Compressor manufacturing method and compressor life prediction method

Abstract

The method for manufacturing a compressor includes preparing a used compressor (Step S2). The method for manufacturing a compressor also includes estimating a deterioration state of a sliding part of the used compressor (Step S4). The method for manufacturing a compressor further includes manufacturing a new compressor by replacing the first refrigeration oil contained in the used compressor, the deterioration state of which satisfies a predetermined standard, with a new second refrigeration oil (Step S8).

Description

[Technical field]

[0001] The present disclosure relates to a method for manufacturing a compressor and a method for predicting a life span of a compressor. [Background technology]

[0002] For example, Japanese Patent Application Laid-Open Publication No. 2009-156504 (Patent Document 1) discloses a refrigeration cycle device that uses a refrigerant. This refrigeration cycle device includes an indoor unit, an outdoor unit, and refrigerant piping that connects the indoor unit and the outdoor unit. Japanese Patent Application Laid-Open Publication No. 2009-156504 discloses a method for reusing existing refrigerant piping in the refrigeration cycle device when changing from a conventional refrigerant to a different refrigerant. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2009-156504 A Summary of the Invention [Problem to be solved by the invention]

[0004] Generally, a compressor deteriorates as the refrigeration cycle device is used. From the viewpoint of environmental protection, it is preferable to reuse the deteriorated compressor.

[0005] The present disclosure has been made to solve the above-mentioned problems, and an object of the present disclosure is to manufacture a new compressor by reusing a used compressor and to predict the life of the newly manufactured compressor. [Means for solving the problem]

[0006] The manufacturing method of a compressor according to the present disclosure includes preparing a used compressor. The manufacturing method also includes estimating a deterioration state of a sliding part of the used compressor. The manufacturing method further includes manufacturing a new compressor by replacing a first refrigeration oil contained in the used compressor, the deterioration state of which satisfies a predetermined standard, with a new second refrigeration oil. Effect of the Invention

[0007] According to the present disclosure, it is possible to manufacture a new compressor by reusing a used compressor, and to predict the lifespan of the newly manufactured compressor. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating a configuration example of a refrigeration cycle device. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of a compressor. [Diagram 3] 1 is an example of a flowchart of a manufacturing method. [Figure 4] 4 is a flowchart showing the process of step S4 in FIG. 3. [Diagram 5] FIG. 13 is a diagram for explaining usage data. [Figure 6] FIG. 13 is a diagram showing an example of the relationship between goodness parameters and added materials. [Figure 7] FIG. 13 is a diagram showing an example of the relationship between goodness parameters and added materials. [Figure 8] 10 is a flowchart illustrating a new compressor life prediction method. [Figure 9] FIG. 11 is a diagram illustrating an example of correlation information. [Figure 10] FIG. 13 is a diagram showing an example of a relationship between a goodness parameter and an added material according to another embodiment. [Figure 11] FIG. 13 is a diagram showing an example of a relationship between a goodness parameter and an added material according to another embodiment. [Figure 12] 1 is a flowchart of a life prediction method. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals and their description will not be repeated. In addition, it is intended from the beginning that at least a part of the configurations in each embodiment will be used in appropriate combination.

[0010] Embodiment 1 [Example of refrigeration cycle equipment configuration] In the present disclosure, a method for manufacturing a compressor is disclosed. As an example, this compressor is used in a refrigeration cycle device. FIG. 1 is a diagram showing a configuration example of a refrigeration cycle device 100 of the present embodiment. The refrigeration cycle device 100 includes a compressor 200, a condenser 2, an expansion valve 3, and an evaporator 4. The compressor 200 is typically a hermetic refrigerant compressor.

[0011] The compressor 200 and the condenser 2 are connected by a pipe 5a. The condenser 2 and the expansion valve 3 are connected by a pipe 5b. The expansion valve 3 and the evaporator 4 are connected by a pipe 5c. The evaporator 4 and the compressor 200 are connected by a pipe 5d. The pipes 5a, 5b, 5c, and 5d form a refrigerant circuit 5. The refrigerant is sealed in the refrigeration cycle apparatus 100 (refrigerant circuit 5) so as to circulate therein.

[0012] When the refrigerant is sucked into the compressor 200, the compressor 200 compresses the refrigerant. The condenser 2 cools the gaseous refrigerant compressed by the compressor 200, so that the refrigerant becomes a high-pressure liquid refrigerant or a two-phase gas-liquid refrigerant. The expansion valve 3 reduces the pressure of the high-pressure liquid refrigerant or the two-phase gas-liquid refrigerant. The evaporator 4 heats the reduced pressure refrigerant, so that the refrigerant becomes a low-pressure gaseous refrigerant. The compressor 200 sucks in the low-pressure gaseous refrigerant and compresses it again. In this manner, the refrigerant circulates within the refrigeration cycle apparatus 100.

[0013] The blower 6 blows air to the condenser 2. The blowing of air from the blower 6 promotes the refrigerant flowing through the condenser 2 to exchange heat with the air and absorb or release heat. In addition, the blower 7 blows air to the evaporator 4. The blowing of air from the blower 7 promotes the refrigerant flowing through the evaporator 4 to exchange heat with the air and absorb or release heat.

