Directional valve failure prediction system and method, directional valve failure inspection system and inspection method

Abstract

The failure prediction system for a directional change valve of the present invention includes a data acquisition unit that repeatedly detects operation times of a plurality of directional change valves that communicate with a cylinder having a piston rod and change the supply direction of a working fluid supplied to the cylinder to change the operating direction of the piston rod over an elapsed time of equipment operation, and acquires a plurality of operation time data for each directional change valve, a deterioration index value calculation unit that calculates deterioration index values ​​of a plurality of statistical deterioration indexes that can represent a failure of the directional change valve based on the operation time data, and a determination unit that ranks the deterioration index values ​​of the statistical deterioration indexes calculated for each directional change valve according to their magnitude, assigns a predetermined score to a directional change valve having a top value equal to or higher than a predetermined range among the ranked deterioration index values, and determines a directional change valve that is expected to fail based on the sum of the predetermined scores.

Description

[Technical field]

[0001] The present invention relates to a system and method for predicting failure of a directional valve.

[0002] The present invention also relates to a fault inspection system and method for a directional control valve, which inspects and replaces a directional control valve whose fault is predicted by the above-mentioned fault prediction system and method.

[0003] This application claims the benefit of priority based on Korean Patent Application No. 10-2022-0112023 dated September 5, 2022, and all contents disclosed in the documents of said Korean patent application are incorporated herein by reference. [Background technology]

[0004] In recent years, rechargeable secondary batteries have been widely used as energy sources for wireless mobile devices. Secondary batteries are also attracting attention as energy sources for electric vehicles and hybrid electric vehicles, which have been presented as a solution to address air pollution caused by existing gasoline and diesel vehicles that use fossil fuels. Therefore, the types of applications using secondary batteries are becoming increasingly diverse due to the advantages of secondary batteries, and secondary batteries are expected to be applied to many more fields and products in the future.

[0005] To manufacture such a secondary battery, many detailed processes are performed, such as a process of coating an active material on a current collector and rolling it to manufacture the components of the positive and negative electrodes, a notching process to form an electrode tab, an electrode assembly manufacturing process of manufacturing an electrode assembly by stacking and / or folding the positive electrode-separator-negative electrode, a welding process to weld the electrode tab and electrode lead, a process to cut the electrode assembly for stacking, and a charge / discharge process to give characteristics before shipping. During each of the above processes, various types of actuators are used to operate materials, each detailed device, or other systems.

[0006] An actuator is a device for driving a movable body such as an instrument, and includes a motor, a cylinder, and the like. The cylinder of the actuator includes a cylindrical cylinder body and a piston rod housed in the cylinder body and equipped with a piston at its tip, and applies a driving force to the movable body by linear movement of the piston rod in the cylinder body. Meanwhile, the linear movement of the piston rod can be performed by the pressure of a working fluid (hydraulic or pneumatic) supplied from the outside. That is, when a working fluid (oil, air, etc.) is supplied from a working fluid supply source to the cylinder body, the piston rod moves linearly due to the pressure of the supplied working fluid. At this time, the linear movement direction of the piston rod can be changed by changing the supply direction of the working fluid. A direction change valve is used as a device for changing the supply direction of the working fluid.

[0007] A directional control valve is a valve disposed in a flow path to change the flow direction of a working fluid. Specifically, the directional control valve includes a plurality of ports in which a flow path is formed through which the working fluid flows in or out, a case in which the plurality of ports are installed and in which an internal flow path is formed that communicates with the flow paths of the plurality of ports, a spool disposed in the internal flow path of the case and that closes or opens the plurality of ports to block a part of the internal flow path, thereby controlling the flow direction of the working fluid, and a spool driver that applies a driving force to the spool so that the spool can move within the internal flow path of the case. The directional control valve forms a flow path by communicating with the working fluid supply source and the cylinder body through the ports, and the spool closes some of the ports and blocks a part of the internal flow path when the working fluid flows along the flow path, thereby determining the flow direction of the working fluid.

[0008] If there is an abnormality in the operation of the cylinder, piston rod, or directional change valve, the movable body cannot be moved according to the set value, which causes abnormal operation of the factory production line and defective products. In particular, if a serious abnormality occurs in any one of the cylinder, piston rod, or directional change valve, it may cause a situation where the operation of a part or the whole of the factory's manufacturing system is interrupted (breakdown).

[0009] In order to prevent the interruption of the operation of the factory manufacturing system, attempts have been made to predict the cylinder failure before the cylinder failure occurs. However, when a failure occurs in a directional control valve that changes the flow direction of the working fluid, an error occurs in which the cylinder is determined to be a faulty cylinder even if the cylinder is normal. Therefore, in order to more fundamentally prevent the interruption of the operation of the factory manufacturing system, it is necessary to grasp the failure or abnormality symptoms of the directional control valve before the directional control valve fails.

[0010] Conventionally, valve abnormalities have been detected by comparing the number of times an opening / closing operation signal is applied to an individual valve with the number of times the valve actually opens and closes (Patent Document 1). However, the opening and closing of a valve may occur even if the operation is delayed due to the occurrence of an abnormality or failure of the valve. In other words, errors may occur when detecting and predicting valve abnormalities based on the number of times the valve opens and closes. Therefore, a technology is needed that can select factors or indicators that can represent valve operation abnormalities or failures, and predict the occurrence of failures based on the factors or indicators. [Prior art documents] [Patent documents]

[0011] [Patent Document 1] Japanese Patent Publication No. 2013-168131 Summary of the Invention [Problem to be solved by the invention]

[0012] The present invention has been devised to solve the above-mentioned problems, and has an object to provide a failure prediction system and method for a directional control valve that selects a statistical deterioration index that can represent a failure of a directional control valve and can predict the presence or absence of a failure of the directional control valve before the failure actually occurs based on the deterioration index.

[0013] Another object of the present invention is to provide a fault inspection system and method for a directional control valve, which inspects and replaces a directional control valve whose fault is predicted by the above-mentioned fault prediction system and method. [Means for solving the problem]

[0014] The present invention provides a directional control valve failure prediction system for solving the above problems, comprising: a data acquisition unit that repeatedly detects operation times of a plurality of directional control valves that communicate with a cylinder having a piston rod and change the supply direction of a working fluid supplied to the cylinder to change the operating direction of the piston rod over an elapsed time of equipment operation, and acquires a plurality of operation time data for each directional control valve; a deterioration index value calculation unit that calculates deterioration index values ​​of a plurality of statistical deterioration indexes that can represent failure of the directional control valve based on the operation time data; and a determination unit that ranks the deterioration index values ​​of the statistical deterioration indexes calculated for each directional control valve according to their magnitude, assigns a predetermined score to directional control valves having upper values ​​above a predetermined range among the ranked deterioration index values, and determines which directional control valves are predicted to fail based on the sum of the predetermined scores.

[0015] As a specific example, the data acquisition unit may acquire data by selecting one or more of a first time it takes for the piston rod to start moving forward in response to an operation signal of the directional change valve, a second time it takes for the piston rod to start moving backward in response to an operation signal of the directional change valve, and a combined time of the first time and the second time as the operation time of the directional change valve.

[0016] As a more specific example, the data acquisition unit may regard the first time and the second time as separate and independent pieces of operating time data, and acquire two pieces of operating time data, the first time and the second time, during one reciprocating motion of the piston rod provided in one of the cylinders.

[0017] As one example, the statistical deterioration indicators may be two or more selected from the group consisting of the mean, standard deviation, first quartile, median, third quartile, skewness, and kurtosis of the operating time data of each directional control valve.

[0018] As another example, the statistical deterioration index may be one or more selected from the group consisting of the mean, standard deviation, first quartile, median, third quartile, skewness, and kurtosis of the operating time data of each directional control valve, and the change value of one or more statistical deterioration indexes selected from the above group.

