processing. Symbol data is generated based on the differential value by differentiation, but the differentiation may react sensitively to the transient waveform and appears as noise in the symbol data. However, accurate symbol data can be obtained by removing noise shorter than a predetermined length by performing shrinkage processing and expansion processing on the symbol data.

The differential processing means may not be symbolized by setting a predetermined range centered on the differential value 0 as a dead zone.
Noise is likely to occur at the maximum point or the minimum point where the differential value becomes 0. Therefore, it is possible to suppress the generation of noise by setting a predetermined range centered on the differential value 0 as a dead zone and not symbolizing it.

According to the present invention, it is possible to detect deterioration or failure even during operation by instructing the instruction means to transiently change the output to the electric component at an arbitrary timing. Therefore, the present invention can detect secular variation and abnormality of an electric component having a capacitance at an arbitrary timing.

It is a figure which shows the structure of the capacitance measuring apparatus which concerns on embodiment of this invention, and a converter. It is a flowchart for demonstrating the abnormality detection method by the capacitance measuring apparatus shown in FIG. It is a figure for demonstrating the operation of the differential processing means and the calculation means of the capacitance measuring apparatus shown in FIG. It is a diagram for explaining that the symbol data is contracted and expanded to remove noise, (A) is a diagram showing a state in which noise is removed, and (B) is restored to the original data because it is not noise. It is a figure which shows the state. It is a figure for demonstrating that a calculation means calculates a variation value based on a symbol data, and (A) is a figure for demonstrating that the total number of "1" and "0" is counted, (B). ) Is a diagram for explaining that each bit from the LSB to the MSB is exchanged and quantified, and (C) is a diagram for explaining that the number of blocks is counted. It is a graph for explaining that the capacitance value is obtained by the clustering method, (A) is a graph in which the capacitance value corresponding to temperature is plotted, and (B) corresponds to output capacity (load power). A graph in which the capacitance value is plotted, and (C) is a graph in which the capacitance value with respect to time is plotted and an approximate curve is drawn. It is a table which shows each condition of a simulation. It is a graph for explaining the simulation result.

The capacitance measuring device according to the embodiment of the present invention will be described with reference to the drawings.
The capacitance measuring device 10 according to the embodiment of the present invention shown in FIG. 1 is a static output capacitor _CO which is an example of an electric component having a capacitance (capacitance) of a converter 100 which is an example of a power conversion device. It measures the electric capacity and detects abnormalities in a state where the specified operable value is deviated, such as capacity loss, capacity reduction failure, and insulation failure.
Here, first, the converter 100 will be described. The converter 100 inputs a three-phase alternating current (Van, Vbn, Vcn) which is a power source P, and outputs a voltage V _DC to the load R.

[Configuration of converter 100]
The converter 100 has a first arm 110, a second arm 120, and a third arm 130.
The first arm 110 to the third arm 130 correspond to the first upper arm 111, the second upper arm 121 and the third upper arm 131, and the first upper arm 111 to the third upper arm 131, respectively. The arm 112, the second lower arm 122, and the third lower arm 132 are connected in series, respectively.

The first upper arm 111 to the third upper arm 131 and the first lower arm 112 to the third lower arm 132 are examples of switching elements in which a signal from an output indicating means of a target voltage described later is connected to a gate terminal. It is formed by an N-channel MOSFET.
A coil L for noise reduction is connected in series between the connection point between the first upper arm 111 to the third upper arm 131, the first lower arm 112 to the third lower arm 132, and the power supply P. ..

The first arm 110 to the third arm 130 are instructed by the control means 140 so that the output voltage (voltage V _DC ) becomes the target voltage.
The control means 140 controls switching between the first arm 110, the second arm 120, and the third arm 130 by PWM (Pulse Width Modulation).