[0014] The refrigeration cycle apparatus 100 may be, for example, an apparatus capable of performing both cooling and heating, an apparatus capable of performing cooling without performing heating, or an apparatus capable of performing heating without performing cooling.

[0015] [Compressor configuration example] Fig. 2 is a diagram showing a configuration example of a compressor 200. Fig. 2 shows an example of a rotary compressor. As shown in Fig. 2, the compressor 200 includes a shell 8, a compression mechanism 9, a suction pipe 10, a discharge pipe 11, a shaft 12, an oil reservoir 13, an oil supply hole 14, a bearing 16, a rotor 17, and a stator 18.

[0016] The compression mechanism 9 is disposed inside the shell 8. A suction pipe 10 and a discharge pipe 11 are connected to the compression mechanism 9. The suction pipe 10 is a pipe for allowing the refrigerant to flow into the inside of the compressor 200. The discharge pipe 11 is a pipe for discharging the refrigerant to the outside of the compressor 200. The compression mechanism 9 compresses the refrigerant that has entered the shell 8 from the suction pipe 10, and discharges it from the discharge pipe 11.

[0017] The compressor 200 includes a motor section. The motor section includes a shaft 12, a rotor 17, and a stator 18. The compressor 200 is driven by the motor section.

[0018] The compressor 200 has at least one sliding part. The sliding part is a portion where one part of the compressor 200 contacts another part. Typically, the one part is made of metal, and the other part is made of metal or an organic material. The sliding part is, for example, a contact part between a shaft and a bearing (a contact part between the shaft 12 and the bearing 16), a contact part between a vane and a piston, a tooth tip part of an orbiting scroll, and the like. The compressor 200 may include a number of sliding parts. In FIG. 2, a contact part between the shaft 12 and the bearing 16 is shown as an example of the sliding part 30.

[0019] The oil reservoir 13 stores refrigeration oil. The refrigeration oil is supplied to sliding parts inside the compression mechanism 9 by the action of a pump (not shown) through an oil supply hole 14. The refrigeration oil comes into contact with the refrigerant inside the compressor 200, so that part of the refrigerant dissolves in the refrigeration oil. The refrigeration oil is, for example, a polyvinyl ether-based refrigeration oil.

[0020] [Reusing compressors] In general, due to the high reliability of the refrigeration cycle apparatus 100 (for example, an air conditioner), even if the useful life (for example, the statutory useful life) of the compressor 200 has elapsed, the compressor 200 is often in a reusable state. Also, even if the useful life of the refrigeration cycle apparatus 100 has elapsed, it is rare for sludge to be generated. On the other hand, depending on the usage conditions of the refrigeration cycle apparatus 100 by the user, etc., wear on the sliding parts is large, and the compressor may be broken or on the verge of breaking down.

[0021] Even if the compressor 200 is operating normally when the refrigeration cycle apparatus 100 is collected, the compressor 200 may break down before reaching the legal lifespan due to further use. A compressor that breaks down before reaching the legal lifespan is also called a "defective machine." From the viewpoint of environmental protection, metal parts and the like of such defective machines can be extracted and reused.

[0022] On the other hand, there are compressors that can be reused until they reach the legal lifespan. Conventionally, metal parts and the like of such compressors have been extracted and reused in the same way as for defective compressors. However, it is preferable to reuse such compressors and return them to a state where they can be used again as new compressors.

[0023] The inventor discovered that it is preferable to specify the state of the sliding parts when determining whether or not a compressor can be reused. Furthermore, the inventor disassembled compressors and the like that were collected from the market and observed the sliding parts. Through this observation, the inventor discovered that compressors contain various sliding parts, such as sliding parts that are intact and sliding parts that are on the verge of seizing.

[0024] In this way, for example, if an operator dismantles a compressor and visually checks the state of the sliding parts, it is possible to determine whether the compressor can be reused. However, when dismantling a compressor to determine whether the compressor can be reused, the number of steps such as the dismantling and inspection of the compressor increases. Therefore, when dismantling a compressor to manufacture a new compressor, the cost may be higher than when manufacturing a compressor from new parts. For this reason, in order to determine whether the compressor can be reused, it is preferable to be able to clearly evaluate the state of the sliding parts without dismantling the compressor. The compressor manufacturing method of the present embodiment is a method that makes it possible to manufacture a new compressor by reusing a used compressor without dismantling the used compressor.

[0025] [Manufacturing method of compressor] FIG. 3 is an example of a flowchart of a manufacturing method for manufacturing a new compressor according to the present embodiment. At least some of the steps in the flowcharts of FIG. 3 and FIG. 4, FIG. 8, and FIG. 12 described below may be performed by an operator. That is, all of the steps in this flowchart may be performed by an operator. Also, some of the steps in this flowchart may be performed by an operator, and the remaining steps may be performed by a manufacturing device (such as a robot). Also, all of the steps in this flowchart may be performed by the manufacturing device. Below, an example in which an operator mainly performs all of the steps will be described.

[0026] First, in step S2, a used compressor 200 is prepared. Next, in step S4, a deterioration state of the sliding parts of this compressor 200 is estimated. The deterioration state of the sliding parts is typically the "wear state" of the sliding parts.

[0027] Next, in step S6, it is determined whether the estimated deterioration state satisfies a predetermined standard. If it is determined in step S6 that the deterioration state satisfies the predetermined standard (YES in step S6), it is determined in step S8 that the used compressor 200 is reusable.

