WO2023240821A1 - Water cooling system leakage monitoring method - Google Patents

Abstract

A water cooling system leakage monitoring method, comprising: acquiring liquid level value change data, and constructing a scale function; decomposing the liquid level value change data into low-order high-frequency components and low-order low-frequency components by using a wavelet transform; reconstructing a high-order scale function by using the low-order low-frequency components; obtaining a liquid level change trend curve according to the high-order scale function, and monitoring, according to the liquid level change trend curve, whether leakage occurs. By means of a wavelet transform method, liquid level fluctuations caused by temperature can be filtered so as to obtain liquid level change trend data, so that the leakage of a valve cooling system can be effectively and accurately determined, defects of valve cooling monitoring means in the prior art can be overcome, and the stability of the valve cooling system is improved.

Description

A method for monitoring leakage in water cooling systems Technical field

The invention relates to the technical field of control and protection of high-voltage direct current transmission converter valve cooling systems, specifically a leakage monitoring method for water cooling systems.

Background technique

Thyristor converter valves and IGBT converter valves are widely used in the field of DC transmission engineering. The thyristor components in the converter valve generate high heat during operation, and the heat generated needs to be taken out through circulating cooling water. The external heat dissipation system performs heat exchange to cool the cooling water to a reasonable range and flow back to the converter valve again, forming an internal circulation system of cooling water.

The internal circulation system is equipped with a buffer water tank to buffer the impact of changes in cooling water volume, and is equipped with a liquid level sensor to send the detected cooling water volume changes to the valve cooling system control and protection device. At present, the traditional valve cold water leakage detection method has problems such as small amount of data processing and simple detection method. The water leakage detection logic is usually an alarm when the short-term liquid level drops beyond the limit, or is supplemented by temperature compensation to eliminate the problem. Due to the influence of changes in water volume caused by changes in water temperature, only serious water leaks can be detected. It is difficult to accurately detect minor water leaks. Moreover, due to the low accuracy of the temperature compensation method, it can easily lead to misjudgment alarms.

With the development of digital converter station technology in recent years, operation and maintenance data of valve cooling equipment within several months or even a year can be collected and stored for equipment operating status assessment. Currently, there is still no effective water leakage monitoring method to analyze and process the above massive amounts of data. data. In order to make up for the shortcomings of existing valve cooling system leakage monitoring methods and improve the quality of DC valve cooling operation and maintenance, a water cooling system leakage monitoring method is proposed to solve the above problems.

Contents of the invention

The purpose of this section is to outline some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, the abstract and the title of the invention to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions cannot be used to limit the scope of the invention.

In view of the above and/or problems existing in existing valve cooling system monitoring designs, the present invention is proposed.

Therefore, one of the objects of the present invention is to provide a leakage monitoring method for a water-cooling system. The wavelet transform method can filter out liquid level fluctuations caused by temperature, thereby obtaining trend data of liquid level changes, and can effectively and accurately determine valves. leakage of the cooling system, and can make up for the shortcomings of the existing technology in valve cooling monitoring means and improve the stability of the valve cooling system.

In order to achieve the above effect, the present invention provides the following technical solution: a water cooling system leakage monitoring method, which includes collecting liquid level value change data and constructing a scale function; using wavelet transformation to decompose the liquid level value change data into low-order and high-order frequency component and low-order low-frequency component; use the low-order low-frequency component to reconstruct the high-order scale function; obtain the trend curve of the liquid level change according to the high-order scale function, and monitor whether there is leakage based on the trend curve of the liquid level change.

As a preferred solution of the present invention, the collection of liquid level value change data and the structure include: obtaining n liquid level change data through a water level sensor, taking an integer j = [log ₂ n], and using j-order The scale function represents:

为液位数据第k个记录值； in,

is the kth recorded value of liquid level data;

Among them, φ(x) is the scale function expression.