[Configuration of Capacitance Measuring Device 10]
Next, the configuration of the capacitance measuring device 10 will be described with reference to the drawings. The capacitance measuring device 10 is a computer on which a capacitance measuring program is operated.
The capacitance measuring device 10 includes an output indicating means 11, an AD conversion means 12, a differential processing means 13, a noise removing means 14, a calculation means 15, a determination means 16, a notification means 17, and a clustering means 18. And the prediction means 19.

The output instruction means 11 (instruction means) instructs the control means 140 to change the output to the electric component having capacitance into a single pulse shape as a transient change.
The AD conversion means 12 converts the input output voltage (voltage V _DC ) from an analog signal to a digital signal.
The differential processing means 13 assigns one or more symbols indicating the positive side corresponding to the differential value when the differential value obtained by differentiating the output is positive, and one or more symbols indicating the negative side corresponding to the differential value when the output is negative. Generate symbol data to which the symbol of is assigned.

The noise removing means 14 removes noise shorter than a predetermined length by performing shrinkage processing and expansion processing on the symbol data generated by the differentiation processing means 13.
The calculation means 15 calculates the degree of fluctuation of the waveform with respect to the transient change from each symbol indicated by the symbol data, and calculates the fluctuation value corresponding to the capacitance value. The capacitance value corresponding to the variable value is stored in a storage means (not shown).
The determination means 16 determines an abnormality when the fluctuation value or the capacitance value by the calculation means 15 is equal to or greater than or equal to the threshold value.
When the determination means 16 determines the abnormality, the notification means 17 notifies the administrator of the abnormality.
The clustering means 18 clusters a data group in which the target voltage, the fluctuation value corresponding to the target voltage, and the threshold value are collected as transient characteristic data.
The predicting means 19 accumulates the capacitance value at predetermined intervals and predicts the time of occurrence of the abnormality from the capacitance value.

[Operation and usage of the capacitance measuring device 10]
The operation and the usage state of the capacitance measuring device 10 of the electric component according to the embodiment of the present invention configured as described above will be described with reference to the drawings.
In this embodiment, it will be described that the capacity loss of the output capacitor _CO shown in FIG. 1 is detected.
First, the AD conversion means 12 shown in FIG. 1 digitally converts an output voltage (voltage _VDC ) and outputs measurement data (see step S10 shown in FIG. 2).
The output instruction means 11 instructs the control means 140 to indicate the target voltage so as to reduce the output voltage in the form of a single pulse (see step S20).

As shown in FIG. 3, the differential processing means 13 relates to an output voltage (voltage V _DC ) from a time t1 at which the output voltage drops to an arbitrary time t2, which is within a predetermined time from the generation time of the single pulse P. The measurement data is differentiated to generate symbol data S [n] (see step S30).

When the differential value obtained by differentiating the output is positive, the differential processing means 13 sets the differential value to three types of values of "0", "1", and "2" indicating the positive side for each predetermined value, or "1". It can be a value in the range of "3" or a value of "1" to "4" or more. Further, in the case of a negative value, the differential value may be set to two types of values, "-1" and "-2" indicating the negative side for each predetermined value, or a value in the range of "-1" to "-3". , It can be a value of "-1" to "-4" or less. That is, the positive side and the negative side can be multivalued.
Further, in the example shown in FIG. 3, the differential processing means 13 assigns "1" as a symbol depending on whether the sign of the differential value is positive or 0, and assigns "0" when the sign is negative. Symbol data can be generated. In this embodiment, two types of symbols, "1" and "0", are used.

Next, the noise removing means 14 removes noise by performing shrinkage processing and expansion processing on the symbol data (see step S40). For example, in the symbol data shown in FIG. 4A, one symbol “1” is sandwiched between the three symbols “0”. The noise removing means 14 replaces "1" with "0" by the shrinkage treatment. Then, by expanding the symbol data in which all are "0", all the symbol data remains "0" and becomes the symbol data of the original length.

Further, in the symbol data shown in FIG. 4B, three symbols "1" are sandwiched between the three symbols "0". This "1" is not noise.
Therefore, even if the noise removing means 14 shrinks three consecutive "1" s, the symbol data in which one "1" remains and the "1" becomes one is expanded to "1". 1 ”can be used as symbol data restored to three consecutive states.