[0028] Hereinafter, the refrigeration oil contained in the used compressor 200 is also referred to as "first refrigeration oil". In step S8, the first refrigeration oil contained in the used compressor 200 is discarded. After the first refrigeration oil of the used compressor 200 is discarded, new refrigeration oil is stored in the oil reservoir 13 (see FIG. 2). In this way, a new compressor 200 is manufactured. The new refrigeration oil is also referred to as "second refrigeration oil". A predetermined additive (such as an antioxidant) is mixed in the second refrigeration oil in advance.

[0029] On the other hand, in step S6, when it is determined that the deterioration state does not satisfy the predetermined standard (NO in step S6), it is determined that the used compressor 200 cannot be reused. Note that the metal part of the used compressor 200 determined to be unable to be reused can be reused.

[0030] Fig. 4 is a flowchart showing details of the process of step S4 (estimation of the deterioration state) in Fig. 3. In step S22, a goodness parameter is calculated. The goodness parameter is a parameter indicating the goodness of the sliding part of the compressor 200. In this embodiment, the larger the goodness parameter is, the better the sliding part of the compressor 200 is. A method of calculating the goodness parameter will be described later.

[0031] Next, it is determined whether the good parameter calculated in step S24 belongs to a normal range (a predetermined range). The normal range is a range that is determined in advance, and a method for determining the normal range will be described later. If the good parameter belongs to the normal range (YES in step S24), it is determined in step S26 that the deterioration state of the sliding part satisfies the predetermined standard. Then, returning to the flowchart of FIG. 3, it is determined as YES in step S6 of FIG. 3. On the other hand, if the good parameter does not belong to the normal range (NO in step S24), it is determined as the deterioration state of the sliding part does not satisfy the predetermined standard in step S26. Then, returning to the flowchart of FIG. 3, it is determined as NO in step S6 of FIG. 3.

[0032] [Good parameters] Next, the usage data used in the calculation of the good parameters described later will be described. FIG. 5 is a diagram for explaining this usage data. As shown in the example of FIG. 5, the usage data may include a first data group, a second data group, a third data group, and a fourth data group. The first data group and the second data group collectively correspond to the "refrigeration oil data" in the present disclosure. The "refrigeration oil data" is data related to the first refrigeration oil. The first data group corresponds to the "first data" in the present disclosure. The second data group corresponds to the "second data" in the present disclosure. The third data group corresponds to the "compressor data" in the present disclosure.

[0033] The first data group is data related to the goodness of the sliding part. In other words, the first data group is data indicating the goodness of the sliding part. As shown in FIG. 5, the first data group includes at least one of the amount of the first refrigeration oil and the amount of an additive to the first refrigeration oil. The additive is a substance added to the first refrigeration oil. The additive is, for example, an anti-wear agent. The anti-wear agent is, for example, tricresyl phosphate. Furthermore, a polyvinyl ether-based refrigeration oil to which tricresyl phosphate has been added as an anti-wear agent is used as the first refrigeration oil.

[0034] The inventors discovered that the sliding parts tend to be in better condition as the amount of the first refrigeration oil and the amount of the additive are increased. Therefore, the amount of the first refrigeration oil and the amount of the additive of the first refrigeration oil are adopted as the first data group.

[0035] As a method for acquiring the amount of the first refrigeration oil, for example, an operator cuts off a pipe (such as the suction pipe 10 and the discharge pipe 11 in FIG. 2) and recovers the first refrigeration oil from the cut portion. Then, the operator measures the amount of the recovered first refrigeration oil.

[0036] A sensor may be used as a method for acquiring the amount of the first refrigeration oil. For example, an ultrasonic sensor is used as the sensor. In a first method using an ultrasonic sensor, the ultrasonic sensor measures the time it takes for ultrasonic waves to be incident on the bottom surface of the used compressor 200, reflected by the liquid surface, and received by the ultrasonic sensor. Then, the ultrasonic sensor calculates a distance based on the time. This distance is a value corresponding to the liquid surface height of the contained first refrigeration oil. The amount of the first refrigeration oil is acquired based on this distance. The first method is disclosed in Japanese Patent No. 4123764.

[0037] In a second method using an ultrasonic sensor, the side surface of the compressor is palpated with the ultrasonic sensor, and the level of the first refrigeration oil is obtained from the signal shape. Specifically, in the second method, ultrasonic waves are applied from the ultrasonic sensor in the horizontal direction to the side surface of the used compressor 200. Then, the liquid level of the first refrigeration oil is obtained based on the difference in propagation characteristics between the gas refrigerant and the liquid refrigerant in which the first refrigeration oil is dissolved. The second method is disclosed in, for example, Japanese Patent No. 6808039.

[0038] In a method of using a capacitance sensor, the capacitance sensor is installed on the side of the used compressor 200. In general, the dielectric constant of the gas refrigerant gas is different from the dielectric constant of the refrigerant oil (including the state in which the refrigerant is dissolved). Based on this difference in dielectric constant, the liquid level of the first refrigerant oil is acquired. A method of using a capacitance sensor is disclosed, for example, in JP 2021-56134 A.