As a preferred solution of the present invention, the use of wavelet transform to decompose the liquid level value transformation data into low-order high-frequency components and low-order low-frequency components includes: using the wavelet transformation function ψ(x) to The scale function f _j (x) is converted; the converted f _j (x) is decomposed to obtain a low-order high-frequency component and a low-order low-frequency component, and the low-order low-frequency component is decomposed again, and each time thereafter Decomposing the low-order low-frequency component obtained in the last decomposition will result in a low-order high-frequency component and a low-order low-frequency component. Decompose it ji times to obtain ji low-frequency high-order components and a final low-order low-frequency component f _i .

As a preferred solution of the present invention, the use of the wavelet transform function ψ(x) to transform the scale function f _j (x) includes: the expression of the wavelet transform function ψ(x) is:

ψ(x)＝φ(2x)-φ(2x-1)

As a preferred solution of the present invention, the use of the wavelet transform function ψ(x) to convert the scale function f _j (x) further includes: the scale function f _j (x) is converted to:

in,

为j阶尺度下的第2k个尺度系数，

为j阶尺度下的第2k+1个尺度系数，k为对应阶数下的第k个值，

为j-1阶尺度下的第k个尺度系数，

为j-1阶尺度下的第k个小波系数。 in,

is the 2kth scale coefficient under the j-order scale,

is the 2k+1th scale coefficient under the j-order scale, k is the k-th value under the corresponding order,

is the kth scale coefficient under the j-1 order scale,

is the kth wavelet coefficient under the j-1 order scale.

As a preferred solution of the present invention, the converted scale function f _j (x) is recorded as f _j =w _j-1 +f _j-1 , and f _j-1 is continued to be converted until it is decomposed To level i, we get

f _j ＝w _j-1 +w _j-2 +…+w _i +f _i

Among them, i<j, w _j-1 , w _j-2 ,..., w _i are the high-frequency components of each order, and f _i is the i-order low-frequency component.

As a preferred solution of the present invention, the expression of the i-order low-frequency component _fi is:

为i阶尺度下的第k个尺度系数。 in,

is the kth scale coefficient under the i-order scale.

As a preferred solution of the present invention, the use of low-order low-frequency components to reconstruct the high-order scale function includes: obtaining the reconstruction function after reconstruction:

为i阶尺度下的第k个尺度系数。 in,

is the kth scale coefficient under the i-order scale.

As a preferred solution of the present invention, the reconstruction function is simplified to obtain:

为i+1阶尺度下的第l个尺度系数； in,

is the lth scale coefficient under the i+1 order scale;

The reconstruction function is repeatedly upgraded from i+1 to i+2, ..., to j, thereby obtaining the scale function of f _i at the jth order.

As a preferred solution of the present invention, wherein: obtaining the trend curve of liquid level change according to the high-order scale function, and detecting whether there is leakage based on the trend curve of liquid level change and the fixed value includes: Thus, the scale function of f _i at order j is obtained. The expression of this scale function is:

为j阶尺度下的第l个尺度系数； in,

is the l-th scale coefficient under the j-order scale;

最大值为A _max，其序号n _max，最小值为A _min，其序号n _min，L为设定的渗漏定值，若A _max-A _min>L，且n _max<n _min，则发出渗漏告警。 The scale function is the trend curve of liquid level change, and the coefficient data is recorded

The maximum value is A _max , and its serial number is n _max . The minimum value is A _min , and its serial number is n _min . L is the set leakage value. If A _max -A _min >L, and n _max <n _min , then Leak warning.

Beneficial effects of the present invention: The present invention can filter out the liquid level fluctuation caused by the influence of temperature through the wavelet transformation method, thereby obtaining the trend data of the liquid level change, can effectively and accurately determine the leakage of the valve cooling system, and can compensate for the current situation. There are technical deficiencies in valve cooling water leakage detection methods to improve the stability of the valve cooling system.

Description of the drawings

In order to explain the technical solutions of the embodiments of the present invention more clearly, the drawings needed to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without exerting creative labor. in:

Figure 1 is a schematic diagram of the wavelet function decomposition of the present invention.