Here, in addition to removing noise by the noise removing means 14, the differential value obtained by differentiating the output voltage becomes very small at the maximum point and the minimum point, and noise due to fluctuations such that the sign of the differential value is frequently switched. Can be removed by the differential processing means 13.

For example, the value may not be changed unless 1 or 0 continues with the same value several times. Further, it is possible to provide a dead zone in the vicinity of the differential value 0 (a predetermined range centered on the differential value 0) so as not to be symbolized (quantified). Further, a third value is assigned to the vicinity where the differential value becomes 0. In the above description, if the sign is positive and the differential value is 0, it is set to "1", and if the sign is negative, it is set to "0". +1 ”, if the absolute value of the differential value is less than the predetermined value, it is“ 0 ”, and if the sign is negative and the differential value is less than the predetermined value, it is“ -1 ”.
By doing so, it is possible to remove noise that tends to occur in the vicinity of the maximum value and the minimum value of the differential value.

Next, the calculation means 15 calculates the degree of fluctuation of the output voltage waveform with respect to a single pulse from each symbol indicated by the symbol data, and calculates the fluctuation value (see step S50).
For example, the calculation means 15 indicates the degree of fluctuation of the waveform from the symbol data, either or both of the total number of the positive side symbols and the total number of the negative side symbols within a predetermined time from the generation time of the single pulse. It can be counted as a variable value.

In the initial state, when the output voltage at an arbitrary time from the time when the output voltage drops is "000111111000" as shown in FIG. 5A, the total number of "1" is 6. Yes, the total number of "0" is 3 + 3 = 6.
In the capacity change state where the capacity of the output capacitor _CO (see FIG. 1) is lost, it becomes as shown in FIG. 5 (A) as "001111001101". In this case, the total number of "1" is 4 + 2 + 1 = 7, and the total number of "0" is 2 + 2 + 1 = 5.
Then, the calculation means 15 calculates the total number 7 of "1" or the total number 5 of "0" to obtain a fluctuation value, and reads the capacitance value corresponding to this fluctuation value from the storage means to obtain the capacitance value. Can be estimated (see step S60).

The determination means 16 can determine that the deterioration occurs when the total number of "1" increases from the predetermined value (first threshold value), and determines that the deterioration occurs when the total number of "0" decreases from the predetermined value (first threshold value). can do. Moreover, it can be judged by both of these conditions. Further, the determination means 16 can determine that the capacitance value is abnormal when the capacitance value indicates an abnormal value (see step S70).

Further, the calculation means 15 sequentially counts the number of consecutive symbols of the same symbol from the symbol data, and calculates the value obtained by square rooting the sum of the squares of the numbers of these symbols as the fluctuation value indicating the degree of fluctuation of the waveform. Can be done (see step S50). This indicates the distance from the origin when the number of symbols is expressed as n-dimensional coordinates.

In the initial state, if the output voltage at an arbitrary time from the time when the output voltage drops is "0001111111000", √ (3 ² + 6 ² + 3 ² + 0 + 0 + 0) = √54 ≒ 7.35. It becomes.
In the capacity change state where the capacity of the output capacitor _CO (see Fig. 1) is lost, when it becomes "001111001101", √ (2 ² +4 ² +2 ² +2 ² + 1 ² + 1 ² ) = √30 ≒ 5.48 It becomes.
Then, the calculation means 15 calculates the distance from the origin when the number of symbols is expressed as n-dimensional coordinates and uses it as a fluctuation value, and reads out the capacitance value corresponding to this fluctuation value from the storage means, thereby statically. The capacitance value can be estimated (see step S60).

The determination means 16 can determine that the deterioration has occurred when the distance from the origin decreases from a predetermined value (second threshold value). Further, the determination means 16 can determine that the capacitance value is abnormal when the capacitance value indicates an abnormal value (see step S70).