[0039] In a method using a spectrometer, the absorbance of at least one of the first refrigeration oil discharged from the used compressor 200 and the first refrigeration oil sucked into the used compressor 200 is measured by the spectrometer. Then, the amount of the first refrigeration oil is measured based on the measured absorbance and an absorption characteristic indicating a relationship between a predetermined absorbance and the amount of the first refrigeration oil. A method using a spectrometer is disclosed in, for example, JP 62-043523 A.

[0040] The amount of additive contained in the first data group (see FIG. 5) may be obtained, for example, by an analyzer. The analyzer may include a gas chromatograph or a liquid chromatograph.

[0041] The second data group is data related to the deterioration of the sliding part. In other words, the second data group is data showing the deterioration property of the sliding part. The second data group may be called a data group related to the deterioration of the refrigeration oil. As shown in FIG. 5, the second data group includes at least one of the total acid value of the first refrigeration oil and the hue value of the first refrigeration oil.

[0042] The total acid number of the first refrigeration oil is measured, for example, in accordance with “JIS K2501.” The total acid number is measured, for example, by indicator titration or potentiometric titration.

[0043] The hue value of the first refrigeration oil is measured, for example, by a hue sensor (such as an absorbance meter). More specifically, the absorbance of at least one of the three primary colors (RGB) of the first refrigeration oil is measured as the hue value. The second data group may include at least one of the viscosity and water concentration of the first refrigeration oil.

[0044] The third data group is data related to the deterioration of the used compressor 200. In other words, the third data group is data indicating the deterioration of the used compressor 200. As shown in Fig. 5, the third data group includes at least one of the noise of the driven used compressor 200, the vibration amount of the driven used compressor 200, and the amount of foreign matter mixed in the first refrigeration oil.

[0045] The noise of the used compressor 200 is acquired, for example, by driving the used compressor 200 before the piping is cut, and the noise is acquired by measurement with a sound level meter while the used compressor 200 is being driven. The amount of vibration of the used compressor 200 is acquired, for example, by driving the used compressor 200, and the amount of vibration is acquired by measurement with a vibration sensor while the used compressor 200 is being driven. The third data group may also include an input current of the used compressor 200. A method for measuring the vibration or input current of the used compressor 200 is disclosed, for example, in WO2019 / 239549.

[0046] The fourth data group is data that is unclear whether it is related to the deterioration degree of the sliding part. The fourth data group includes at least one of a remaining amount of an antioxidant and a water content. The antioxidant is added to the refrigeration oil. The water content is the water content of the refrigeration oil. The fourth data group may also include the viscosity of the first refrigeration oil.

[0047] [Method for determining good parameters] Next, a method for determining a calculation method for good parameters will be described in stages. First, in the first stage, for example, an operator classifies obtainable data. An example of classification is as shown in FIG.

[0048] Next, in the second stage, the worker selects at least one data from the first to fourth data groups. For example, the worker selects data from at least one of the first and second data groups. For a data group from which data is not selected, the data selected from the data group may be set to an arbitrary fixed value.

[0049] Next, in a third step, the operator calculates, as a first value, the product or sum of the quantities represented by the data selected from the first data group. Similarly, the operator calculates, as a second value, the product or sum of the quantities represented by the data selected from the second data group, the third data group, and the fourth data group.

[0050] Next, in the fourth step, the worker calculates the parameter by dividing the first value by the second value. Next, in the fifth step, the worker compares the calculated parameter with the state of the sliding part, and considers whether or not a correlation is obtained between the parameter and the wear amount (wear state) of the sliding part. As a result, if there is no desired correlation, the parameter is discarded, and if the desired correlation is obtained, the calculation method (calculation formula) of the parameter is determined as the calculation method of the good parameter.

[0051] [Formula for calculating goodness parameters] Next, a specific example of the calculation formula of the goodness parameter in step S22 of Fig. 4 will be described. Here, the first refrigeration oil amount V of the first data group, the additive amount A of the additive of the refrigeration oil of the first data group, the total acid value C of the first refrigeration oil of the second data group, and the hue value D of the first refrigeration oil of the second data group are used (selected) as data used for calculating the goodness parameter. The additive of the refrigeration oil of the first data group is a phosphorus-based anti-wear agent, more specifically, tricresyl phosphate. The hue value D of the first refrigeration oil is blue absorbance.

[0052] The goodness parameter W is calculated by the following formula (1). W = (V × A) / (C × D) (1) The numerator on the right side of the formula (1) is the "multiplication value (first multiplication value) of the amount V of the first refrigeration oil and the amount A of the phosphorus-based antiwear agent." Also, the denominator on the right side of the formula (1) is the "multiplication value (second multiplication value) of the total acid number C of the first refrigeration oil and the blue light absorbance D of the first refrigeration oil." Then, in the example of formula (1), the goodness parameter W is calculated by dividing the first multiplication value by the second multiplication value.

[0053] The value of the numerator in formula (1) is the multiplication value of the data values ​​belonging to the first data group regarding the quality of the sliding part. Therefore, this numerator value is a value that has a positive effect on the sliding part. The value of the denominator in formula (1) is the multiplication value of the data values ​​belonging to the second data group regarding the deterioration of the sliding part. Therefore, this denominator value is a value that has a negative effect on the sliding part. Therefore, it is clear that the larger the quality parameter W, the better the sliding part.

