Patent Description:
Noise reduction structures for transformers are conventionally known. For example, <CIT> (PTL <NUM>) discloses a configuration in which, in a transformer noise reduction structure including a soundproof wall surrounding a transformer body, a resonant sound absorbing structure that resonates with a specific frequency of noise generated when the transformer is in operation is installed on the floor surface within the closed space formed by the outer surface of the transformer and the inner surface of the soundproof wall. <CIT> (PTL <NUM>) discloses a configuration in which a weight for noise reduction is attached to part of a reinforcing member attached to the side surface of a transformer tank to make the frequency of noise and the resonance frequency of the reinforcing member different from each other and thus reduce noise. <CIT> discloses a known power equipment inspection apparatus for a transformer, generating abnormality information and outputting abnormality information automatically.

Transformer noise reduction measures by installing a soundproof wall and a resonant sound absorbing structure as disclosed in PTL <NUM> increase the transformer cost. Measures by attaching a weight to a reinforcing member as disclosed in PTL <NUM> are limited in the frequency of noise that can be reduced. Moreover, in the case where a member that is a main source of noise is not identified, a needless cost increase is caused by unnecessarily attaching a weight to a member to which a weight need not be attached. There is thus a need to reduce transformer noise efficiently or at low cost.

It could therefore be helpful to provide a transformer noise performance diagnosis method and noise reduction method that can reduce transformer noise efficiently or at low cost.

A transformer noise performance diagnosis method according to an embodiment of the present disclosure comprises: a first step of measuring an excitation noise of a stacked iron core included in a transformer and acquiring a frequency spectrum of the excitation noise, the stacked iron core being formed by stacking electrical steel sheets; a second step of, for excitation vibration calculation for the stacked iron core in the transformer using a constitutive equation that includes an elasticity matrix representing a relationship between stress and strain in the stacked iron core in matrix representation, determining transverse elasticity moduli in two planes each including a stacking direction of the stacked iron core in the transformer, the transverse elasticity moduli being included as elements in the elasticity matrix; a third step of performing the excitation vibration calculation for the stacked iron core in the transformer using the constitutive equation that includes the elasticity matrix including, as the elements, the transverse elasticity moduli determined in the second step and acquiring a frequency spectrum of an excitation vibration of the stacked iron core in the transformer; a fourth step of calculating a difference between the frequency spectrum of the excitation noise of the stacked iron core in the transformer acquired in the first step and the frequency spectrum of the excitation vibration of the stacked iron core in the transformer acquired in the third step, as a difference spectrum; and a fifth step of diagnosing noise performance of the transformer based on the difference spectrum calculated in the fourth step.

A transformer noise reduction method according to an embodiment of the present disclosure comprises a step of, based on a result of diagnosis of the noise performance of the transformer obtained by the above-described transformer noise performance diagnosis method, identifying a part that causes an increase in the noise of the transformer, and generating and notifying a diagnosis result urging to take a noise reduction measure for the identified part.

Thus, a transformer noise performance diagnosis method and noise reduction method according to the present disclosure can reduce transformer noise efficiently or at low cost.

A transformer such as a distribution transformer is formed by winding a coil around a stacked iron core obtained by stacking electrical steel sheets. Examples of important performances for a transformer include iron loss (no-load loss) property, excitation current property, and noise property.

Distribution transformers are installed in various locations. In particular, transformers installed in urban areas are strongly required to have low noise. Thus, noise performance, in particular, noise reduction, has become increasingly important as a performance required of transformers in recent years, in view of the influence on the surrounding environments of the transformers installed.

Grain-oriented electrical steel sheets, which are often used as iron core material for transformers, vibrate due to material expansion and shrinkage associated with excitation. Material expansion and shrinkage associated with excitation is also referred to as magnetostriction. Vibration due to magnetostriction is also referred to as magnetostrictive vibration. Magnetostrictive vibration is one of the main causes of noise in transformers. Therefore, the noise performance of a transformer can strongly depend on the magnetostrictive property of the electrical steel sheets used as iron core material. In order to reduce the noise of the transformer, electrical steel sheets having low magnetostrictive property can be employed as the iron core material of the transformer.

However, even in the case where electrical steel sheets having excellent magnetostrictive performance are used as the iron core material, reduction in transformer noise is often insufficient. A possible cause of insufficient noise reduction is the occurrence of a resonance phenomenon in accessory parts other than the iron core, such as the tank or the fixing metal fittings of the iron core of the transformer. It is therefore very important to reduce noise caused by mechanical vibrations of accessory parts other than the transformer iron core when designing and producing transformers.