The calculation means 15 can perform calculation as a variable value converted into a decimal number or a hexadecimal number by exchanging each bit of the symbol data from LSB to MSB from MSB to LSB (see step S50). The fluctuation value can be an n-ary number with n being 3 or more.

In the initial state, when the output voltage at an arbitrary time from the time when the output voltage drops is "000111111000" as shown in FIG. 5 (B), when the MSB is replaced from the LSB, " 01111111000 ". Therefore, when this symbol data is converted into a decimal number, it becomes 504.
In the capacity change state where the capacity of the output capacitor _CO (see FIG. 1) is lost, it becomes "001111001101" as shown in FIG. 5B, and when the MSB is replaced from the LSB, it becomes "101100111100". Converted to decimal, it becomes 2876.
Then, the calculation means 15 can estimate the capacitance value by reading the capacitance value corresponding to the variable value in which the LSB to the MSB are exchanged from the storage means (see step S60).

The determination means 16 can determine that the value has deteriorated when the decimal value (variation value) increases from a predetermined value (third threshold value). Further, the determination means 16 can determine that the capacitance value is abnormal when the capacitance value indicates an abnormal value (see step S70).
In addition to converting the symbol data to decimal numbers, it can be a numerical value of ternary numbers or higher.

The calculation means 15 can count the number of blocks until the symbol changes, and can calculate the total number of blocks as a variable value (see step S50).

In the initial state, when the output voltage at an arbitrary time from the time when the output voltage drops is "000111111000" as shown in FIG. 5 (C), it is a block until the symbol changes. Since it can be divided into "000", "111111", and "000", the total number is 3 because the block of "0" is 2 and the block of "1" is 1.
In the capacity change state where the capacity of the output capacitor _CO (see FIG. 1) is lost, when it becomes "001111001101" as shown in FIG. 5 (C), the block until the symbol changes is "00". It can be divided into "1111", "00", "11", "0", and "1", and the total number is 3 because the block of "0" is 3 and the block of "1" is 3. Is 6.
Then, the calculation means 15 calculates the total number of blocks to obtain a variable value, and can estimate the capacitance value by reading the capacitance value corresponding to the variable value from the storage means (see step S60). ..

The determination means 16 can determine that the value has deteriorated when the value of the number of blocks (variation value) increases from a predetermined value (fourth threshold value). Further, the determination means 16 can determine that the capacitance value is abnormal when the capacitance value indicates an abnormal value (see step S70).

When the determination means 16 detects deterioration, the notification means 17 notifies the administrator (see step S80). This notification may be displayed on the screen or may be notified by sound. Further, the notification means 17 may notify via a network (not shown). Further, the notification means 17 can notify the capacitance value (see step S90).

The predicting means 19 can predict the transition of the capacitance value by accumulating the capacitance value (fluctuation value) at predetermined intervals in the storage means and obtaining an approximate expression, so that it is possible to predict an abnormality. (See step S100). Therefore, since the replacement time of the output capacitor _CO due to deterioration can be predicted, it is possible to schedule replacement preparations. This prediction can be estimated by AI (artificial intelligence) based on statistical data such as output voltage, output current, load, and ambient environment, in addition to obtaining an approximate expression.

In this way, the capacitance measuring device 10 shown in FIG. 1 instructs the control means 140 that the output indicating means 11 changes the output voltage of the converter 100 to the output capacitor _CO in a single pulse shape. Therefore, it is possible to calculate the fluctuation value of the output capacitor _CO and measure the capacitance value at an arbitrary timing, and it is possible to detect capacity loss or failure.

Further, in the power supply device for an electric vehicle described in Patent Document 1, the frequency is calculated by detecting the zero cross where the signal obtained by differentiating the current signal intersects the zero level, but the detection of the zero cross by the differentiation is pinpoint. It is difficult to accurately grasp the change because it observes various changes and there is a risk of erroneous detection of noise.
However, in the capacitance measuring device 10 according to the present embodiment, since the output voltage is symbolized according to the sign of the differentiated differential value, the transient waveform can be continuously observed. Therefore, it is possible to accurately grasp the capacitance change of the output capacitor _CO .