[0019] As an example, the deterioration index value of the statistical deterioration index may be calculated based on operation time data of each directional control valve operated for a specific time interval after the directional control valve is used repeatedly for a certain period of time.

[0020] As a specific example, the data acquisition unit may group the operation time data of each directional control valve for each unit time interval during an inspection period consisting of a plurality of unit time intervals into separate operation time data groups, and the deterioration index value calculation unit may calculate the deterioration index value of each directional control valve for each operation time data group.

[0021] As one example, the determination unit may rank the end-of-life deterioration index values ​​calculated for a group of operating time data for a specific unit time period after operating for a predetermined unit time period during the inspection period for each directional control valve, assign a predetermined score to a directional control valve having a top value above a predetermined range among the ranked end-of-life deterioration index values, and determine the directional control valve predicted to fail based on the sum of the predetermined scores.

[0022] As another example, the determination unit may rank each directional control valve to obtain an average terminal deterioration index value obtained by averaging each terminal deterioration index value calculated for a group of operating time data for a specific unit time period after operating for a predetermined unit time period during the inspection period, assign a predetermined score to a directional control valve having a top value above a predetermined range among the ranked average terminal deterioration index values, and determine a directional control valve that is predicted to fail based on the sum of the predetermined scores.

[0023] As another example, an initial deterioration index value for a group of operating time data in an initial unit time section of the inspection period, or a difference value obtained by subtracting the final deterioration index value from the average value of the initial deterioration index values ​​obtained for the group of operating time data in the initial unit time section, may be introduced as an additional statistical deterioration index that can represent a failure of the directional control valve.

[0024] As another example, the initial deterioration index value for the group of operating time data in the initial unit time section of the inspection period, or the difference value obtained by subtracting the average final deterioration index value from the average value of the initial deterioration index values ​​obtained for the group of operating time data in the initial unit time section, may be introduced as an additional statistical deterioration index that can represent a failure of the directional control valve.

[0025] In another aspect of the present invention, a system for inspecting a directional control valve includes the directional control valve failure prediction system, and an inspection unit that measures whether or not there is an air leak in a directional control valve that has been determined to be a suspected faulty directional control valve by the determination unit.

[0026] In another aspect of the present invention, a method for predicting a failure of a directional change valve includes the steps of: repeatedly detecting operation times of a plurality of directional change valves, the directional change valves communicating with a cylinder having a piston rod and changing a direction of operation of the piston rod by changing a supply direction of a working fluid supplied to the cylinder, over an elapsed time of equipment operation, and acquiring a plurality of operation time data for each directional change valve; selecting a plurality of statistical deterioration indicators capable of representing a failure of the directional change valves, and calculating deterioration index values ​​of the selected statistical deterioration indicators based on the operation time data; ranking each deterioration index value for each directional change valve according to its size; and assigning a predetermined score to a directional change valve having an upper value equal to or higher than a predetermined range among the ranked deterioration index values, and determining a directional change valve predicted to fail based on a sum of the predetermined scores.

[0027] As a specific example, a change value of one or more statistical deterioration indicators selected from the plurality of statistical deterioration indicators may be introduced as an additional statistical deterioration indicator for determining a predicted directional control valve failure.

[0028] According to another aspect of the present invention, a method for inspecting a directional control valve includes inspecting a directional control valve determined to be a directional control valve suspected to be faulty by the method for predicting a fault in the directional control valve, and replacing a directional control valve found to be faulty by the inspection. Effect of the Invention

[0029] According to the present invention, it is possible to predict whether or not a directional control valve will fail before it actually fails, and replace a directional control valve that is likely to fail in advance. Therefore, by removing a directional control valve that is predicted to fail in advance, it is possible to prevent a situation in which the entire factory or manufacturing system is interrupted (breakdown).

[0030] In addition, by predicting the failure of the directional control valve, which is the driving force of the cylinder drive, before predicting the failure of the cylinder, it is possible to reduce judgment errors that occur when judging the failure of the cylinder. Also, by predicting the failure of the directional control valve, which has operation time data that is much shorter than the operation time data when predicting the failure of the cylinder, it is possible to significantly shorten the time required for failure prediction judgment.

[0031] In addition, the present invention can statistically calculate the operation time or more that can represent a failure of the directional control valve, thereby making it possible to more accurately predict an abnormality in the directional control valve.

[0032] Furthermore, the present invention can significantly reduce the number of directional control valves to be inspected, thereby significantly reducing the number of personnel, workload, and time required for maintenance. [Brief description of the drawings]

[0033] [Figure 1] 10 is a schematic diagram showing how a piston rod moves linearly by changing the supply direction of the hydraulic fluid using a direction change valve; FIG. [Diagram 2] FIG. 2 is a schematic diagram showing a location where a failure occurs in a directional control valve. [Diagram 3] 1 is a graph showing the cumulative operating time distribution of normal and abnormal directional valves. [Figure 4] FIG. 2 is a block diagram for explaining the concept of failure occurrence prediction according to the present invention. [Diagram 5] FIG. 1 is a schematic diagram illustrating a system for predicting failure of a directional valve according to an embodiment of the present invention. [Figure 6] 1 is a graph showing a state in which operation time data of a directional control valve is grouped and statistically visualized. [Figure 7] FIG. 2 is a schematic diagram showing a failure prediction mechanism of a directional valve failure prediction system according to an embodiment of the present invention. [Figure 8] FIG. 1 is a schematic diagram illustrating an example of a statistical degradation indicator based on the operation time of a diverter valve. [Figure 9]FIG. 11 is a schematic diagram showing a failure prediction mechanism of a failure prediction system for a directional control valve according to a modified embodiment of the present invention. [Figure 10] FIG. 10 is a schematic diagram illustrating a failure prediction system for a directional control valve according to another embodiment of the present invention. [Figure 11] FIG. 2 is a schematic diagram showing changes in a statistical degradation indicator; [Figure 12] FIG. 13 is a schematic diagram showing a failure prediction mechanism of a directional control valve failure prediction system according to another embodiment of the present invention. [Figure 13] FIG. 13 is a schematic diagram showing a failure prediction mechanism of a directional control valve failure prediction system according to another embodiment of the present invention. [Figure 14] 1 is a schematic diagram showing a fault inspection system for a directional control valve according to the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0034] The present invention will be described in detail below. Before that, the terms and words used in the specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings, but should be interpreted as meanings and concepts that are consistent with the technical idea of ​​the present invention based on the principle that the inventor can appropriately define the concepts of the terms in order to best describe his own invention.

[0035] In this application, the terms "comprise" and "have" are intended to specify the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, and should be understood as not precluding the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof. In addition, when a part such as a layer, film, region, or plate is described as being "on" another part, this includes not only the case where it is "directly on" the other part, but also the case where there is another part in between. Conversely, when a part such as a layer, film, region, or plate is described as being "under" another part, this includes not only the case where it is "directly under" the other part, but also the case where there is another part in between. In addition, in this application, being "on" may include not only the case where it is located on the top, but also the case where it is located on the bottom.

[0036] FIG. 1 is a schematic diagram showing how a piston rod changes direction and moves linearly in response to the supply direction of a working fluid changed by a direction change valve.

[0037] 1(a) and 1(b), the directional control valve 10 communicates with a hydraulic fluid source 30 and a cylinder 20 to change the supply direction of the hydraulic fluid supplied from the hydraulic fluid source 30 to the cylinder 20. The hydraulic fluid may be oil or air, and the hydraulic fluid source 30 may be a fluid storage tank or a pump. The directional control valve 10 includes a plurality of ports 11 having a flow path 111 through which the hydraulic fluid flows in or out, a case 12 in which the plurality of ports 11 are installed and in which an internal flow path 121 communicating with the flow paths of the plurality of ports 11 is formed, a spool 13 disposed in the internal flow path 121 of the case and controlling the flow direction of the hydraulic fluid by closing or opening the plurality of ports and blocking a part of the internal flow path, and a spool driver 15 applying a driving force to the spool 13 so that the spool 13 can move within the internal flow path 121 of the case 12. The spool 13 may further include a packing 14 for shielding.