Various techniques may be available for reducing the excitation noise of a transformer. One example is a method that installs a soundproof wall made of iron sheets or concrete around the transformer body. This method may reduce noise by the sound insulation effect of the soundproof wall, but the noise reduction is likely to be insufficient due to resonance within the soundproof wall. Such noise caused by resonance within the soundproof wall may be reduced by installing a resonant sound absorbing structure within the soundproof wall as disclosed in the foregoing PTL <NUM> (<CIT>). However, installing not only the soundproof wall but also the resonant sound absorbing structure further increases the cost of the transformer.

Transformer noise may be reduced without installing a soundproof wall, by attaching a reinforcing member to the side of the tank of the transformer and attaching a weight to part of the reinforcing member as disclosed in the foregoing PTL <NUM> (<CIT>). However, such a measure by attaching a weight is limited in the frequency of noise that can be reduced. For example, the frequency of noise reduced is limited to twice the excitation frequency in PTL <NUM>. Moreover, in the case where the noise generated by the reinforcing member to which the weight is attached is not the main noise source of the transformer noise, the noise reduction effect by attaching the weight is negligible. If the noise reduction effect is negligible, attaching the weight is needless and simply causes an increase in cost.

As a transformer noise performance diagnosis method according to this embodiment, a method that can easily identify a main noise source of transformer noise will be described below. Moreover, as a transformer noise reduction method according to this embodiment, a method that can take measures for the noise source identified by the noise performance diagnosis method efficiently or at low cost will be described below.

An embodiment of a transformer noise performance diagnosis method and noise reduction method according to the present disclosure will be described below with reference to the drawings. The drawings are schematic and may be different from actual ones. The following embodiment is illustrative of a device or method for embodying the technical idea of the present disclosure, but is not intended to limit the configuration to those described below. That is, various modifications can be made to the technical idea of the present disclosure within the technical scope defined by the claims.

A stacked iron core <NUM> to be analyzed in this embodiment is assumed here to be a stacked iron core for a three-phase tripod transformer used as a distribution transformer, for example. As illustrated in <FIG>, the stacked iron core <NUM> may be formed by stacking a plurality of grain-oriented electrical steel sheets <NUM> that each include three legs 22c connected between an upper yoke 22a and a lower yoke 22b and have a predetermined thickness. The stacked grain-oriented electrical steel sheets <NUM> are fixed by wrapping glass tape around them. The stacked iron core <NUM> to be analyzed in this embodiment is not limited to the stacked iron core for a three-phase tripod transformer illustrated in <FIG>.

Each step of the transformer noise performance diagnosis method according to this embodiment may be executed by a noise performance diagnosis device <NUM> illustrated in <FIG>. The noise performance diagnosis device <NUM> includes a controller <NUM>, a storage <NUM>, and an interface <NUM>.

The controller <NUM> controls and manages each functional unit included in the noise performance diagnosis device <NUM>, and the entire noise performance diagnosis device <NUM>. The controller <NUM> may include at least one processor such as a central processing unit (CPU), in order to control and manage various functions. The controller <NUM> may be composed of one processor or a plurality of processors. The processor included in the controller <NUM> may achieve the functions of the noise performance diagnosis device <NUM> by reading and executing a program stored in the storage <NUM>.

The storage <NUM> may have a function as memory that stores various information. The storage <NUM> may store, for example, the program executed by the controller <NUM>, data used in the processes executed by the controller <NUM>, the results of the processes, etc. The storage <NUM> may function as work memory for the controller <NUM>. The storage <NUM> may be implemented by, for example, semiconductor memory or the like, but is not limited to such and may include any storage device. For example, the storage <NUM> may be implemented as internal memory of the processor used as the controller <NUM>, or implemented as a hard disk drive (HDD) accessible from the controller <NUM>.

The interface <NUM> may include a communication interface for communicating with other devices by wire or wirelessly. The interface <NUM> may include an input-output port for inputting and outputting data from and to other devices. The interface <NUM> transmits and receives necessary data and signals to and from a process computer or host system. The interface <NUM> may communicate based on a wired communication standard or a wireless communication standard. Examples of the wireless communication standard include cellular phone communication standards such as <NUM>, <NUM>, and <NUM>. Other examples of the wireless communication standard include IEEE <NUM> and Bluetooth®. (Bluetooth is a registered trademark in Japan, other countries, or both). The interface <NUM> may support one or more of these communication standards. The interface <NUM> is not limited to these examples, and may communicate with other devices or input/output data based on any of various standards.