In addition, signal processing is performed by replacing the output voltage with a code such as a number such as "1" and "0", a character, a symbol, etc., and digitizing or symbolizing (encoding) it with a positive or negative code of the differential value obtained by differentiating the output voltage. Many methods used in the above can be applied, and changes in parts such as electrolytic capacitors of the output filter of the power converter can be easily identified, so that abnormalities such as defects, failures, and deterioration can be determined. be able to.

In the determination based on the first threshold value to the fourth threshold value, the transient characteristics are not always constant, but are varied due to differences in parameters such as various load conditions and device variations.
Since the data of these transient characteristics can collect the target voltage, the fluctuation value corresponding to the target voltage, and the threshold value as numerical values, the clustering means 18 shown in FIG. 1 can collect a group of data scattered for each capacitance based on these. By clustering, it is possible to identify changes due to capacitor failures, aging, etc. of the electrical components to be monitored even under varying conditions.

Here, the identification of failure and secular variation by clustering by the clustering means 18 will be described in detail.
When the capacitance value is estimated by the arithmetic means 15, it is predicted by clustering it.
Clustering can be performed by various methods.
As the clustering method, for example, hierarchical clustering (Ward's method, group average method, shortest distance method, longest distance method, etc.), partition clustering (kmeans method, kmedians method, etc.) and the like can be used.
The clustering means 18 and the predicting means 19 predict failures and secular changes based on these clustering methods.

A temperature sensor that measures the temperature of the converter 100 that is the monitored device is provided, and when the output capacity (load power) is unknown, it changes over time (aging) from the measured temperature and the estimated capacitance value. It is also possible to predict the decrease in capacitance value due to (change).

For example, in the graph shown in FIG. 6A, the capacitance value corresponding to the temperature measured in year X is plotted. Further, in this graph, the capacitance value for each temperature measured in the next year, X + 1, is plotted. This measurement period can be arbitrarily changed, for example, every 3 months or 6 months.
The clustering means 18 clusters the estimated values for these measured values by, for example, a group average method or the like to obtain the median value. Also, instead of the median, the mean or median can be the center of the cluster.

Next, a case of measuring the output capacity (load power) of the converter 100 as the monitored device will be described. In this case, the temperature is unknown.
In the graph shown in FIG. 6B, the capacitance values corresponding to the output capacitance (load power) measured in the year X and the year X + 1 are plotted.
The clustering means 18 calculates the secular variation based on the clustering method. The estimated values for these measured values are clustered by the group average method or the like to obtain the median value. Further, as described in the graph of FIG. 6A, the average value or the center value can be used instead of the median value.

In this way, when the capacitance value for each cluster in the graphs shown in FIGS. 6A and 6B is calculated, the prediction means 19 can predict the capacitance value.
The prediction means 19 plots the median value, the average value, and the center value of the capacitance values calculated in this way for each year to obtain a function showing the approximate curve of FIG. 6C.
From the function showing this approximate curve, it is predicted that it will fall below the specified value in years or months by looking ahead of the approximate curve, or by looking at the difference in value or slope from the standard curve. can. Therefore, since it is possible to predict future changes in the capacitance value, it is possible to predict deterioration of electrical components having capacitance.

If the calculation means 15 calculates the capacitance value for each time, the prediction means 19 is a function showing an approximate curve from the capacitance value for each time as shown in the graph shown in FIG. 6 (C). Can be calculated. It can be predicted by the clustering means 18 without using clustering.
At this time, the approximate curve is obtained after excluding the variation element with a filter (extracting the basic element with a low-pass filter or a Kalman filter) based on the approximate curve. By doing so, the accuracy of the approximate curve can be improved.

Further, in the case of the graph shown in FIG. 6B, it is also possible to extract only the values at the same output power and perform clustering. By doing so, it is possible to eliminate the influence that the vibration cycle at the time of step change changes depending on the magnitude of the load power.