[0038] The spool driver 15 may be a solenoid coil and a movable plunger that is moved by the solenoid coil. Alternatively, it may be a pilot valve that is opened and closed by the solenoid coil and the movable plunger to supply high-pressure fluid to the spool. Both are the same in that the movable plunger moves linearly due to the magnetic field generated by the solenoid coil. However, the difference is that in the former, the movable plunger is directly connected to the spool 13 and the spool 13 moves due to the linear movement of the movable plunger, and in the latter, when the movable plunger opens the pilot valve, the spool 13 moves due to the pressure of the high-pressure fluid that flows in through the pilot valve. The spool driver 15 may be disposed at one end or both ends of the case 12. When the spool driver 15 is disposed at only one end of the case 12, an elastic body (not shown) such as a spring may be disposed at the other end of the case 12. In this case, when the spool driving unit 15 is turned on by an on operation signal automatically or manually issued by the control unit, the spool 13 resists the pressing force of the elastic body and can move toward the elastic body. Conversely, when the spool driving unit 15 is turned off by an off operation signal from the control unit or the like, the spool 13 can move toward the spool driving unit 15 by the restoring force of the elastic body. The operation signal is an electric signal applied by the control unit to a solenoid coil.

[0039] FIG. 1(a) is a schematic diagram showing the forward movement of the piston rod 21 by the operation of the directional control valve 10 having five ports 11a-11e. First, the spool 13 is moved to the left on the internal flow path 121 by applying an operation signal to the spool driver 15. The spool driver 15 may be operated remotely by automation or directly by an operator for equipment inspection or maintenance. When the spool driver 15 is operated remotely, the operation signal may be a remote signal applied to the spool driver 15 via a process control unit (not shown). When the operator directly operates the spool driver 15, the operation signal may be an on / off operation of the valve power source by the operator. Meanwhile, when the movement of the spool 13 is completed, the flow direction of the working fluid is regulated by the spool 13, and the working fluid flows from the fourth port 11d to the second port 11b. The working fluid is supplied through the second port 11b and pressurizes the piston rod 21 to the left, so that the piston rod 21 moves forward. The operation time of the direction-changing valve in the present invention means that the supply direction of the hydraulic fluid is changed from the start of the operation signal, and the changed supply direction of the hydraulic fluid is maintained until the hydraulic fluid is sufficiently supplied to provide the piston rod with hydraulic pressure capable of linear motion.

[0040] In this specification, the actuation time or time taken to actuate a directional control valve refers to the time taken from the initiation of an actuation signal applied to the spool drive until the spool is actuated to transmit sufficient hydraulic pressure to the piston rod so that the piston rod can be redirected.

[0041] 1(b) is a schematic diagram showing that the piston rod 21 moves backward by the operation of the directional control valve 10 having five ports 11a-11e. First, an operation signal is applied to the spool driver 15 to move the spool 13 to the right on the internal flow path 121. When the movement of the spool 13 is completed, the flow direction of the working fluid is restricted by the spool 13, and the working fluid flows from the fourth port 11d toward the first port 11a. The working fluid is supplied via the first port 11a and pressurizes the piston rod 21 to the right, causing the piston rod 21 to move backward.

[0042] The left and right movement of the spool 13 is merely an example, and the piston rod 21 may move backward when the spool 13 moves leftward depending on the design of the directional control valve. In addition, in Fig. 1(a) and Fig. 1(b), the directional control valve 10 having five ports 11a-11e has been described for the sake of convenience, but the present invention is not necessarily limited thereto.

[0043] FIG. 2 is a schematic diagram showing a location where a failure occurs in the directional control valve 10.

[0044] As shown in FIG. 2, the main causes of failure of the directional control valve 10 can be classified into (1) leakage of hydraulic fluid due to damage to the port 11, (2) leakage of hydraulic fluid due to deterioration of the packing 14 of the spool 13, (3) leakage of hydraulic fluid due to poor fastening between the cylinder 20 or the hydraulic fluid supply source 30 and the directional control valve 10, and (4) leakage of hydraulic fluid due to damage to the case 12. Even if leakage occurs as described above, the directional control valve can still perform a switching operation (or an opening and closing operation). However, when leakage of hydraulic fluid occurs as described above, additional hydraulic fluid must be supplied to achieve a pressure for moving the piston rod 21. Therefore, even if an operation signal is applied to the spool driver 15, the piston rod 21 does not start moving until additional hydraulic fluid is supplied. In other words, the operational deterioration of the directional control valve 10 can be expressed as a delay in starting the operation of the piston rod 21.

[0045] FIG. 3 is a graph showing the operating time distribution of normal and abnormal directional valves.

[0046] FIG. 3(a) is a graph showing the number of times that the operation time of a normal directional change valve is measured for a predetermined time. As shown in the figure, in the case of a normal directional change valve, a normal distribution curve appears in the normal range (about 0.2 seconds to 0.5 seconds). In contrast, FIG. 3(b) is a graph showing the number of times that the operation time of an abnormal directional change valve is measured for a predetermined time. As shown in the figure, in the case of an abnormal directional change valve, a non-normal distribution is shown in a range outside the normal range (more than about 0.5 seconds). In this way, the operation time of the directional change valve is closely related to the deterioration of the operation of the directional change valve. The present invention is characterized in that the operation time of such a directional change valve is selected as a factor that can represent the failure of the directional change valve, and as described later, a statistical deterioration index and its deterioration index value are calculated based on the operation time data of the directional change valve, and the deterioration index value is used to predict a directional change valve that is expected to fail. The statistical deterioration index is based on operation time data that can represent the failure of the directional change valve, and can similarly represent the failure of the directional change valve. In this respect, it is different from the conventional technology that diagnoses a fault in a directional control valve simply by the number of times it is opened and closed.

[0047] FIG. 4 is a block diagram for explaining the concept of failure occurrence prediction according to the present invention.

[0048] As shown in Figure 4(a), the parts of the directional control valve show abnormal symptoms before a breakdown occurs. If the breakdown of the parts cannot be predicted from such abnormal symptoms, a breakdown will occur as a result, which may cause a partial or total breakdown of the factory's manufacturing system (BM). Replacing parts after a breakdown is very uneconomical and reduces manufacturing efficiency.

[0049] Meanwhile, as shown in FIG. 3(b), the present invention can detect abnormal symptoms in advance when abnormal symptoms occur in the directional change valve parts by using the directional change valve failure prediction system or directional change valve failure prediction method using the directional change valve failure prediction algorithm specific to the present invention. That is, it is possible to predict the failure of the directional change valve in advance before the failure occurs, check the directional change valve parts for abnormality, and replace the problematic parts, thereby preventing the system operation from being interrupted as in the past. The technical idea of ​​the present invention is not to diagnose the failure of the directional change valve or to analyze the cause of the failure, but to predict the directional change valves that are expected to fail or have a high probability of failure before the directional change valve fails. Therefore, even a normal directional change valve that is not currently a failed directional change valve can be determined as a directional change valve that is expected to fail. In this respect, it is different from the technology that diagnoses the failure or determines only the normality of the directional change valve.

[0050] The present invention will be described in detail below.

[0051] (First embodiment) FIG. 5 is a schematic diagram illustrating a failure prediction system for a directional valve according to one embodiment of the present invention.