The noise performance diagnosis method according to this embodiment will be described below, assuming that each step of the flowchart illustrated in <FIG> is executed by the controller <NUM> in the noise performance diagnosis device <NUM>. Each step of the noise performance diagnosis method may be performed by another device or by a human.

First, in step S1 (first step), the controller <NUM> acquires the measurement result of the frequency spectrum of noise obtained by measuring the excitation noise of the stacked iron core <NUM> in the transformer subjected to vibration analysis illustrated in <FIG>. Specifically, the excitation frequency of the stacked iron core <NUM> is set to <NUM> and the excitation noise is measured. Typically, the frequency spectrum of the excitation noise of a transformer is composed of frequency components that are integral multiples of twice the excitation frequency (i.e. even multiples of the excitation frequency). Hence, the spectrum of the excitation noise at each frequency of <NUM> pitch in the range from <NUM> to <NUM> is acquired as the frequency spectrum of the noise. At transformer production sites, the excitation noise properties of transformers are commonly measured as a quality control item for shipped products. There is thus no particular difficulty in the measurement. The excitation frequency may be set to <NUM>. In the case where the excitation frequency is set to <NUM>, the spectrum of the excitation noise at each frequency of <NUM> pitch from <NUM> to <NUM> is acquired.

An example in which the excitation frequency is set to <NUM> will be described below. <FIG> is a graph illustrating an example of the frequency spectrum of noise acquired in the case where the excitation frequency is set to <NUM>. In the graph of <FIG>, the horizontal axis represents the frequency and the vertical axis represents the magnitude of excitation noise.

Next, in step S2 (second step), the controller <NUM> determines transverse elasticity moduli included as elements in an elasticity matrix, in order to perform excitation vibration calculation for the stacked iron core <NUM> and acquire the frequency spectrum of the excitation vibration in step S4 described later. The excitation vibration calculation for the stacked iron core <NUM> is possible through accurate estimation of the mechanical property values of the stacked iron core <NUM> formed by stacking a large number of thin steel sheets. The mechanical property values of the stacked iron core <NUM> can be accurately estimated based on, for example, the technique disclosed in <CIT>. The excitation vibration calculation for the stacked iron core <NUM> in this embodiment is performed using the technique disclosed in <CIT> in principle.

In this embodiment, a constitutive equation indicating the relationship between stress and strain is used as a governing equation for elastic structural analysis, in order to numerically analyze the vibration of the stacked iron core <NUM> of the three-phase tripod transformer illustrated in <FIG>. The constitutive equation is represented as the following equation (<NUM>) by replacing the laminate (stacked product) with an equivalent homogeneous body and expressing the influence of stacking using matrix physical property: <MAT> where [σ] is a stress matrix, [C] is an elasticity matrix (stiffness matrix) as a response function, and [ε] is a strain matrix.

As illustrated in <FIG>, the directions of the stacked iron core <NUM> are expressed using the X-axis, Y-axis, and Z-axis of the XYZ orthogonal coordinate system. The grain-oriented electrical steel sheets <NUM> extend along the XY plane, and are stacked in the Z-axis direction.

The stress acting on the stacked iron core <NUM> includes a normal component acting in a direction (compression direction or tensile direction) perpendicular to the stacked iron core <NUM> and a shear component acting in the shear direction of the stacked iron core <NUM>. <FIG>, <FIG>, and <FIG> illustrate normal stresses acting in the Z-axis direction, the X-axis direction, and the Y-axis direction, respectively. The normal stresses acting in the Z-axis direction, the X-axis direction, and the Y-axis direction are denoted by σz, σx, and σy, respectively. <FIG>, <FIG>, and <FIG> illustrate shear stresses acting in the ZX plane, the XY plane, and the YZ plane, respectively. The shear stresses acting in the ZX plane, the XY plane, and the YZ plane are denoted by τzx, τxy, and τyz, respectively. The stress matrix [σ] has normal stress and shear stress as components.

The strain of the stacked iron core <NUM> includes a component that deforms the stacked iron core <NUM> in the perpendicular direction (compression direction or tensile direction) and a component that deforms the stacked iron core <NUM> in the shear direction. The normal strains in the Z-axis direction, the X-axis direction, and the Y-axis direction are denoted by εz, εx, and εy, respectively. The shear strains in the ZX plane, the XY plane, and the YZ plane are denoted by yzx, yxy, and yyz, respectively.