Figure 2 is a graph of liquid level change data of the present invention.

曲线图。 Figure 3 shows the coefficient data of the scale function f _i (x) of the present invention at the jth order.

Graph.

Detailed ways

In order to make the above objects, features and advantages of the present invention more obvious and understandable, the specific implementation modes of the present invention will be described in detail below with reference to the accompanying drawings.

Many specific details are set forth in the following description to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described here. Those skilled in the art can do so without departing from the connotation of the present invention. Similar generalizations are made, and therefore the present invention is not limited to the specific embodiments disclosed below.

Second, reference herein to "one embodiment" or "an embodiment" refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. "In one embodiment" appearing in different places in this specification does not all refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

Example 1

Referring to Figures 1 to 3, this embodiment provides a water cooling system leakage monitoring method, including:

S1. Collect liquid level value change data and construct a scale function:

Obtain n liquid level change data through the water level sensor, take the integer j=[log ₂ n]=12, and use the j-order scale function to express:

为液位数据第k个记录值； in,

is the kth recorded value of liquid level data;

Among them, φ(x) is the scale function expression.

The valve cooling system is sequentially provided with a main circulation pump, a converter valve, a high-level water tank or a buffer water tank, and a cooling tank that are connected through pipelines and form a loop. The high-level water tank or buffer water tank is connected to the main circulation pump. The high-level water tank or buffer water tank is equipped with internal There is a water level sensor that records the liquid level value regularly.

S2. Use wavelet transform to decompose the liquid level value change data into low-order high-frequency components and low-order low-frequency components, discard the high-frequency component caused by temperature changes, and decompose the low-frequency component.

S21. Use the wavelet transform function ψ(x) to convert the scale function f _j (x):

The expression of wavelet transform function ψ(x) is:

ψ(x)＝φ(2x)-φ(2x-1)

The scale function f _j (x) is converted to:

in,

为j阶尺度下的第2k个尺度系数，

为j阶尺度下的第2k+1个尺度系数，k为对应阶数下的第k个值，

为j-1阶尺度下的第k个尺度系数，

为j-1阶尺度下的第k个小波系数。 in,

is the 2kth scale coefficient under the j-order scale,

is the 2k+1th scale coefficient under the j-order scale, k is the k-th value under the corresponding order,

is the kth scale coefficient under the j-1 order scale,

is the kth wavelet coefficient under the j-1 order scale.

S22. Decompose the converted f _j (x) to obtain a low-order high-frequency component and a low-order low-frequency component. Decompose the low-order low-frequency component again, and then decompose the low-order low-frequency component obtained from the previous decomposition each time. Decomposition will result in a low-order high-frequency component and a low-order low-frequency component. Decompose it ji times to obtain ji low-frequency high-order components and a final low-order low-frequency component f _i ;

Record the scale function f _j (x) obtained after conversion as f _j =w _j-1 +f _j-1 , and continue to convert f _j-1 until it is decomposed to order i, and we get

f _j ＝w _j-1 +w _j-2 +…+w _i +f _i

Among them, i<j, w _j-1 , w _j-2 ,..., w _i are the high-frequency components of each order, _fi is the i-order low-frequency component, and the expression of the i-order low-frequency component f _i is:

为i阶尺度下的第k个尺度系数。 in,

is the kth scale coefficient under the i-order scale.

S3. Use low-order low-frequency components to reconstruct the high-order scale function:

After reconstruction, we get the reconstruction function:

为i阶尺度下的第k个尺度系数；只有在阶数尺度下的系数才可用，其他阶数仅是i阶下的尺度系数。 in,

is the kth scale coefficient under the i-order scale; only the coefficients under the order scale are available, and other orders are only the scale coefficients under the i-order.