[0052] The directional change valve failure prediction system 100 of the present invention includes a data acquisition unit 110 that repeatedly detects operation times of a plurality of directional change valves 10 that communicate with a cylinder 20 having a piston rod 21 and change the operating direction of the piston rod 21 by changing the supply direction of the working fluid supplied to the cylinder 20 over the elapsed time of equipment operation, and acquires a plurality of operation time data for each directional change valve 10, a deterioration index value calculation unit 120 that calculates a deterioration index value of a statistical deterioration index that can represent a failure of the directional change valve 10 based on the operation time data, and a determination unit 130 that ranks the calculated deterioration index values ​​for each directional change valve 10 according to their magnitude, and determines a directional change valve 10 having a higher value than a predetermined range among the ranked deterioration index values ​​as a directional change valve 10 that is expected to fail.

[0053] The operation time of the directional control valve 10 referred to in the present invention includes at least one of the first time taken for the piston rod 21 to start moving forward when the supply direction of the working fluid is changed by the operation signal of the directional control valve 10, the second time taken for the piston rod 21 to start moving backward when the supply direction of the working fluid is changed by the operation signal of the directional control valve 10, and the sum of the first and second times. As shown in FIG. 2, when the operation of the directional control valve 10 deteriorates, not only the first and second times at which the piston rod 21 starts moving forward or backward, but also the sum of the first and second times are delayed. Therefore, not only the first and second times, but also their sum, or a combination of the first and the sum, or a combination of the second and the sum, can be used as operation time data on which the deterioration index value is calculated. In this embodiment, for the convenience of calculation, the first and the second times are treated as separate and independent operation time data. That is, since the time when the piston rod 21 starts moving forward and the time when the piston rod 21 starts moving backward by the directional control valve are generally almost the same, the first time data and the second time data obtained during one reciprocating motion of the piston rod 21 are regarded as separate data. As a result, two operation time data can be obtained during the reciprocating motion of one piston rod 21. For example, assuming that there are 50 directional control valves to be predicted as failures, the directional control valve must operate twice to reciprocate the piston rod of each cylinder, so 100 operation time data can be obtained during the reciprocating motion of each piston rod. That is, in this embodiment, the first time and the second time are regarded as one statistical data, respectively, to determine the direction change valve predicted to be failed. Of course, only one of the first time or the second time can be obtained as operation time data to predict failure. However, when both data are obtained, data covering all the operations of the directional control valve related to the reciprocating motion of the piston rod 21 is included, so that it is advantageous that the failure judgment of the directional control valve can be performed more strictly and the failure predictability can be improved.

[0054] The operation time data can be acquired, for example, by sensors S1 and S2 installed at the start and end of the cylinder 20 housing as shown in FIG. 5. The sensor S1 installed at the end detects when the piston rod 21 reaches the forward end. Similarly, it detects when the piston rod 21 leaves the forward end. The sensor S2 installed at the start end detects when the piston rod 21 reaches the backward end. Similarly, it detects when the piston rod 21 leaves the backward end. The above sensors can be installed inside or outside the cylinder. The above sensors can be, for example, limit switches that indicate the position of the piston at the tip of the piston rod by switching on / off.

[0055] The data acquiring unit 110 may acquire the time elapsed from when an operation signal is applied to the spool driving unit 15 until the sensors S1 and S2 detect the separation of the piston rod 21 as operation time data. For example, the time elapsed from when an operation signal is applied to the spool driving unit 15 until the sensor S2 installed at the start end generates a piston rod separation detection signal may be the first time. Also, the time elapsed from when an operation signal is applied to the spool driving unit 15 until the sensor S1 installed at the end end generates a piston rod separation detection signal may be the second time. The directional control valves operate continuously throughout the equipment operation time. The reciprocating motion of the cylinder is performed by the operation of the directional control valve. Therefore, when one cylinder reciprocates, the data acquiring unit 110 may acquire the first time and the second time as data for the number of reciprocating motions. Since the present invention determines the direction change valves expected to fail by relatively comparing the operation times of each directional control valve, a plurality of pieces of operation time data are acquired for each directional control valve. To this end, the data acquisition unit 110 may include a data collection device and a database for storing data.

[0056] The operation time data is obtained for each directional valve over the operation time of the equipment. For example, if one cylinder reciprocates 1,800 times per hour, 3,600 operation time data can be obtained per hour, 10,800 data can be obtained in 3 hours, and 86,400 data can be obtained after 24 hours. If the directional valve operates repeatedly for 30 days, 86,400 x 30 operation time data can be obtained. If a statistical index is calculated using such a large amount of data at once, the amount of data to be processed becomes excessively large. In this case, a large load is placed on the algorithm or program for failure prediction, and it is not possible to quickly determine a failure. Furthermore, if the number of directional valves to be predicted as failure targets increases, the amount of data to be processed increases further, and the above problem becomes more severe.

[0057] Therefore, when acquiring data for failure prediction and calculating the degradation index value using the data, a so-called grouping technique is used. Grouping is a statistical technique for reducing the amount of data, and it involves grouping data by object, period, or characteristic, and treating the group as one data (group), thereby reducing the amount of data that must be processed.

[0058] FIG. 6 is a graph showing a state where the operation time data of the directional change valve is grouped and statistically visualized. Referring to FIG. 6(a), the operation time data of the directional change valve is 3,600 per hour, and 10,800 for a three-hour operation, but when grouped as in FIG. 6(b), it can be grouped into three data groups. When the entire data on the operation time of the directional change valve is displayed as in FIG. 6(a), the tendency cannot be clearly understood, but when the data is grouped and visually displayed as in FIG. 6(b), it is advantageous in that the change in the operation time data according to the elapsed time of the equipment operation can be understood at a glance. In addition, when statistical indicators such as standard deviation and first quartile are calculated based on the total number of data as in FIG. 6(a), the amount of data processing or calculation increases as described above. However, when statistical indicators such as standard deviation are calculated for each data group for each time period as in FIG. 6(b), and the standard deviation values ​​of the three data groups are averaged, the standard deviation value corresponding to the total number of data can be obtained while greatly reducing the amount of data processing.

[0059] In FIG. 6, one hour is set as a unit time, and operation time data acquired during one hour is made into one data group. However, the unit time used as a reference for acquiring the grouped data groups may be 3 hours, 8 hours, 24 hours, or more. For example, a plurality of 24-hour periods may be defined as one unit time interval, and operation time data of a directional change valve operated in each unit time interval may be grouped into one data group. In this case, one data group is a group of operation time data of one directional change valve that has repeatedly operated over the elapsed operation time of the equipment for 24 hours. In this manner, multiple data groups can be obtained over a specific inspection period such as one week, several weeks, or one month. For example, in order to predict the failure of a directional change valve that has operated for 30 days in a factory, if a data group is acquired with one day (24 hours) as a unit time interval, the data acquisition unit may acquire 30 data groups for each directional change valve.

[0060] FIG. 7 is a schematic diagram showing a failure prediction mechanism by the failure prediction system 100 for a directional control valve according to an embodiment of the present invention.

[0061] The above diagram shows that operation time data groups were acquired for a total of n directional change valves V1 to Vn during a 30-day inspection period. That is, in this case, one day (24 hours) is set as a unit time period, and the inspection period (30 days) consists of 30 unit time periods, and the operation time data groups were acquired by grouping the operation time data of each directional change valve for each unit time period. Therefore, 30 operation time data groups are obtained for each individual directional change valve such as V1, and the data groups are collected and stored in the data acquisition unit.

[0062] Referring again to FIG. 5, the failure prediction system 100 of the directional control valve of the present invention includes a degradation index value calculation unit 120 that calculates degradation index values ​​of a plurality of statistical degradation indexes that can represent a failure of the directional control valve based on the above operation time data.