The elasticity matrix [C] has <NUM> × <NUM> = <NUM> elements that specify the relationship between the six components of stress and the six components of strain. The <NUM> elements are represented by elasticity moduli Cij (i = <NUM> to <NUM>, j = <NUM> to <NUM>). The relationship between stress and strain is represented by the elasticity matrix as shown in the following equation (<NUM>):
[Math. <NUM>] <MAT>.

Since the stacked iron core <NUM> is made by stacking the grain-oriented electrical steel sheets <NUM>, the stacked iron core <NUM> has mechanical symmetry and also has <NUM>-degree symmetry in the longitudinal direction of the stacked grain-oriented electrical steel sheets <NUM> and in a direction orthogonal to the longitudinal direction. Hence, the stacked iron core <NUM> can be regarded as having orthotropy as an anisotropy classification. The elasticity matrix of an orthotropic object basically has a total of nine elasticity moduli, C11, C12, C13, C22, C23, C33, C44, C55, and C66, as shown in the following equation (<NUM>):
[Math. <NUM>] <MAT>.

Of these nine elasticity moduli, the elasticity moduli C11, C12, C13, C22, C23, and C33 are calculated based on the longitudinal elasticity moduli Ex, Ey, and Ez and the Poisson's ratios vxy, vyx, vyz, vzy, vzx, and vxz according to the following equations (<NUM>) to (<NUM>): <MAT>.

Moreover, the elasticity modulus C44 corresponds to the transverse elasticity modulus Gyz in the YZ plane, the elasticity modulus C55 corresponds to the transverse elasticity modulus Gzx in the ZX plane, and the elasticity modulus C66 corresponds to the transverse elasticity modulus Gxy in the XY plane, as shown in the following equations (<NUM>), (<NUM>), and (<NUM>): <MAT>.

Here, Ex, Ey, and Ez denote the longitudinal elasticity modulus (Young's modulus) in the X direction, the longitudinal elasticity modulus (Young's modulus) in the Y direction, and the longitudinal elasticity modulus (Young's modulus) in the Z direction respectively, and vxy, vyx, vyz, vzy, vzx, and vxz denote the Poisson's ratio in the XY plane (the ratio of the longitudinal strain in the X direction and the transverse strain in the Y direction), the Poisson's ratio in the YX plane, the Poisson's ratio in the YZ plane, the Poisson's ratio in the ZY plane, the Poisson's ratio in the ZX plane, and the Poisson's ratio in the XZ plane respectively. The relationship represented by the following equation (<NUM>), called the reciprocity theorem, holds between the longitudinal elasticity moduli and the Poisson's ratios:
[Math. <NUM>] <MAT>.

According to the reciprocity theorem, the Poisson's ratio vyx in the YX plane is expressed using Ex, Ey, and vxy, the Poisson's ratio vzy in the ZY plane is expressed using Ez, Ey, and vyz, and the Poisson's ratio vxz in the XZ plane is expressed using Ez, Ex, and vzx.

Thus, the values of the total of nine elasticity moduli C11, C12, C13, C22, C23, C33, C44, C55, and C66 representing the elasticity matrix of an orthotropic object are expressed using the total of nine mechanical property values: the longitudinal elasticity moduli Ex, Ey, and Ez, the transverse elasticity moduli Gyz, Gzx, and Gxy, and the Poisson's ratios vxy, vyz, and vzx. Therefore, determining these nine mechanical property values is equivalent to determining the nine elasticity moduli representing the elasticity matrix. A method of determining the longitudinal elasticity moduli, the transverse elasticity moduli, and the Poisson's ratios will be described below.

Regarding the longitudinal elasticity moduli of the stacked iron core <NUM> having orthotropy, the longitudinal elasticity moduli Ex and Ey can be set to values equal to the longitudinal elasticity moduli Ex0 and Ey0 of one steel sheet, respectively. On the other hand, the longitudinal elasticity modulus Ez cannot be set to a value equal to the longitudinal elasticity modulus Ez0 of one steel sheet. This is because there is a slight gap between the stacked steel sheets. In view of this, in this embodiment, an experiment is conducted to determine the relationship between the load and displacement in the stacking direction of the stacked steel sheets, and the longitudinal elasticity modulus Ez is set based on the result of the experiment. In this embodiment, it is assumed that Ez is set to <NUM> GPa based on the result of the experiment. Here, given that the magnitude of the value of the longitudinal elasticity modulus in the stacking direction has little influence on the vibration calculation result, the error in the vibration calculation result is small even if Ez is set to a value equal to the longitudinal elasticity modulus Ez0 of one steel sheet.