[0054] The calculation of the goodness parameter W using the formula (1) may be performed, for example, by an operator through mental calculation, or may be performed using an information processing device (PC: Personal Computer).

[0055] Next, modified examples of the calculation formula for the life parameter will be described. For example, the good parameter W may be set to A. Alternatively, the good parameter W may be set to V×A. Alternatively, the good parameter W may be set to A / C.

[0056] In the example of formula (1), the value related to the quality of the sliding parts is the numerator, and the value related to the deterioration of the first refrigeration oil is the denominator. However, the numerator and denominator of formula (1) may be reversed. The smaller the parameter calculated by such a formula, the better the quality of the sliding parts. As described above, the formula for calculating the parameters and the normal ranges are appropriately designed based on the analysis results of the recovered compressor.

[0057] [Normal range settings] Next, a method for setting the normal range will be described. First, a plurality of used compressors 200 are prepared. The used compressors 200 may be collected from the market. The used compressors 200 may also be manufactured under accelerated conditions that simulate a certain market for new compressors.

[0058] The worker calculates the value of the usage data (here, the amount of additive A) and the above-mentioned good parameter W for each of the prepared multiple used compressors 200. Then, the worker disassembles the used compressor 200 and observes the state of the sliding part. The observation of the sliding part may be performed only visually by the worker. When the observation of the sliding part is performed only visually by the worker, an empirical relative evaluation such as a multi-stage (e.g., three-stage) evaluation is added to each of the observed multiple used compressors. In addition, at least one of the wear amount of the sliding part and the surface roughness of the sliding part may be obtained by observing the sliding part. By obtaining a correlation between the state of the sliding part obtained by the observation by the worker and the good parameter W, the worker can predict the state of the sliding part from the good parameter W based on this correlation.

[0059] FIG. 6 is a diagram for explaining this correlation. FIG. 6 is also a diagram for setting the normal range. In the example of FIG. 6, an example of the relationship between the amount A of the phosphorus-based anti-wear agent (additive amount A) and the good parameter W is shown. In the example of FIG. 6, the vertical axis indicates A and the horizontal axis indicates W. Note that the amount A of the phosphorus-based anti-wear agent is a relative value in which the amount of the phosphorus-based anti-wear agent mixed in new refrigeration oil is set to "1". In other words, the amount A of the phosphorus-based anti-wear agent is a value between 0 and 1.

[0060] The white circles in Fig. 6 indicate normal wear of the sliding parts. Normal wear is wear that is deemed to be usable when the second refrigeration oil (new refrigeration oil) is charged into the compressor. Usable means, for example, that the compressor can be used to the extent that it can reach a product life that is acceptable to the market.

[0061] The black dots in Fig. 6 indicate abnormal wear of the sliding parts. The abnormal wear is wear to such an extent that it is determined that the compressor cannot be used even if the second refrigeration oil is filled in the compressor. The term "unusable" means, for example, that the compressor cannot be used to the extent that it can reach a product life acceptable to the market.

[0062] In addition, the determination of normal wear and abnormal wear was made by observing the sliding parts described above. In addition, a compressor including a sliding part with normal wear is also called a "normal compressor", and a compressor including a sliding part with abnormal wear is also called an "abnormal compressor". The white circles and black circles are defined in the same way in Figures 10 and 11 described below.

[0063] In Fig. 6, there is a compressor that is indicated by a black circle even though the good parameter W is large (see point S1 in Fig. 6). There is a high possibility that this compressor is in a failure mode caused by the inclusion of foreign matter (entanglement of foreign matter). The foreign matter is, for example, chips generated when cutting the pipes when the refrigeration cycle apparatus 100 is installed.

[0064] In this type of failure mode, the refrigeration oil is not deteriorated. Therefore, abnormal wear occurs even though the good parameter W is large. The reason for this abnormal wear is that in a compressor that is hardly used, the sliding parts are hardly deteriorated and the good parameter W is large, but foreign matter may be mixed in the compressor. Note that the foreign matter may be discharged to the outside when the compressor is used.

[0065] As shown in FIG. 6, when a compressor having an extremely small good parameter W and a compressor having an extremely large good parameter W include a sliding part with abnormal wear, the condition of the sliding part may be determined based on the average value and standard deviation of the good parameter W of normal compressors.

[0066] The solid line L1 in FIG. 6 indicates the average value Wa of the good parameters W of a normal compressor. The dashed line L2 indicates the value Wb obtained by adding the standard deviation to the average value Wa. The dashed line L3 indicates the value Wc obtained by subtracting the standard deviation from the average value Wa. In other words, the dashed lines L2 and L3 are the upper and lower boundary lines when "average value Wa±nσ" where n=1, where σ indicates the standard deviation. The range with Wb as the lower limit and Wc as the upper limit corresponds to the "normal range" in step S24 in FIG. 4.

[0067] Furthermore, the value of n may be set, for example, by an operator creating FIG. 6 so that an abnormal compressor is not included in the normal range. In the example of FIG. 6, n=1 is preferable. If n is greater than 1, an abnormal compressor may be determined to be a normal compressor. If n is less than 1, a normal compressor may be determined to be an abnormal compressor.