[0063] Examples of statistical deterioration indexes include, but are not limited to, the average, standard deviation, skewness, kurtosis, first quartile, median, third quartile, skewness change, and kurtosis change of the operation time data of each directional change valve. Even if multiple directional change valves operate for the same time, the tendency of the directional change valve to show failure symptoms varies due to various causes. The above-mentioned statistical deterioration indexes are measured for such directional change valves, and a directional change valve that is relatively deteriorated can be selected. That is, the present invention does not absolutely compare the performance and operation time of each directional change valve, but compares the operation time data of each directional change valve and the statistical deterioration index based thereon to determine a directional change valve that is predicted to fail as a directional change valve that is predicted to fail. For example, if the operation time of a specific directional change valve is longer than the average, the performance is deteriorated and it is highly likely to be determined as a directional change valve that is predicted to fail. If a specific directional change valve shows a difference from other directional change valves in other statistical deterioration indexes such as the standard deviation, skewness, and kurtosis of other operation time data, it is also highly likely to be determined as a directional change valve that is predicted to fail.

[0064] Among the statistical degradation indices mentioned above, the standard deviation is a characteristic value that indicates the degree of dispersion of data around the mean value. The first quartile is the value that is 1 / 4 of the way down from the bottom when the data is sorted from low to high and then divided into 4 equal parts. The median and third quartile are the values ​​that are 1 / 2 and 3 / 4 of the way down from the bottom when the data is sorted from low to high and then divided into 4 equal parts.

[0065] FIG. 8 is a schematic diagram showing an example of a statistical deterioration index based on the operation time of a directional change valve. FIG. 8(a) shows the relationship between the third quartile, median, first quartile and average. As shown in the upper graph of FIG. 8(b), skewness is an index showing the asymmetry of data based on a normal distribution curve, and kurtosis is a measure showing the high and low of data based on a normal distribution curve, as shown in the lower graph of FIG. 8(b). The above statistical deterioration indexes can be calculated by converting the operation time data of each directional change valve into a numerical value and converting it into a deterioration index value by a predetermined computing program. Since the operation time of a directional change valve is a factor that can reflect or represent the deterioration, failure or failure symptom of a directional change valve, the above statistical deterioration index calculated based on the operation time can also represent the failure of a directional change valve. The deterioration index value calculation unit of the present invention is equipped with a predetermined computing program, and therefore can calculate the deterioration index value of the statistical deterioration index of each directional change valve for each operation time data group of each unit time section as shown in FIG. 7.

[0066] Meanwhile, in the present invention, at least a plurality of statistical deterioration indexes are used to judge a direction change valve that is expected to fail. No matter how much data is held as the basis for failure judgment, if a failure is judged by comparing one statistical deterioration index, the failure prediction probability will inevitably decrease. Therefore, two or more statistical deterioration indexes are selected from the statistical deterioration indexes based on the operation time data to calculate the deterioration index value. When selecting the statistical deterioration indexes, it is preferable to select indexes with statistical characteristics that are as different as possible. For example, by selecting one or more indexes that indicate a quantitative change in data, such as the mean, standard deviation, first quartile, median, and third quartile, and selecting one or more indexes that indicate asymmetry or change in data, such as skewness and kurtosis, the accuracy of failure occurrence prediction can be further improved.

[0067] 5 again, the present invention includes a determination unit 130 for determining a diverting valve that is predicted to fail based on the deterioration index value of the statistical deterioration index. In order to relatively compare a plurality of diverting valves, the determination unit 130 ranks the deterioration index value of the statistical deterioration index calculated for each diverting valve according to the magnitude. In addition, a predetermined score is given to a diverting valve having a top value above a predetermined range among the ranked deterioration index values, and a diverting valve that is predicted to fail is determined based on the sum of the predetermined scores.

[0068] For example, the standard deviation and skewness of operation time data of a plurality of target directional change valves over the elapsed time of operation of the same equipment may be calculated for each directional change valve, and a ranking may be assigned to each directional change valve. For example, a score of 1 point may be assigned to the standard deviation and skewness of the directional change valve having a top value in the ranking, and a directional change valve having a score of 2 points may be determined as a directional change valve predicted to fail. However, this is merely an example, and specific determination conditions such as the type of statistical deterioration index to be selected, the criteria for selecting the top value, and the size of the score may be determined in various ways in consideration of various factors such as the characteristics of the directional change valve to be evaluated, the equipment operation conditions, and the factory operation conditions. In other words, the detailed failure prediction algorithm by the determination unit may be adjusted as much as possible.

[0069] 7 again, the determination unit 130 may determine which directional valves are likely to fail based on the statistical deterioration indexes of the 30 operation time data groups acquired for each of the multiple (n) directional valves V1 to Vn. In this case, the determination unit 130 may rank the deterioration index values ​​of the statistical deterioration indexes calculated based on the total operation time data of each directional valve for the entire 30-day inspection period, and assign a predetermined score to the directional valves to determine which directional valves are likely to fail.

[0070] However, in this case, as described above, the amount of data to be processed increases exponentially, so that an excessive load is placed on the system and rapid calculation is difficult. In addition, comparing the operation time data for the entire 30 days for each directional change valve is not only inefficient but may also reduce the reliability of failure prediction. That is, a directional change valve usually fails after being used repeatedly for a certain period of time. Therefore, determining a directional change valve that is likely to fail based on a deterioration index value calculated based on a group of operation time data belonging to an initial unit time section of the inspection period is inefficient in that the possibility of failure is not high. It is reasonable to determine a directional change valve that is likely to fail based on operation time data of each directional change valve that has operated for a specific (unit) time section after operating for at least a certain period or a predetermined unit time section. That is, as shown in FIG. 7, for example, a directional change valve that is likely to fail can be determined based on operation time data of a directional change valve that has operated for one day on the 30th day after operating for 29 days. In this case, since all the directional change valves were used for the same period (29 days), the deterioration tendency of each directional change valve becomes clear, and therefore, by comparing the deterioration index value calculated for one day on the 30th day, which is the end period (hereinafter referred to as the end deterioration index value), the deterioration degree or the possibility of failure of each directional change valve can be reliably grasped. In this respect, as shown in FIG. 5, the data acquisition unit 110 of the directional change valve failure prediction system 100 of this embodiment needs to acquire end data after at least a certain period of use among a plurality of unit time sections, and the deterioration index value calculation unit 120 also calculates the end deterioration index value based on this end data (group), and the determination unit 130 also ranks the end deterioration index value for each directional change valve to determine the directional change valve predicted to fail. However, in the present invention, the "end period" and "end deterioration index value" are not limited to the deterioration index value calculated based on the final unit time section after repeated use for a certain period (for example, the unit time section on the 30th day in FIG. 7) or the operation time data group (D30) of that unit time section. Referring to FIG. 7, for example, a deterioration index value may be calculated based on any one of the operation time data groups D28, D29, and D30 after the directional valve has been operated for 27 days.In this case, any one of 28 days, 29 days, and 30 days may be selected as the end period, and the deterioration index value calculated based on the selected end period data group is the end period deterioration index value. That is, the end period in this embodiment may be a specific time period or a specific unit time period after the directional control valve is used (operated) for a certain period or a predetermined unit time period, and does not necessarily mean the final unit time period immediately after the certain period of use. In addition, the "certain period" used may be freely selected depending on the purpose of the inspection or failure prediction, the characteristics of the directional control valve, etc. In FIG. 7, it is assumed that the directional control valve is used for 29 days, but it is also possible to predict the failure of the directional control valve after it is used for a longer or shorter period.

[0071] Moreover, the end does not necessarily mean only a single unit time interval.