Regarding the Poisson's ratios of the stacked iron core <NUM> having orthotropy, the Poisson's ratio vxy in the XY plane can be set to a value equal to the Poisson's ratio νxy0 of one steel sheet. On the other hand, the Poisson's ratio vyz in the YZ plane and the Poisson's ratio vzx in the ZX plane cannot be set directly to the Poisson's ratios vyz0 and vzx0 of one steel sheet. This is because the dynamic linkage between the strain in the stacking direction and the strain in the direction perpendicular to the stacking direction is likely to be very weak in the stacked iron core <NUM>. It is extremely difficult to actually measure vyz and vzx. However, given the above consideration, vyz and vzx are expected to be very small. Hence, it is assumed in this embodiment that vyz and vzx are both zero.

Regarding the transverse elasticity moduli of the stacked iron core <NUM>, the transverse elasticity modulus Gxy in the XY plane can be set to a value equal to the transverse elasticity modulus Gxy0 of one steel sheet. On the other hand, the transverse elasticity moduli in two planes each including the stacking direction, namely, the transverse elasticity modulus Gzx in the ZX plane and the transverse elasticity modulus Gyz in the YZ plane, cannot be set directly to the transverse elasticity moduli Gxz0 and Gyz0 of one steel sheet. This is because the influence of slippage between the steel sheets in the X direction and the Y direction orthogonal to the stacking direction, which occurs at the interface of the stacked steel sheets, needs to be reflected on the transverse elasticity moduli Gzx and Gyz. Therefore, in order to perform vibration analysis using the constitutive equation that represents the relationship between the stress and strain of the stacked iron core <NUM> in matrix representation, it is important to determine the transverse elasticity moduli in the two planes each including the stacking direction of the stacked iron core <NUM> in the transformer included in the elasticity matrix in the constitutive equation, namely, the transverse elasticity modulus Gzx in the ZX plane and the transverse elasticity modulus Gyz in the YZ plane.

In view of this, in this embodiment, the transverse elasticity moduli Gzx and Gyz in the two planes each including the stacking direction are determined based on the method disclosed in <CIT> for the value of the clamping pressure in the stacking direction when producing the stacked iron core <NUM>.

Next, in step S3, the controller <NUM> acquires frequency spectrum data of excitation magnetostriction used in the excitation vibration calculation for the stacked iron core <NUM> in the transformer in step S4 described later. The controller <NUM> acquires frequency spectrum data of excitation magnetostriction of the same electrical steel sheet as the grain-oriented electrical steel sheets <NUM> forming the stacked iron core <NUM> in the transformer subjected to vibration analysis illustrated in <FIG>. The controller <NUM> acquires, as the frequency spectrum data of excitation magnetostriction, spectrum data of excitation magnetostriction amplitude at each frequency of <NUM> pitch in the range from <NUM> to <NUM>. The controller <NUM> can acquire the frequency spectrum data of excitation magnetostriction, for example, by measuring the excitation magnetostriction of the electrical steel sheet or acquiring the frequency spectrum data from the manufacturer of the electrical steel sheet. <FIG> is a graph illustrating an example of the acquired frequency spectrum data of excitation magnetostriction. In the graph of <FIG>, the horizontal axis represents the frequency and the vertical axis represents the magnitude of magnetostriction amplitude. The magnitude of magnetostriction amplitude at each frequency is expressed in dB as a value normalized by being divided by the value of magnetostriction amplitude when the frequency is <NUM>. The dB expression corresponds to a value obtained by multiplying, by <NUM>, the common logarithm of the value to be expressed.

Next, in step S4, the controller <NUM> performs numerical calculation of the excitation vibration of the stacked iron core <NUM> in the transformer subjected to vibration analysis illustrated in <FIG>, and calculates the frequency spectrum of the vibration response function of the stacked iron core <NUM>.

Specifically, the controller <NUM> performs vibration response analysis on the stacked iron core <NUM> in the transformer subjected to vibration analysis, using structural analysis software. Of the total of nine mechanical property values of the stacked iron core <NUM>, i.e. the longitudinal elasticity moduli Ex, Ey, and Ez, the transverse elasticity moduli Gyz, Gzx, and Gxy, and the Poisson's ratios vxy, vyz, and vzx, the seven mechanical property values excluding the transverse elasticity moduli Gyz and Gzx are set as follows, as described above: <MAT> <MAT> <MAT>.