In the graph shown in FIG. 6 (A), the capacitance value was determined based on the distribution of two parameters, the temperature and the capacitance value, and in the graph shown in FIG. 6 (B), the output capacitance (load power). For example, parameters such as ambient temperature, circuit parameters, input voltage, input current, output voltage, and output current may be clustered as n-dimensional data.

[simulation]
The data of the initial response was taken by the converter 100 shown in FIG. 1, and the difference between 100% and 80% of the output capacitor _CO was simulated.
The verification method verifies the characteristics when the output voltage target value of the converter 100 is subjected to an internal response in which the output voltage target value changes from 400 V to 300 V by 100 μs. Further, the simulation was performed under each condition shown in FIG.

In the simulation, a single pulse was generated for the output voltage when the sampling frequency was set to 5 KHz and the rated capacity of the output capacitor was reduced by 5% from 3300 μF to 5% to 40%, t1 = 0.4 seconds. From the symbol data from t2 = 0.47 seconds, the number of "1" whose sign of the differential value is positive and whose differential value is 0 is counted. In addition, the number of "0" in which the sign of the differential value is negative is also counted.

As a result, as shown in the graph of FIG. 8, in the initial state, "1" is 220, "0" is 130, "1" is 220 when 5% decrease, "0" is 130, and "1" is 10% decrease. 223, "0" is 127, "1" is 228 for a 15% decrease, "0" is 122, "1" is 231 for a 20% decrease, "0" is 119, and "1" is 234 for a 25% decrease. "0" is 116, "1" is 236 for a 30% decrease, "0" is 114, "1" is 241 for a 35% decrease, "0" is 109, and "1" is 242 for a 40% decrease, "0". Was 108.

As can be seen from this, when the number of capacitors is reduced, the total number of "1" increases. Then, the arithmetic means 15 associates the total number of "1" with the capacitance value in advance and stores it in a storage means (not shown), so that the value of the output capacitor is obtained from the total number of "1" obtained from the differential value for a certain period. (Capacitance value) can be inferred.
Using this result, when the capacitance value (fluctuation value) at predetermined intervals is stored in the storage means, the transition is predicted based on the fluctuation tendency of the capacitance value, so that the power converter remains in operation. It is possible to predict and detect abnormalities such as changes over time in capacitors.

In the present embodiment, the detection of deterioration in which the capacity of the output capacitor _CO of the converter 100 shown in FIG. 1 gradually disappears with the passage of time causes a capacity loss has been described. However, in the present invention, the capacity suddenly increases. It is possible to detect even a decrease in failure.
Further, although the output capacitor _CO of the converter 100 has been described as an example, it is possible to detect an abnormality in a battery by applying the present invention to a charging circuit even for an electric component having a capacitance, for example, a battery. ..

Further, in the present embodiment, the output voltage of the converter 100 is changed in the form of a single pulse to make a transient change, but if the voltage, current, electric power, etc. can be changed transiently, the transient change will occur. , The output indicating means 11 shown in FIG. 1 may indicate an internal response, a step response, or a change due to a sine wave.
Further, the output indicating means 11 instructs the output indicating means 11 to decrease the voltage as a single pulse, but if there is no problem, the single pulse that increases the voltage is instructed so that the voltage is not damaged even if the voltage increases. May be good.

Further, in the present embodiment, the number of differentiations is one, but symbol data may be generated based on the value when the output is differentiated a plurality of times.
Further, since the converter 100 functions as a constant voltage source, the output is designed to measure the output voltage, but the output can also be used as electric power. Further, if the converter functions as a constant current source, the output can be an output current or electric power.

Further, since the power conversion device measures the output voltage and the output current for the control means for controlling the PID in both the constant voltage source and the constant current source, the capacitance value is determined by the output voltage and the output current. The capacitance measuring device 10 according to the present embodiment for measuring can be realized without adding a new circuit for measuring the output voltage and the output current.