[0072] FIG. 9 is a schematic diagram showing a failure prediction mechanism by a failure prediction system for a directional control valve according to a modified embodiment of the present invention. Referring to FIG. 9, the end-of-life deterioration index values ​​calculated based on the operation time data groups D28, D29, and D30 for 28, 29, and 30 days after the directional control valve is operated for 27 days are averaged, and the average end-of-life deterioration index value can be used as a deterioration index value for determining a directional control valve that is predicted to fail. Therefore, in the example of FIG. 9, strictly speaking, the end-of-life is 3 days, and the deterioration index value for failure prediction is an average end-of-life deterioration index value obtained by averaging each deterioration index value calculated based on each operation time data group for the 3 days. Predicting failure based on an average end-of-life deterioration index value calculated based on a plurality of unit time sections or operation time data groups may be more advantageous in terms of statistical or mathematical data reliability than predicting failure based on an end-of-life deterioration index value calculated based on a single unit time section or a single operation time data group as in FIG. 7.

[0073] Referring again to Fig. 7, the process of selecting standard deviation A and skewness B as statistical deterioration indexes for an operation time data group obtained based on the operation time data of the directional change valve on the 30th day after the directional change valve has been used (operated) for 29 days, and determining deterioration index values ​​of the standard deviation value and skewness value for each directional change valve is shown. In this case, D30 is an operation time data group of a directional change valve operated for 24 hours on the 30th day, and as described above, 86,400 pieces of data are grouped. Based on this operation time data group of D30, the standard deviation value and skewness value can be determined and ranked for each directional change valve.

[0074] 9 again, this example shows a process of selecting standard deviation A and skewness B as statistical deterioration indexes based on each operation time data group D28, D29, and D30 obtained based on the directional change valve operation time data from the 28th to 30th days after the directional change valve has been used (operated) for 27 days, and reaveraging the standard deviation and skewness values ​​calculated for each operation time data group to obtain an average terminal deterioration index value for each directional change valve. The average terminal deterioration index values ​​are ranked for each directional change valve, and a predetermined score is assigned to a directional change valve having a top value above a predetermined range, and a directional change valve predicted to fail can be determined based on the sum of the predetermined scores.

[0075] A specific example of determining which directional control valve is likely to fail based on the failure prediction mechanisms of FIGS. 5 and 7 will be described.

[0076] Table 1 below shows the final deterioration index values ​​on the 30th day calculated for 29 directional valves that had been in operation for 29 days, calculated using five statistical deterioration indexes: skewness, kurtosis, 1st quartile, 3rd quartile, and standard deviation.

[0077] Table 2 shows that a score of 1 point was given to directional valves that were in the top 25% (7th, etc.) of the ranked terminal deterioration index values.

[0078] [Table 1]

[0079] [Table 2]

[0080] In Table 2, directional change valves with a total score of 2 or more are judged to be directional change valves likely to fail. In this case, directional change valves 1 and 2 are judged to be directional change valves likely to fail. Therefore, the above directional change valves need to be inspected as they may be in trouble.

[0081] In the above example, a score of 1 point is given to the top 25%, and the directional change valves with a total score of 2 points or more are judged to be directional change valves that are likely to fail. However, the top percentage value, the score given, and the total score that is the criterion for judging a directional change valve that is likely to fail can be changed. Therefore, when predicting the failure of a directional change valve using the failure prediction system of the present invention, a failure prediction algorithm for various cases can be derived. What is important is that according to the present invention, a plurality of statistical deterioration indexes are selected based on a plurality of operation time data, each deterioration index value is derived therefrom, the values ​​are ranked, and a directional change valve that is likely to fail can be judged by the sum of a predetermined score. Therefore, within the scope of such a failure prediction system or failure prediction method, the detailed failure prediction algorithm can be changed as many times as necessary to increase statistical reliability.

[0082] Second embodiment FIG. 10 is a schematic diagram illustrating a system 200 for predicting a failure of a directional valve according to another embodiment of the present invention.

[0083] This embodiment differs from the first embodiment in that, in addition to individual statistical indices such as standard deviation, skewness, and kurtosis, additional statistical degradation indices such as the change in the mean, the change in skewness, and the change in kurtosis are introduced.

[0084] That is, the amount of change in the average, other than the average value, of the deterioration index values ​​for determining the direction-changing valve that is expected to fail, or the amount of change in the deterioration indexes of skewness and kurtosis are also closely related to the deterioration of the operation of the direction-changing valve. Therefore, if the change value of such a statistical deterioration index is used as a new statistical deterioration index to obtain a deterioration index value together with the existing statistical deterioration index, the reliability of the failure prediction can be further improved.

[0085] Fig. 11 is a schematic diagram showing such a change in a statistical deterioration index. Fig. 11(a) shows a change in skewness, and Fig. 11(b) shows a change in kurtosis. In this embodiment, when selecting a plurality of statistical deterioration indexes for failure prediction, one or more of the normal statistical deterioration indexes (e.g., standard deviation) may be selected, and one or more of the change values ​​of the statistical deterioration indexes (e.g., skewness change values) may be selected as new statistical deterioration indexes.

[0086] In order to add a change in a statistical deterioration index to a new statistical deterioration index, the values ​​of the deterioration index before and after the change must be known. For this purpose, the data acquisition unit 210 of the failure prediction system 200 of this embodiment must acquire at least the initial operation time data and the final operation time data for each directional control valve.

[0087] 12 and 13 are schematic diagrams showing a failure prediction mechanism by the failure prediction system for a directional control valve according to the embodiment of FIG.

[0088] 12, for example, a statistical deterioration index with a standard deviation A and skewness B may be selected based on the operating time data group D1 on the first day, which is the beginning of the 30-day inspection period, and the deterioration index value may be calculated. Also, a statistical deterioration index with a standard deviation A and skewness B may be selected based on the operating time data group D30 on the final day, 30 days after the directional control valve has been used for 29 days, and the deterioration index value may be calculated. In addition, a skewness value based on the data group D1 and a skewness value based on the data group D30 may be calculated, and the difference between them may be used as a skewness change value, and this skewness change value C may be used as a new statistical deterioration index together with the deterioration indexes of the standard deviation and skewness.

[0089] 10 and 12, three parameters, namely, standard deviation A on the 30th day which is the final period, skewness B, and skewness change value C which is the difference between the skewness values ​​on the 1st day and the 30th day, are calculated as deterioration index values ​​by deterioration index value calculation unit 220. Determination unit 230 ranks these three deterioration index values, gives a predetermined score to a directional control valve having a top value above a predetermined range among the ranked values, and may determine a directional control valve predicted to fail based on the sum of the predetermined scores.

[0090] On the other hand, the initial data group that serves as the basis for calculating the change value of the statistical deterioration index or the initial statistical deterioration index value calculated based on the initial data group is not limited to a single unit time interval or an initial statistical deterioration index value based thereon.

[0091] 13, for example, a group of operation time data D1 to D7 of seven unit time sections of one week from the 1st to the 7th may be used as basic data for calculating an initial deterioration index value. In this case, a deterioration index value (e.g., average, skewness) is obtained for each of the data groups D1 to D7, and the average of the deterioration index values ​​is used as the initial deterioration index value. Then, a final deterioration index value (average, standard deviation A, skewness value B) is obtained on the 30th day after 29 days of use, and a difference value (e.g., change value of average or change value of skewness C') obtained by subtracting the final deterioration index value from the average value of the initial deterioration index values ​​may be introduced as an additional statistical deterioration index.

[0092] 9, the final deterioration index value serving as a basis for determining the difference value may be based not only on a single unit time interval, but also on an average final deterioration index value based on a plurality of operation time data groups in a plurality of unit time intervals. Therefore, a difference value obtained by subtracting the final deterioration index value or the average final deterioration index value from the initial deterioration index value for the operation time data group in the initial unit time interval of the inspection period or the average value of the initial deterioration index values ​​determined for the operation time data group in the initial unit time interval may be introduced as an additional statistical deterioration index that can represent a failure of the directional control valve.

[0093] A specific example of determining which directional control valve is likely to fail based on the failure prediction mechanisms of FIGS. 10 and 13 will be described.