The controller <NUM> then determines the remaining two transverse elasticity moduli Gyz and Gzx in the two planes each including the stacking direction, based on the method disclosed in <CIT> for the value of the clamping pressure in the stacking direction when producing the iron core as mentioned above. The controller <NUM> performs vibration calculation using the transverse elasticity moduli Gzx and Gyz in the two planes each including the stacking direction, to calculate the frequency spectrum of the vibration response function of the stacked iron core <NUM> in the transformer. <FIG> is a graph illustrating an example of the frequency spectrum of the vibration response function of the stacked iron core <NUM> in the transformer calculated in step S4. In the graph of <FIG>, the horizontal axis represents the frequency and the vertical axis represents the magnitude of the response function. The magnitude of the response function is represented as a value normalized so that the vibration response value when the frequency is <NUM> will be <NUM> dB.

Next, in step S5, the controller <NUM> calculates the frequency spectrum of the excitation vibration of the stacked iron core <NUM> in the transformer based on the frequency spectrum data of the excitation magnetostriction of the electrical steel sheet acquired in step S3 and the frequency spectrum of the vibration response function of the stacked iron core <NUM> in the transformer calculated in step S4. Specifically, the controller <NUM> calculates the frequency spectrum of the excitation vibration of the stacked iron core <NUM> in the transformer as the product of the frequency spectrum data of the excitation magnetostriction of the electrical steel sheet and the frequency spectrum of the vibration response function of the stacked iron core <NUM> in the transformer. In the case where the frequency spectrum is expressed in dB, the controller <NUM> calculates the frequency spectrum of the excitation vibration of the stacked iron core <NUM> in the transformer as the sum of the frequency spectrum of the excitation magnetostriction of the electrical steel sheet and the frequency spectrum of the vibration response function of the stacked iron core <NUM> in the transformer.

<FIG> is a graph illustrating an example of the calculated frequency spectrum of the excitation vibration of the stacked iron core <NUM> in the transformer. In the graph of <FIG>, the horizontal axis represents the frequency and the vertical axis represents the calculated value of the magnitude of the excitation vibration. The magnitude of the excitation vibration is expressed in dB.

In the noise performance diagnosis method according to this embodiment, steps S3 to S5 in <FIG> constitute a third step to calculate the excitation vibration of the stacked iron core <NUM> in the transformer subjected to vibration analysis illustrated in <FIG> and acquire the frequency spectrum of the excitation vibration.

Next, in step S6 (fourth step), the controller <NUM> calculates the difference between the frequency spectrum of the excitation noise of the stacked iron core <NUM> in the transformer acquired in the first step (step S1) and the frequency spectrum of the excitation vibration of the stacked iron core <NUM> in the transformer calculated in the second step (steps S2 to S5). <FIG> is a graph illustrating an example of the calculated frequency spectrum of the difference between the excitation noise spectrum (measured value) and the frequency spectrum (calculated value) of the excitation vibration of the stacked iron core <NUM> in the transformer.

Next, in step S7 (fifth step), the controller <NUM> diagnoses the noise performance of the transformer based on the difference spectrum calculated in the fourth step (step S6). The frequency spectrum (calculated value) of the excitation vibration of the stacked iron core <NUM> in the transformer illustrated in <FIG> as an example represents the predicted value of the excitation vibration noise emitted only by the iron core made up of the electrical steel sheets. The frequency spectrum (measured value) of the excitation noise of the stacked iron core <NUM> in the transformer illustrated in <FIG> as an example, on the other hand, represents the excitation vibration noise of the entire transformer, including not only the iron core made up of the electrical steel sheets but also the accessory parts other than the electrical steel sheets, such as metal fittings for fixing the iron core. In view of the meanings of these frequency spectra, the difference spectrum between the excitation noise spectrum (measured value) and the frequency spectrum of the excitation vibration (calculated value) of the stacked iron core <NUM> in the transformer illustrated in <FIG> as an example can be interpreted as corresponding to the increase in transformer noise due to the noise emitted by the accessory parts other than the electrical steel sheets of the target transformer as a noise source. Through such interpretation of the physical meaning of the difference spectrum between the excitation noise spectrum (measured value) and the frequency spectrum of the excitation vibration (calculated value) of the stacked iron core <NUM> in the transformer illustrated in <FIG> as an example, the controller <NUM> can easily identify the frequency of noise generated in the accessory parts other than the electrical steel sheets of the transformer.