[0068] In this way, the normal range of the good parameter W is defined, so that the operator can clearly distinguish between a normal compressor and an abnormal compressor. In other words, if the operator analyzes the first refrigeration oil and calculates the good parameter W, the operator can determine whether the sliding state is normal or abnormal based on FIG. 6. Furthermore, the operator can determine whether the second refrigeration oil can be filled into the used compressor 200 to reach a lifespan acceptable to the market. In addition, when foreign matter is caught in the used compressor 200, the sliding part of the used compressor 200 may become abnormal even though the good parameter W is large. In order to determine that the used compressor 200 having such a sliding part is an abnormal compressor, it is preferable to set an upper limit value Wb for the good parameter W. By setting the upper limit value in this way, the operator can determine, for example, that a compressor containing foreign matter is an abnormal compressor. The normal range may be determined by the operator's visual inspection without using the average and standard deviation. In this manner, in the example of FIG. 6, the range in which the normal compressors indicated by the white circles are included but the abnormal compressors indicated by the black circles are not stepped on (the range between the dashed lines L3 and L2) is set as the normal range.

[0069] As described above, the formula for calculating the good parameter W may be set as the good parameter W=A. However, hereinafter, an example in which it is not appropriate to set the good parameter W=A will be described. FIG. 7 is a diagram for explaining such an example. In the example of FIG. 7, the vertical axis indicates the amount A of the phosphorus-based antiwear agent, and the horizontal axis indicates the good parameter W. The good parameter W is calculated by the formula (1).

[0070] In the example of Fig. 7, as shown by the white circles, the amount A of the phosphorus-based anti-wear agent in the normal compressor is distributed in the range of about 0.4 to 1.0, while the amount A of the phosphorus-based anti-wear agent in the abnormal compressor is widely distributed from 0 to 1.0.

[0071] 7, if the amount A of the phosphorus-based anti-wear agent is 0.4 or less, the used compressor 200 can be determined to be an abnormal compressor. However, even if the amount A of the phosphorus-based anti-wear agent is 0.4 to 1.0, the used compressor 200 cannot be determined to be a normal compressor because the range of 0.4 to 1.0 includes abnormal compressors.

[0072] That is, in the example of Fig. 7, the worker cannot determine whether the used compressor 200 is a normal compressor or an abnormal compressor based on the good parameter W=A. Therefore, the worker cannot determine whether the used compressor 200 is reusable or not. Therefore, in the case of Fig. 7, it is inappropriate to set the good parameter W=A. Note that, in Fig. 11 described later, it will be explained that it is preferable to set the good parameter W=A.

[0073] What data values ​​are appropriate as data values ​​used to calculate the goodness parameters depends on the classification of the used compressor 200. The classification of the used compressor 200 is defined by the type of the used compressor 200, the type of the first refrigeration oil contained in the used compressor 200, the use of the device having the used compressor 200, and the like.

[0074] The types of the used compressor 200 include, for example, a scroll compressor, a rotary compressor, and a screw compressor. The types of the first refrigeration oil include polyol ester oil, polyvinyl ether oil, polyalkylene glycol oil, and mineral oil. The applications of the device having the used compressor 200 include commercial use, household use, air conditioning use, and refrigeration use.

[0075] For example, it is preferable that the operator determine in advance the data values ​​and normal ranges used in calculating the good parameter W by creating the correlation diagrams of FIG. 6 and FIG. 7 for each of the above-mentioned sections.

[0076] [New compressor life prediction] Next, a method for predicting the life span of a new compressor manufactured by the method of Fig. 3 will be described. Fig. 8 is a flowchart showing the method for predicting the life span of a new compressor. First, in step S32, good parameters are prepared. These good parameters are parameters calculated by equation (1) or the like in the state of used compressor 200, which is the previous state of the new compressor whose life span is to be predicted.

[0077] Next, in step S34, a new compressor life is predicted based on the correlation information created in advance and the calculated good parameters.

[0078] Fig. 9 is a diagram showing an example of correlation information. In the example of Fig. 9, the horizontal axis indicates the goodness parameter W, and the vertical axis indicates the amount correlated with the lifespan. As a modified example, the vertical axis may be the value of the lifespan itself, instead of the amount correlated with the lifespan. In the example of Fig. 9, a positive correlation is shown.

[0079] 9, when the worker calculates the good parameter W in step S34, the worker identifies an amount having a correlation with the life corresponding to the good parameter W. Then, the worker identifies the life from the amount having a correlation with the life.

[0080] The process of step S34 may be manually performed by an operator. Alternatively, the process of step S34 may be performed, for example, by an operator inputting the goodness parameter W to an information processing device, which then executes a predetermined calculation to output (predict) the lifespan. The predetermined calculation is, for example, a calculation using AI (Artificial Intelligence).

[0081] Next, an example of a method for creating the correlation information in FIG. 9 will be described. An operator assembles a compressor for which the good parameter W has been calculated. Then, the operator checks the lifespan of each of a plurality of compressors having different states of the sliding parts by an accelerated test or the like. It is preferable that the time of the accelerated test is converted into the time of use in the market. Since it is assumed that a new compressor will be reused, new refrigeration oil is filled when the compressor is assembled.

[0082] Then, the worker plots the calculated good parameter W in association with the compressor life corresponding to the good parameter W. Based on this plot, the correlation information in FIG. 9 is created.