Since the present invention can measure the capacitance value of a capacitive electric component even during operation, it is suitable for an electric device using a capacitor, a battery, etc., and detects an abnormality in an output filter (output capacitor) of a power converter. Best for.

10 Capacitance measuring device 11 Output instruction means 12 AD conversion means 13 Differentiation processing means 14 Noise reduction means 15 Calculation means 16 Judgment means 17 Notification means 18 Clustering means 19 Prediction means 100 Converter 110 First arm 111 First upper arm 112 First 1 Lower arm 120 2nd arm 121 2nd upper arm 122 2nd lower arm 130 3rd arm 131 3rd upper arm 132 3rd lower arm 140 Control means _{CO Output} capacitor L Coil P Power supply R Load

Claims

An instruction means for instructing a transient change in output to a capacitive electric component,
When the differential value obtained by differentiating the output a predetermined number of times is positive, one or more symbols indicating the positive side corresponding to the differential value are assigned, and when the differential value is negative, one or more indicating the negative side corresponding to the differential value is assigned. Differentiation processing means to generate symbol data to which the symbol of
A capacitance measuring device provided with a calculation means for calculating a fluctuation degree of a waveform with respect to a transient change from each symbol indicated by the symbol data and calculating a fluctuation value corresponding to the capacitance value.
The capacitance measuring device according to claim 1, further comprising a determining means for determining an abnormality based on the fluctuation value.
The capacitance measuring device according to claim 1 or 2, wherein the instruction means is instructed to reduce the output in a single pulse shape as the transient change.
The capacitance measuring device according to any one of claims 1 to 3, further comprising a predicting means for predicting an abnormality occurrence time from the capacitance value by accumulating the capacitance value at predetermined intervals.
The calculation means indicates the degree of fluctuation of the waveform from the symbol data, either or both of the total number of the positive side symbols and the total number of the negative side symbols within a predetermined time from the occurrence time of the transient change. The capacitance measuring device according to any one of claims 1 to 3, which is counted as a variable value.
The calculation means sequentially counts the number of consecutive symbols of the same symbol from the symbol data within a predetermined time from the occurrence time of the transient change, and squares the sum of the squares of these symbols. The capacitance measuring device according to any one of claims 1 to 3, which is calculated as a fluctuation value indicating a degree of fluctuation of a waveform.
The differential processing means generates symbol data as the symbol to which 1 is assigned when the sign of the differential value is positive and 0 is assigned when the sign of the differential value is negative.
The arithmetic means replaces each bit of the symbol data from LSB to MSB from MSB to LSB within a predetermined time from the occurrence time of the transient change, and converts n into an n-ary number having 3 or more as a variable value. The capacitance measuring device according to any one of claims 1 to 3 for calculation.
Any of claims 1 to 3 in which the calculation means counts the number of blocks from the symbol data to the change of the symbol within a predetermined time from the occurrence time of the transient change, and calculates the total number of blocks as a variable value. Capacitance measuring device according to the above section.
The capacitance according to any one of claims 1 to 7, further comprising a noise removing means for removing noise shorter than a predetermined length by performing shrinkage processing and expansion processing on the symbol data generated by the differential processing means. Capacitance measuring device.
The capacitance measuring device according to any one of claims 1 to 8, wherein the differential processing means does not symbolize a predetermined range centered on a differential value of 0 as a dead zone.
Computer,
Instructional means for instructing transient changes in output to capacitive electrical components,
When the differential value obtained by differentiating the output a predetermined number of times is positive, one or more symbols indicating the positive side corresponding to the differential value are assigned, and when the differential value is negative, one or more indicating the negative side corresponding to the differential value is assigned. Differentiation processing means to generate symbol data to which the symbol of
A capacitance measurement program that calculates the degree of fluctuation of the waveform with respect to transient changes from each symbol indicated by the symbol data and functions as a calculation means for calculating the fluctuation value corresponding to the capacitance value.