For example, the component at a frequency of <NUM> is large in the difference spectrum illustrated in <FIG>. Based on this, the controller <NUM> can easily diagnose that the noise of the entire transformer increases as a result of any of the accessory parts of the transformer vibrating at <NUM>. Each component of the difference spectrum is also referred to as "difference value". The frequency at which the difference value is maximum is also referred to as "peak frequency". The controller <NUM> may determine the frequency at which the difference value is maximum as the peak frequency based on the difference spectrum.

The controller <NUM> acquires the measurement results of the vibration frequencies of the accessory parts. The vibration frequency of each accessory part can be measured by attaching an acceleration sensor to the accessory part and exciting it, or by measuring the vibration frequency of the accessory part with a laser Doppler vibrometer in a state in which the transformer is excited.

The controller <NUM> may extract any accessory part whose vibration frequency corresponds to a frequency with a large value in the difference spectrum, and generate and notify a diagnosis result urging to take noise reduction measures for the extracted part. The controller <NUM> may extract any part whose vibration frequency is the same value as the peak frequency of the difference spectrum or any part whose vibration frequency has a difference of not more than a predetermined value from the peak frequency, and generate and notify a diagnosis result urging to take noise reduction measures for the extracted part. The part extracted based on the difference spectrum can be regarded as being identified as a part that causes an increase in transformer noise. For example, in the case where the difference spectrum is calculated as illustrated in the graph of <FIG>, any part whose vibration frequency is <NUM> may be extracted from among the accessory parts and subjected to noise reduction measures. In this way, the transformer noise can be reduced efficiently or at low cost.

The following will describe verification of the effects of implementing the transformer noise performance diagnosis method and noise reduction method according to this embodiment by way of an example.

First, grain-oriented electrical steel sheets <NUM> of <NUM> in thickness were prepared. The prepared grain-oriented electrical steel sheets <NUM> were then stacked together to produce a stacked iron core <NUM> for a three-phase tripod transformer subjected to vibration analysis as illustrated in <FIG>. The thickness of the stacked steel sheets of the stacked iron core <NUM> was <NUM>. The dimensions of each of the upper yoke 22a and the lower yoke 22b were <NUM> in width and <NUM> in length. The dimensions of each of the three legs 22c were <NUM> in width with an iron core window length of <NUM>. The legs 22c were connected between the upper yoke 22a and the lower yoke 22b with spacing of <NUM> from each other. An IV electric wire was wound around each of the three legs 22c of the produced stacked iron core <NUM> to form an excitation coil.

A <NUM> three-phase current was applied to the coil, and the power supply voltage was adjusted so that the iron core magnetic flux density would be exactly <NUM> T. In this state, the excitation noise was measured using a noise meter to obtain the frequency spectrum of the noise as in step S1 in <FIG>. Suppose the measurement result of the frequency spectrum of the noise in this example was the same as that illustrated in the graph of <FIG>. Of the components of the frequency spectrum of the noise measured in this example, the magnitude of the component at a frequency of <NUM> was approximately <NUM> dBA.

Next, the excitation magnetostriction of the prepared grain-oriented electrical steel sheets <NUM> when excited at an excitation frequency of <NUM> and a magnetic flux density of <NUM> T was measured using a magnetostriction measurement device to obtain the frequency spectrum of the magnetostriction. Suppose the frequency spectrum of the magnetostriction in this example was the same as that illustrated in the graph of <FIG>. Of the components of the frequency spectrum of the magnetostriction in this example, the magnitude of the component at a frequency of <NUM> was approximately <NUM>.

Vibration response analysis was then performed on the stacked iron core <NUM> in the transformer subjected to vibration analysis using structural analysis software. Here, seven out of the total of nine mechanical property values of the stacked iron core <NUM>, i.e. the longitudinal elasticity moduli Ex, Ey, and Ez, the transverse elasticity moduli Gyz, Gzx, and Gxy, and the Poisson's ratios vxy, vyz, and vzx, were set as follows: <MAT> <MAT> <MAT> where x corresponds to the steel sheet rolling direction, y corresponds to a direction orthogonal to x, and z corresponds to the steel sheet stacking direction.

The remaining two transverse elasticity moduli Gyz and Gzx in the two planes each including the stacking direction were determined using the technique disclosed in <CIT> as mentioned above.