[0083] In addition, the required life of a new compressor is set as a life threshold value. Then, from a used compressor 200 for which a good parameter larger than a good parameter corresponding to the life threshold value has been obtained, an operator can manufacture a new compressor having a life longer than the life threshold value.

[0084] [Summary of this embodiment] In this embodiment, as shown in Fig. 3, an operator estimates the deterioration state of the sliding parts (step S4). Next, the operator judges whether or not the deterioration state meets a predetermined standard (step S6). Then, for a used compressor 200 whose deterioration state meets the predetermined standard, a new compressor is manufactured by replacing the first refrigeration oil contained in the used compressor 200 with new second refrigeration oil. Therefore, the manufacturing method of this embodiment allows an operator to manufacture a new compressor at low cost by reusing a used compressor.

[0085] Furthermore, estimating the deterioration state (step S4) includes calculating a good parameter based on refrigeration oil data (the first data group and the second data group in FIG. 5) related to the first refrigeration oil (step S22 in FIG. 4). Furthermore, estimating the deterioration state (step S4) includes estimating the deterioration state based on the good parameter (step S24). Therefore, the worker can estimate the deterioration state of the sliding parts from the viewpoint of the first refrigeration oil. Furthermore, for example, even if the used compressor 200 is a hermetic refrigerant compressor, the worker can estimate the deterioration state of the sliding parts without opening and closing the hermetic container.

[0086] The refrigeration oil data includes a first data group related to the condition of the sliding parts and a second data group related to the deterioration of the first refrigeration oil, so that the operator can estimate the deterioration state of the sliding parts from the viewpoint of the condition of the sliding parts and the deterioration of the first refrigeration oil.

[0087] The first data includes at least one of the amount of the first refrigeration oil and the amount of the additive of the first refrigeration oil, so that the operator can estimate the deterioration state of the sliding part from the viewpoint of at least one of the amount of the first refrigeration oil and the amount of the additive of the first refrigeration oil.

[0088] The second data includes at least one of the total acid value of the first refrigeration oil and the hue value of the first refrigeration oil, so that the operator can estimate the deterioration state of the sliding part from the viewpoint of at least one of the total acid value of the first refrigeration oil and the hue value of the first refrigeration oil.

[0089] In addition, estimating the deterioration state may include estimating the deterioration state based on the refrigeration oil data and the compressor data related to the deterioration of the used compressor. Therefore, the worker can estimate the deterioration state of the sliding part from the viewpoint of the deterioration of the used compressor 200.

[0090] 5, the compressor data includes at least one of the noise of the used compressor when driven, the vibration amount of the used compressor when driven, and the amount of foreign matter mixed in the first refrigeration oil. Therefore, the operator can estimate the deterioration state of the sliding parts from the viewpoint of at least one of the noise of the used compressor when driven, the vibration amount of the used compressor when driven, and the amount of foreign matter mixed in the first refrigeration oil.

[0091] The goodness parameter is calculated, for example, by the above formula (1). Therefore, the worker can estimate the deterioration state of the sliding portion by a relatively simple calculation.

[0092] Furthermore, according to the life estimation method of the present embodiment, as shown in Fig. 8, the life of the new compressor can be predicted based on the good parameters calculated in step S22. In other words, the worker can predict the life of the new compressor by using the good parameters calculated in step S22. Therefore, the worker can predict the life of the new compressor without disassembling the new compressor.

[0093] Embodiment 2 In the first embodiment, an example in which tricresyl phosphate is mainly used as the anti-wear agent is described. In the second embodiment, an example in which triphenyl phosphate is used as the anti-wear agent is described. In the second embodiment, the used compressor is a scroll-type hermetic compressor that was collected after performing accelerated tests under various conditions.

[0094] The formula for calculating the goodness parameter W in the second embodiment is the following formula (2). W = (V × A) / C (2) FIG. 10 is a diagram for explaining a method of determining a normal range in the second embodiment. FIG. 10 is a diagram showing the relationship between the amount of antiwear agent (additive amount A) which is tricresyl phosphate and the good parameter W calculated by the formula (2). The vertical axis of FIG. 10 indicates the additive amount A, and the horizontal axis indicates the good parameter W. The dotted line L4 in FIG. 10 indicates a value Wd. The value Wd is a value obtained by adding n (here, n=3) times the standard deviation of the good parameter W to the average value of the good parameter W of the abnormal compressor. As shown in FIG. 10, when the plots of the abnormal compressor are concentrated in a range where the good parameter W is small, the operator may not set an upper limit value as the normal range and may not set a lower limit value.

[0095] The above n=3 is a value set to separate an abnormal compressor from a normal compressor, and is adjusted depending on the state of separation between the two. Furthermore, when the purpose is to identify a normal compressor, it is desirable to set a normal range so that an abnormal compressor is not mixed in with the normal compressor, and there is no particular problem even if a normal compressor is mixed in with the abnormal compressor. Moreover, the goodness parameter W may be used to determine an abnormal compressor.

[0096] As described above, the normal range may be defined only by the lower threshold value without being defined by the upper threshold value, as shown in the second embodiment. Although not shown in the figure, the normal range may be defined only by the upper threshold value without being defined by the lower threshold value.