[0094] As in the example of the first embodiment, five items, namely, skewness, kurtosis, first quartile, third quartile, and standard deviation, were adopted as statistical deterioration indexes, and the final deterioration index values ​​on the 30th day were calculated and ranked for 29 directional control valves that had been in operation for 29 days.

[0095] Meanwhile, in this example, the average values ​​of the skewness, kurtosis and average of the unit time section for the first 7 days were calculated as the initial deterioration index value, and the difference values ​​(absolute values) between the skewness, kurtosis and average value (final deterioration index value) on the 30th day were calculated. The change in skewness, change in kurtosis and average change were used as new statistical deterioration indexes, and the deterioration surface value was ranked together with the deterioration index values ​​of the above five statistical deterioration indexes, and is shown in Table 3.

[0096] Table 4 shows the total of eight ranked terminal deterioration index values, including these difference values, with a score of 1 point given to directional change valves that were in the top 25% (7th, etc.) or higher.

[0097] [Table 3]

[0098] [Table 4]

[0099] In Table 4, the directional change valves with a total score of 3 or more are judged to be directional change valves that are likely to fail. In this case, the directional change valve No. 1 is judged to be the directional change valve that is likely to fail. Therefore, the directional change valve needs to be inspected because it may be broken.

[0100] The data acquisition units 110, 210 of the failure prediction system 100, 200 of the present invention may include a data collection device and a database for storing data, as described above. The data acquisition units 110, 210 may include a predetermined statistical program for grouping data into groups. The deterioration index value calculation units 120, 220 may include a predetermined computing program to calculate a selected statistical deterioration index or a difference value of the statistical deterioration index. The determination units 130, 230 may include a data reading device, an analysis device, a calculation device, etc., in order to rank the calculated deterioration index values, give a predetermined score, and calculate the sum of the scores to determine the direction change valve predicted to be failed. Alternatively, the data acquisition units 110, 210, the deterioration index value calculation units 120, 220, and the determination units 130, 230 may be computing devices realized by controlling hardware including a calculation device such as a CPU and a storage device such as a hard disk with predetermined software, and are set to be able to communicate with each other.

[0101] The present invention also provides a method for predicting failures of a directional control valve using the above-described directional control valve failure prediction system or the like.

[0102] Specifically, the method includes the steps of repeatedly detecting operation times of a plurality of directional change valves that communicate with a cylinder having a piston rod, supply a fluid to the cylinder, and change the operation direction of the piston rod by changing the supply direction of the fluid over an elapsed time of equipment operation, and acquiring a plurality of operation time data for each directional change valve; selecting a plurality of statistical deterioration indicators that can represent failures of the directional change valves, and calculating deterioration index values ​​of the selected statistical deterioration indicators based on the operation time data; ranking each deterioration index value for each directional change valve according to its size; and assigning a predetermined score to directional change valves having upper values ​​above a predetermined range among the ranked deterioration index values, and determining which directional change valves are predicted to fail based on the sum of the predetermined scores.

[0103] In the step of acquiring the plurality of pieces of operation time data, a first time when the piston rod starts to move forward in response to an operation signal of the directional control valve, a second time when the piston rod starts to move backward in response to an operation signal of the directional control valve, or a combined time thereof may be acquired as the operation time data. In this case, if the inspection target period is made up of a plurality of unit time sections in order to reduce the amount of data processing, the operation time data of each directional control valve may be grouped for each unit time section to acquire individual operation time data groups.

[0104] Then, a plurality of statistical deterioration indexes capable of representing the failure of the directional control valve are selected based on the operation time data. Examples of such statistical deterioration indexes include the mean, standard deviation, first quartile, median, third quartile, skewness, and kurtosis of the operation time data of each directional control valve. When the statistical deterioration indexes are selected, the deterioration index values ​​of each of the selected statistical deterioration indexes are calculated. In this case, when the operation time data is grouped as described above into individual operation time data groups, the deterioration index value of each directional control valve can be calculated for each operation time data group.

[0105] Next, the calculated deterioration index values ​​are ranked for each directional control valve according to their magnitude. Since the deterioration index values ​​are deterioration indexes, the directional control valves having higher values ​​among the ranked deterioration index values ​​are more likely to be directional control valves predicted to fail.

[0106] Then, a predetermined score is given to the directional control valves having a higher value than a predetermined range among the ranked deterioration index values, and the directional control valves predicted to be faulty are determined based on the sum of the predetermined scores.

[0107] The deterioration index value used as the basis for determining whether a directional control valve is likely to fail is preferably calculated based on operation time data for a specific time period after the directional control valve is repeatedly used for a certain period. In this case, when the inspection period is composed of a plurality of unit time periods, the end-of-life deterioration index values ​​calculated for the operation time data group for a specific unit time period after the directional control valve operates for a predetermined unit time period during the inspection period, or the average value of the end-of-life deterioration index values ​​for the operation time data group for the specific unit time period, may be ranked and used as the basis for determining whether a directional control valve is likely to fail.

[0108] Meanwhile, a change value of one or more statistical deterioration indexes selected from the plurality of statistical deterioration indexes may be introduced as an additional statistical deterioration index for determining a directional control valve predicted to have a failure. In this case, in order to obtain the change value, a difference value obtained by subtracting the final deterioration index value or an average value of the final deterioration index values ​​from an initial deterioration index value calculated for an initial unit time section or operation time data group of an inspection target period or an average value of the initial deterioration index values ​​calculated for an initial unit time section or operation time data group of an inspection target period may be introduced as the change value of the statistical deterioration index.

[0109] FIG. 14 is a schematic diagram illustrating a fault inspection system 1000 for a directional valve according to the present invention.

[0110] As shown in the figure, the directional control valve failure inspection system includes a directional control valve failure prediction system 100, 200 of the present invention, which is configured with a data acquisition unit 110, 210, a deterioration index value calculation unit 120, 220, and a judgment unit 130, 230. The directional control valve failure inspection system 1000 further includes an inspection unit 300 connected to the judgment units 130, 230 of the directional control valve failure prediction system 100, 200, for measuring the presence or absence of air leakage from a directional control valve judged by the judgment unit as a directional control valve suspected to be faulty.

[0111] The inspection unit 300 may be, for example, an ultrasonic acoustic camera. The ultrasonic acoustic camera is an industrial camera that can capture gas leaks and electric arcs in real time by measuring ultrasonic waves that humans cannot hear. The ultrasonic energy generated at the air leak point is detected by a sensor array, and the leak point is displayed against a visible light image of the inspection target, so that the leak point can be quickly detected and can be saved in JPEG image or MP4 video format.

[0112] The present invention also provides a method for inspecting a directional control valve including the above-mentioned method for predicting a failure of the directional control valve, the inspection method including the steps of inspecting a directional control valve determined to be a directional control valve suspected to be faulty by the above-mentioned method for predicting a failure of the directional control valve, and replacing a directional control valve found to be faulty by the inspection.

[0113] According to the present invention, only the directional change valves determined to be suspected to be faulty are inspected in the inspection department, so that the inspection time for the directional change valves can be significantly reduced, and the costs and manpower required for inspecting the directional change valves can be significantly reduced.

[0114] <Example> The system for predicting the failure of the directional change valve of the present invention was used to determine which directional change valves were likely to fail, for a cylinder that operates a folding unit that alternately folds two types of bi-cells (negative and positive) and a separator, and a number of directional change valves that are connected to the cylinder and change the operating direction of the cylinder. The number of actual directional change valve failures was also evaluated.

[0115] Example 1 in Table 5 is the result of judging a total of 29 directional control valves with different evaluation dates (evaluation orders). Example 2 in Table 6 is the result of judging using an algorithm in which detailed evaluation conditions (top % selection conditions, etc.) were modified and supplemented with reference to the second result.