The reconstruction function is simplified to get:

为i+1阶尺度下的第l个尺度系数； The above reconstruction process is from i to i+1, where,

is the lth scale coefficient under the i+1 order scale;

The reconstruction function is repeatedly upgraded from i+1 to i+2,..., to j, thereby obtaining the scale function of f _i at the jth order. The purpose of the reconstruction function is to restore the decomposed low-frequency components to be consistent with the original data. At the same scale, the function at the i scale is raised by one level i+1 through reconstruction, and so on until the jth order. The functions at different scales are reconstructed to the jth order. It is consistent with the original data function to facilitate data analysis. This article only describes the process of repeatedly increasing the order from i to i+1, and from i+1 to i+2 to j, which is the cycle of the algorithm.

Reconstruction is mainly achieved through the properties of the φ function and ψ function, but only low-frequency component reconstruction is used here, so only the properties of the φ function are used.

S4. Obtain the trend curve of the liquid level change based on the high-order scaling function, and monitor whether there is leakage based on the trend curve of the liquid level change:

The expression of the scale function of f _i at order j is:

为j阶尺度下的第l个尺度系数； in,

is the l-th scale coefficient under the j-order scale;

最大值为A _max，其序号n _max，最小值为A _mi，其序号n _nmi，L为设定的渗漏定值，若A _max-A _min>L，且n _max<n _min，则发出渗漏告警。将记录的液位数据通过小波变换分解滤除数据中受温度影响造成的波动数据，提取液位变化趋势数据，再将趋势数据进行重构，利用重构的趋势数据来判断渗漏情况，渗漏定值可以根据不同密闭式阀冷系统中各个部件泄漏量和消耗量累加计算得出，比如主泵循环泵机封的渗漏量，此渗漏量远小于日常液位波动数值，通过长期数据累计得到。 This scale function is the trend curve of liquid level change, and the coefficient data is recorded

The maximum value is A _max , and its serial number is n _max . The minimum value is A _mi , and its serial number is n _nmi . L is the set leakage value. If A _max -A _min >L, and n _max <n _min , then Leak warning. Decompose the recorded liquid level data through wavelet transform to filter out the fluctuation data caused by temperature in the data, extract the liquid level change trend data, and then reconstruct the trend data, and use the reconstructed trend data to determine the leakage situation. The leakage setting value can be calculated based on the cumulative leakage and consumption of each component in different closed valve cooling systems, such as the leakage of the main pump circulation pump seal. This leakage is far smaller than the daily liquid level fluctuation value. Through long-term The data is accumulated.

曲线图如图3，可以知道，最大值A _max为47.22，其序号n _max＝0，最小值为A _min为38.32，其序号n _mi＝4096，设定的渗漏定值为L＝3，此时判定A _max-A _min>L，且n _max<n _min(8.9>3，且0<4096)进而发出渗漏告警。 In this embodiment, as shown in Figure 2, 4320 liquid level change data are obtained through the water level sensor, and the integer j=[log ₂ n]=12 is taken. When i=4 is taken, the scale function of _fi (x) at the jth order coefficient data

The graph is shown in Figure 3. It can be seen that the maximum value A _max is 47.22, its serial number n _max = 0, the minimum value A _min is 38.32, its serial number n _mi = 4096, and the set leakage value is L = 3. At this time, it is determined that A _max -A _min >L, and n _max <n _min (8.9>3, and 0 <4096), and a leakage alarm is issued.

Comparing Figure 2 and Figure 3, we can see that the original liquid level data fluctuates greatly and it is impossible to accurately determine the leakage of the system. The difference between the two data points (711, 49.9) and (846, 41.3) in Figure 2 is 8.6. The data in Figure 3 obtained by the method of the present invention can easily and conveniently determine the system leakage situation, and in practical applications, an appropriate judgment period can also be selected to issue alarm information in a timely manner, and thus system faults can be discovered earlier, such as At the moment (1536, 42.86) in Figure 3, the leakage judgment condition of the system has been met.

It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solution of the present invention can be carried out. Modifications or equivalent substitutions without departing from the spirit and scope of the technical solution of the present invention shall be included in the scope of the claims of the present invention.