[0097] Embodiment 3 Fig. 11 is a diagram showing another example of the relationship between the additive amount A and the good parameter W. When the analysis results are as shown in Fig. 11, for example, the good parameter W may be set to A. Then, the normal range (lower threshold) of the good parameter W (additive amount A) is set to the value We indicated by the straight line L5. In this way, the good parameter W may be one piece of data shown in Fig. 5 (the additive amount A of the first data in this embodiment).

[0098] Embodiment 4 3 and 4, an operator can specify the state of the sliding parts of the compressor without disassembling the compressor. Therefore, an operator can specify the state of the sliding parts of the compressor 200 by using the good parameters of the compressor 200 that is still connected to the refrigeration cycle device 100 of FIG.

[0099] Therefore, in this embodiment, a description will be given of a life prediction method for the compressor 200 connected to the refrigeration cycle apparatus 100. Fig. 12 is an example of a flowchart of the life prediction method of this embodiment.

[0100] In step S42, the compressor 200 to be subjected to life prediction is prepared. In addition, in the case where the compressor 200 is connected to the refrigeration cycle apparatus 100, the refrigeration cycle apparatus 100 is prepared.

[0101] Next, in step S44, the good parameters of the compressor are calculated. For example, equation (1) is used as the calculation formula. Alternatively, other equations may be used. Then, in step S46, the life of the compressor 200 is predicted based on the good parameters and the correlation information created in advance.

[0102] Next, an example of a method for acquiring data used for calculating the goodness parameter W will be described. For example, an operator extracts a small amount of the first refrigeration oil from the compressor 200 through a valve for extracting the first refrigeration oil. Then, the operator acquires usage data by the above-mentioned method. Note that it is desirable that the amount of the first refrigeration oil extracted is an amount that does not affect the operation of the refrigeration cycle apparatus 100.

[0103] The correlation information used in step S46 is, for example, the correlation information shown in Fig. 9. In this manner, the correlation information is information indicating the correspondence between the good parameter W and the lifespan.

[0104] That is, the life prediction method disclosed in the fourth embodiment is expressed as follows: The life prediction method includes preparing a compressor (a compressor whose life is to be predicted), calculating a parameter (good parameter) based on refrigeration oil data related to a first refrigeration oil of the compressor, and predicting a life of the compressor based on the parameter.

[0105] In particular, the good parameter is calculated using the above-mentioned formula (1) or the like. In addition, in order to improve the accuracy of the life prediction, not only the first refrigeration oil amount of the first data group but also other data may be used to calculate the good parameter. The other data is, for example, at least one of the additive amount of the first refrigeration oil, the total acid number of the first refrigeration oil, and the hue value of the first refrigeration oil. According to the life prediction method of the present embodiment, for example, the life of the compressor 200, the target of the life prediction, can be predicted even if the compressor 200 is not separated from the refrigeration cycle device 100.

[0106] The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present disclosure is defined by the claims, not the above description, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0107] 2 condenser, 3 expansion valve, 4 evaporator, 5 refrigerant circuit, 5a, 5b, 5c, 5d piping, 6, 7 blower, 8 shell, 9 compression mechanism, 10 suction pipe, 11 discharge pipe, 12 shaft, 13 oil reservoir, 14 oil supply hole, 16 bearing, 17 rotor, 18 stator, 30 sliding part, 100 refrigeration cycle device, 200 compressor.

Claims

1. Providing a used compressor; Estimating a deterioration state of a sliding portion of the used compressor; manufacturing a new compressor by replacing the first refrigerating machine oil contained in the used compressor whose deterioration state satisfies a predetermined standard with a new second refrigerating machine oil; determining that the new compressor will not be manufactured from the used compressor whose deterioration state does not satisfy the predetermined standard.

2. The estimating of the degradation state includes: Calculating a parameter based on refrigeration oil data regarding the first refrigeration oil; and estimating the deterioration state based on the parameter.

3. The refrigeration oil data is First data on the quality of the sliding portion; and and second data relating to deterioration of the first refrigeration oil. The method for manufacturing a compressor according to claim 2, further comprising: estimating the deterioration state based on at least one of the following data:

4. The first data is An amount of the first refrigeration oil; and an amount of an additive to the first refrigeration oil.

5. The second data is The total acid value of the first refrigerating machine oil; and a hue value of the first refrigeration oil.

6. The method for manufacturing a compressor according to any one of claims 2 to 4, wherein estimating the deterioration state includes estimating the deterioration state based on the refrigeration oil data and compressor data related to deterioration of the used compressor.

7. The compressor data is the noise of the used compressor being driven; The vibration amount of the driven used compressor; and and an amount of foreign matter mixed in the first refrigeration oil.

8. The refrigeration oil data is An amount of the first refrigeration oil; The amount of a phosphorus-based antiwear agent mixed in the first refrigeration oil; The total acid value of the first refrigerating machine oil; The blue absorbance of the first refrigeration oil; 3. The method for manufacturing a compressor according to claim 2, wherein the parameter is calculated by dividing a multiplied value of an amount of the first refrigeration oil and an amount of the phosphorus-based wear inhibitor by a multiplied value of the total acid number and the blue light absorbance.

9. A compressor life prediction method comprising: predicting a life of the new compressor manufactured by the compressor manufacturing method according to any one of claims 2 to 4, based on the parameters.

Images