The clamping pressure in the stacking direction of the iron core when producing the stacked iron core <NUM> for a three-phase tripod transformer illustrated in <FIG> was <NUM> MPa. Accordingly, the transverse elasticity moduli of the stacked iron core <NUM> were determined to be Gyz = Gzx = <NUM> GPa. Suppose the frequency spectrum of the vibration response function of the stacked iron core <NUM> calculated in this example was the same as that illustrated in the graph of <FIG>. Of the components of the frequency spectrum of the vibration response function calculated in this example, the magnitude of the component at a frequency of <NUM> was approximately 13dB.

Following this, the frequency spectrum of the excitation vibration of the stacked iron core <NUM> in the transformer was calculated based on the frequency spectrum data of the excitation magnetostriction of the electrical steel sheets and the frequency spectrum of the vibration response function of the stacked iron core <NUM> in the transformer. Suppose the frequency spectrum of the excitation vibration of the stacked iron core <NUM> calculated in this example was the same as that illustrated in the graph of <FIG>. Of the components of the frequency spectrum of the excitation vibration calculated in this example, the magnitude of the component at a frequency of <NUM> was approximately <NUM> dBA.

The difference spectrum between the frequency spectrum of the excitation noise of the stacked iron core <NUM> in the transformer illustrated in <FIG> and the frequency spectrum of the excitation vibration of the stacked iron core <NUM> in the transformer illustrated in <FIG> was then calculated. Suppose the difference spectrum calculated in this example was the same as that illustrated in the graph of <FIG>. Of the components of the difference spectrum calculated in this example, the magnitude of the component at a frequency of <NUM> was approximately <NUM> dB.

After this, the noise performance of the transformer was diagnosed based on the difference spectrum illustrated in <FIG>. In this example, it was diagnosed that there was a part vibrating at <NUM> among the accessory parts of the transformer to be diagnosed and the noise generated by the vibration of that part caused an increase in transformer noise.

Hence, the vibration frequency of each accessory part of the transformer to be diagnosed was measured using a laser vibrometer while exciting the transformer at a frequency of <NUM> and a magnetic flux density of <NUM> T. As a result, it was found that the end of the metal fitting clamping the upper yoke 22a of the stacked iron core <NUM> in the transformer was vibrating at <NUM>.

In view of this, one bolt was added to the end of the metal fitting clamping the upper yoke 22a of the stacked iron core <NUM> in the transformer to increase the tightening force and enhance the rigidity of the metal fitting. This resulted in <NUM> dB reduction of the excitation noise of the transformer in overall value.

As described above, in this example, it was possible to identify the accessory part causing the increase in transformer noise and easily take noise reduction measures for the identified part.

Although the embodiment of the present disclosure has been described by way of the drawings and examples, various changes and modifications may be made by those of ordinary skill in the art based on the present disclosure. Such various changes and modifications are therefore included in the scope of the present disclosure. For example, the functions included in the components, steps, etc. may be rearranged without logical inconsistency, and a plurality of components, steps, etc. may be combined into one component, step, etc. and a component, step, etc. may be divided into a plurality of components, steps, etc. The embodiment of the present disclosure may also be implemented as a program executed by a processor included in the device or a storage medium storing the program. These are also encompassed within the scope of the present invention, which is defined by the appended claims.

Claim 1:
A transformer noise performance diagnosis method comprising:
a first step (S1) of measuring an excitation noise of a stacked iron core included in a transformer and acquiring a frequency spectrum of the excitation noise, the stacked iron core being formed by stacking electrical steel sheets;
a second step (S2) of, for excitation vibration calculation for the stacked iron core in the transformer using a constitutive equation that includes an elasticity matrix representing a relationship between stress and strain in the stacked iron core in matrix representation, determining transverse elasticity moduli in two planes each including a stacking direction of the stacked iron core in the transformer, the transverse elasticity moduli being included as elements in the elasticity matrix;
a third step (S3, S4, S5) of performing the excitation vibration calculation for the stacked iron core in the transformer using the constitutive equation that includes the elasticity matrix including, as the elements, the transverse elasticity moduli determined in the second step and acquiring a frequency spectrum of an excitation vibration of the stacked iron core in the transformer;
a fourth step (S6) of calculating a difference between the frequency spectrum of the excitation noise of the stacked iron core in the transformer acquired in the first step and the frequency spectrum of the excitation vibration of the stacked iron core in the transformer acquired in the third step, as a difference spectrum; and
a fifth step (S7) of diagnosing noise performance of the transformer based on the difference spectrum calculated in the fourth step.