Claims (10)

A water cooling system leakage monitoring method, characterized by: including: Collect liquid level value change data and construct a scale function; Using wavelet transform, the liquid level value change data is decomposed into low-order high-frequency components and low-order low-frequency components; Use low-order low-frequency components to reconstruct high-order scaling functions; The trend curve of the liquid level change is obtained according to the high-order scale function, and whether there is leakage is monitored according to the trend curve of the liquid level change. The water cooling system leakage monitoring method according to claim 1, characterized in that: collecting liquid level value change data and constructing a scale function includes: Obtain n liquid level change data through the water level sensor, take the integer j=[log ₂ n], and express it with a j-order scale function:

in,

is the kth recorded value of liquid level data;

Among them, φ(x) is the scale function expression. The water cooling system leakage monitoring method according to claim 2, characterized in that: using wavelet transform to decompose the liquid level value transformation data into low-order high-frequency components and low-order low-frequency components includes: Use the wavelet transform function ψ(x) to transform the scale function f _j (x); Decompose the converted f _j (x) to obtain a low-order high-frequency component and a low-order low-frequency component, decompose the low-order low-frequency component again, and then decompose the low-order low-frequency component obtained from the previous decomposition each time. Decomposition will result in a low-order high-frequency component and a low-order low-frequency component. Decompose it ji times to obtain ji low-frequency high-order components and a final low-order low-frequency component _fi . The water cooling system leakage monitoring method according to claim 3, characterized in that: using the wavelet transformation function ψ (x) to convert the scale function f _j (x) includes: The expression of the wavelet transform function ψ(x) is: ψ(x)＝φ(2x)-φ(2x-1) The water cooling system leakage monitoring method according to claim 4, characterized in that: using the wavelet transformation function ψ(x) to convert the scale function f _j (x) further includes: The scale function f _j (x) is converted to:

in,

in,

is the 2kth scale coefficient under the j-order scale,

is the 2k+1th scale coefficient under the j-order scale, k is the k-th value under the corresponding order,

is the kth scale coefficient under the j-1 order scale,

is the kth wavelet coefficient under the j-1 order scale. The water cooling system leakage monitoring method according to claim 5, characterized in that: the scale function f _j (x) obtained after conversion is recorded as f _j =w _j-1 +f _j-1 , and f _j is continued to be converted _-1 , until decomposed to order i, we get f _j ＝w _j-1 +w _j-2 +…+w _i +f _i Among them, i<j, w _j-1 , w _j-2 ,..., w _i are the high-frequency components of each order, and f _i is the i-order low-frequency component. The water cooling system leakage monitoring method according to claim 6, characterized in that: the expression of the i-order low-frequency component f _i is:

in,

is the kth scale coefficient under the i-order scale. The water cooling system leakage monitoring method according to claim 7, characterized in that: using low-order low-frequency components to reconstruct the high-order scale function includes: After reconstruction, we get the reconstruction function:

in,

is the kth scale coefficient under the i-order scale. The water cooling system leakage monitoring method according to claim 8, characterized in that: the reconstruction function is simplified to obtain:

in,

is the lth scale coefficient under the i+1 order scale; The reconstruction function is repeatedly upgraded from i+1 to i+2, ..., to j, thereby obtaining the scale function of f _i at the jth order. The water cooling system leakage monitoring method according to claim 9, characterized in that: the trend curve of the liquid level change is obtained according to the high-order scale function, and whether leakage is detected based on the trend curve of the liquid level change and the fixed value. Leakage includes: As a result, the scale function of f _i at order j is obtained. The expression of the scale function is:

in,

is the l-th scale coefficient under the j-order scale; The scale function is the trend curve of liquid level change, and the coefficient data is recorded

The maximum value is the A _max serial number n _max , the minimum value is the A _mi serial number n _mi , and L is the set leakage value. If A _max -A _min >L, and n _max <n _min , a leakage alarm will be issued.

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