[0116] <Example 1> [Table 5]

[0117] In Table 5, the overdetection rate, undetected rate, and detection rate are expressed by the following formulas.

[0118] Over-inspection rate = (total number of recommendations - number of actual defects among total number of recommendations) / total number of inspections Uninspected rate = (total number of defects - number of recommended defects) / total number of inspections Detection rate = Actual number of defects among total recommendations / Total recommendations

[0119] As shown in Table 5 above, in the case of the second evaluation, the over-inspection rate decreased compared to the first evaluation, but the uninspected rate and detection rate increased. Therefore, the selection criteria for the top % were changed for the third evaluation and the third evaluation was carried out. In addition, all valves recommended as faulty in the third evaluation were inspected and repaired, and the fourth evaluation was carried out and judged using the same algorithm.

[0120] <Example 2> [Table 6]

[0121] As shown in Table 2 above, in the case of the 3rd and 4th stages evaluated using the supplementary algorithm, the undetected rate was 0%, and the overdetected rate was less than 25%. Therefore, when evaluating directional valve failures using the supplementary algorithm, the number of inspections and the inspection time can be significantly reduced.

[0122] The above description is merely illustrative of the technical idea of ​​the present invention, and various modifications and variations may be made by those skilled in the art without departing from the essential characteristics of the present invention. Therefore, the drawings disclosed in the present invention are for illustration purposes, not for limiting the technical idea of ​​the present invention, and the scope of the technical idea of ​​the present invention is not limited by such drawings. The scope of protection of the present invention should be interpreted by the claims, and all technical ideas within the equivalent range should be interpreted as being included in the scope of the present invention.

[0123] Meanwhile, although terms indicating directions such as up, down, left, right, front, and back are used in this specification, it is obvious that such terms are used merely for convenience of explanation and may change depending on the position of the target object, the position of the observer, etc. [Explanation of symbols]

[0124] 10: Directional valve 11:Port 11a: first port, 11b: second port, 11c: third port, 11d: fourth port, 11e: fifth port 111: Flow path 12: Case 121: Internal flow path S1, S2: Sensors 100, 200: Directional valve failure prediction system 110, 210: Data acquisition section 120, 220: Deterioration index value calculation unit 130, 230: Judgment section 300: Inspection Department 1000: Directional valve fault inspection system

Claims

1. a data acquisition unit that repeatedly detects operation times of a plurality of direction change valves that are in communication with a cylinder having a piston rod and change a supply direction of a working fluid supplied to the cylinder to change an operating direction of the piston rod over an elapsed time of equipment operation, and acquires operation time data for each direction change valve; a degradation index value calculation unit for calculating degradation index values ​​of a plurality of statistical degradation indexes representing failures of the directional control valve based on the operation time data; a determination unit that ranks deterioration index values ​​of the statistical deterioration index calculated for each directional control valve according to their magnitude, assigns a predetermined score to directional control valves having upper values ​​above a predetermined range among the ranked deterioration index values, and determines which directional control valves are likely to fail based on a sum of the predetermined scores.

2. 2. The system for predicting a failure of a directional control valve according to claim 1, wherein the data acquisition unit acquires data by selecting, as an operation time of the directional control valve, one or more of a first time required for the piston rod to start moving forward in response to an operation signal of the directional control valve, a second time required for the piston rod to start moving backward in response to an operation signal of the directional control valve, and a sum of the first time and the second time.

3. The data acquisition unit regards the first time and the second time as separate and independent pieces of operation time data, 3. The system for predicting a failure of a directional control valve according to claim 2, wherein two pieces of operating time data, the first time and the second time, are acquired during one reciprocating motion of the piston rod provided in one of the cylinders.

4. 2. The directional valve failure prediction system according to claim 1, wherein the statistical deterioration index is two or more selected from the group consisting of a mean, a standard deviation, a first quartile, a median, a third quartile, a skewness, and a kurtosis of the operation time data of each directional valve.

5. one or more selected from the group consisting of mean, standard deviation, first quartile, median, third quartile, skewness, and kurtosis of the operation time data of each directional control valve; The system for predicting failures of a directional control valve according to claim 1 , wherein the statistical deterioration index is a change value of one or more statistical deterioration indexes selected from the group.

6. 2. The system for predicting failures of a directional control valve according to claim 1, wherein the deterioration index value of the statistical deterioration index is calculated based on operation time data of each directional control valve operated for a specific time interval after the directional control valve is used repeatedly for a certain period of time.

7. the data acquiring unit groups operation time data of each directional control valve for each unit time interval during an inspection period consisting of a plurality of unit time intervals to create individual operation time data groups; The system for predicting failures of a directional control valve according to claim 1 , wherein the deterioration index value calculation unit calculates a deterioration index value of each directional control valve for each group of operation time data.

8. 8. The system for predicting failure of a directional control valve according to claim 7, wherein the determination unit ranks each directional control valve with an end-of-life deterioration index value calculated for a group of operation time data for a specific unit time period after operation for a predetermined unit time period during the inspection period, assigns a predetermined score to a directional control valve having a top value equal to or higher than a predetermined range among the ranked end-of-life deterioration index values, and determines which directional control valves are likely to fail based on a sum of the predetermined scores.

9. 8. The failure prediction system for a directional control valve according to claim 7, wherein the determination unit ranks each directional control valve to obtain an average terminal deterioration index value obtained by averaging each terminal deterioration index value calculated for a group of operation time data for a specific unit time period after operation for a predetermined unit time period during the inspection period, assigns a predetermined score to a directional control valve having a top value equal to or higher than a predetermined range among the ranked average terminal deterioration index values, and determines which directional control valves are likely to fail based on a sum of the predetermined scores.

10. 9. The system for predicting failures of a directional control valve according to claim 8, wherein a difference value obtained by subtracting the final deterioration index value from an initial deterioration index value for a group of operation time data in an initial unit time section of the inspection period or an average value of the initial deterioration index values ​​obtained for the group of operation time data in the initial unit time section is introduced as an additional statistical deterioration index representing a failure of the directional control valve.

11. 10. The system for predicting failures of a directional control valve according to claim 9, wherein a difference value obtained by subtracting the average final deterioration index value from an early deterioration index value for a group of operating time data in an initial unit time section of the inspection period or an average value of the early deterioration index values ​​obtained for the group of operating time data in the initial unit time section is introduced as an additional statistical deterioration index representing a failure of the directional control valve.

12. A system for predicting a failure of a directional control valve according to any one of claims 1 to 11; an inspection unit that measures whether or not there is air leakage from the directional control valve that is determined by the determination unit to be a directional control valve that is likely to be faulty.

13. repeatedly detecting operation times of a plurality of directional control valves, each of which is connected to a cylinder having a piston rod and changes a supply direction of a working fluid supplied to the cylinder, thereby changing an operating direction of the piston rod, over an elapsed time of operation of the equipment, and acquiring a plurality of operation time data for each directional control valve; selecting a plurality of statistical deterioration indicators representative of a failure of the directional control valve and calculating deterioration indicator values ​​of the selected statistical deterioration indicators based on the operating time data; ranking the respective deterioration index values ​​for each directional control valve according to their magnitude; assigning a predetermined score to directional control valves having upper values ​​above a predetermined range among the ranked deterioration index values, and determining which directional control valves are predicted to fail based on a sum of the predetermined scores.

14. The method for predicting a failure of a directional control valve according to claim 13, further comprising: introducing a change value of one or more selected statistical deterioration indicators from the plurality of statistical deterioration indicators as an additional statistical deterioration indicator for determining a predicted directional control valve failure.

15. Inspecting a directional control valve determined to be a directional control valve suspected to be faulty by the method for predicting a fault in a directional control valve according to claim 13 or 14; replacing any diverter valve found to be faulty by the inspection.

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