Directional control valve failure prediction system and failure prediction method, directional control 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 a failure of a direction change valve.

[0002] The present invention also relates to a failure inspection system and inspection method for a direction change valve that inspects and replaces a direction change valve whose failure has been predicted by the above failure prediction system and prediction method.

[0003] This application claims the benefit of priority based on Korean Patent Application No. 10-2022-0112023 filed on September 5, 2022, and all the contents disclosed in the literature of the Korean patent application are included as part of this specification.

Background Art

[0004] In recent years, rechargeable secondary batteries have been widely used as an energy source for wireless mobile devices. In addition, secondary batteries have also attracted attention as an energy source for electric vehicles, hybrid electric vehicles, etc., which are proposed as solutions to solve air pollution caused by existing gasoline vehicles, diesel vehicles, etc. that use fossil fuels. Therefore, the types of applications using secondary batteries are very diverse due to the advantages of secondary batteries, and it is expected that secondary batteries will be applied to more fields and products in the future.

[0005] To manufacture such secondary batteries, a number of detailed processes are performed, such as a process of coating and rolling an active material on a current collector for manufacturing a positive electrode and a negative electrode, which are constituent parts, a notching process for forming an electrode tab, an electrode assembly manufacturing process for manufacturing an electrode assembly by laminating and / or folding (Folding) a positive electrode - separator - negative electrode, a welding process for welding an electrode tab and an electrode lead, a process of cutting an electrode assembly for stacking, a charge - discharge process for imparting characteristics before shipment, etc. At 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 equipment, and includes motors, cylinders, and the like. A cylinder, among other actuators, comprises a cylindrical cylinder body and a piston rod housed within the cylinder body with a piston at its tip. The linear movement of the piston rod within the cylinder body provides driving force to the movable body. On the other hand, the linear movement of the piston rod can be performed by the pressure (hydraulic or pneumatic) of a working fluid supplied from the outside. That is, when a working fluid (such as oil or air) is supplied to the cylinder body from a working fluid source, the piston rod moves linearly due to the pressure of the supplied working fluid. In this case, the direction of the linear movement of the piston rod can be changed by changing the direction of the working fluid supply. A direction change valve is used as a device for changing the direction of the working fluid supply.

[0007] A direction change valve is a valve positioned in a flow path to change the direction of flow of a working fluid. Specifically, a direction change valve consists of a plurality of ports in which flow paths are formed through which working fluid flows in or out; a case in which the plurality of ports are installed and an internal flow path is formed that communicates with the flow paths of the plurality of ports; a spool positioned in the internal flow path of the case and controlling the direction of flow of the working fluid by closing or opening the plurality of ports and blocking a part of the internal flow path; and a spool drive unit that applies driving force to the spool so that the spool can move within the internal flow path of the case. The direction change valve forms a flow path by communicating with the working fluid supply source and the cylinder body via the ports, and the spool determines the direction of flow of the working fluid by closing some of the ports and blocking a part of the internal flow path when the working fluid flows along the flow path.

[0008] If there is a malfunction in the operation of such cylinders, piston rods, and directional valves, the movable parts cannot be moved according to the set values, leading to malfunctions in the factory production line and defective products. In particular, if a serious malfunction occurs in any one of the above cylinders, piston rods, and directional valves, it may cause part or all of the factory's manufacturing system to break down.

[0009] To prevent disruptions to the factory manufacturing system, we have attempted to predict cylinder failures before they occur. However, when a directional valve that changes the flow direction of the working fluid malfunctions, an error occurs in which a cylinder is incorrectly identified as a faulty cylinder even if it is otherwise functioning normally. Therefore, to more fundamentally prevent disruptions to the factory manufacturing system, it is necessary to identify signs of failure or abnormality in the directional valve before it actually fails.

[0010] Conventionally, valve abnormalities were detected by comparing the number of opening / closing operation signals applied to individual valves with the actual number of times the valves were opened and closed. (Patent Document 1) However, valve opening and closing can occur even if the valve operation is delayed due to an abnormality or malfunction. In other words, errors may occur when detecting and predicting valve abnormalities through the number of opening and closing operations. Therefore, there is a need for a technology that can select factors or indicators that can represent valve malfunctions or failures and predict the occurrence of failures based on these factors or indicators. [Prior art documents] [Patent Documents]

[0011] [Patent Document 1] Japanese Patent Publication No. 2013-168131 [Overview of the project] [Problems that the invention aims to solve]

[0012] The present invention was devised to solve the above-mentioned problems, and aims to provide a directional control valve failure prediction system and method that can select a statistical degradation index that can represent the failure of the directional control valve, and predict whether or not a failure will occur in the directional control valve before the failure occurs based on that degradation index.

[0013] Furthermore, the present invention aims to provide a fault inspection system and inspection method for a directional control valve that inspects and replaces a directional control valve whose failure has been predicted by the above-described fault prediction system and prediction method. [Means for solving the problem]

[0014] The present invention, which solves the above problems, includes a data acquisition unit that repeatedly detects the operating time of multiple direction change valves that communicate with a cylinder equipped with a piston rod and change the direction of operation of the piston rod by changing the direction of supply of the working fluid supplied to the cylinder, over the elapsed time of equipment operation, and acquires multiple operating time data for each direction change valve; a deterioration index value calculation unit that calculates deterioration index values ​​of multiple statistical deterioration indices that can represent the failure of the direction change valve based on the operating time data; a determination unit that ranks the deterioration index values ​​of the statistical deterioration indices calculated for each direction change valve by magnitude, assigns a predetermined score to direction change valves that have upper values ​​above a predetermined range among the ranked deterioration index values, and determines the direction change valve that is expected to fail based on the sum of the predetermined scores.

[0015] As a specific example, the data acquisition unit may select one or more of the following as the operating time of the direction change valve to acquire data: the first time it takes for the piston rod to start moving forward in response to the operating signal of the direction change valve, the second time it takes for the piston rod to start moving backward in response to the operating signal of the direction change valve, or the sum of the first and second times.

[0016] As a more specific example, the data acquisition unit may consider the first time and the second time as separate and independent operating time data, and acquire two operating time data, the first time and the second time, when the piston rod provided in one cylinder undergoes one reciprocating motion.

[0017] As one example, the above statistical degradation index may be two or more selected from a group consisting of the mean, standard deviation, first quartile, median, third quartile, skewness, and kurtosis of the operating time data for each direction change valve.

[0018] As another example, the statistical degradation index may be one or more values ​​selected from a group consisting of the mean, standard deviation, first quartile, median, third quartile, skewness, and kurtosis of the operating time data for each direction change valve, and the change in one or more statistical degradation indexes selected from the above group.

[0019] As one example, the degradation index value of the above statistical degradation index can be calculated based on the operating time data of each directional valve that operated during a specific time interval after the directional valve had been repeatedly used for a certain period of time.

[0020] As a specific example, the data acquisition unit can group the operating time data of each direction change valve for each unit time interval within an inspection period consisting of multiple unit time intervals to create individual operating time data groups, and the deterioration index value calculation unit can calculate the deterioration index value of each direction change valve for each operating time data group.

[0021] As one example, the determination unit can rank the terminal degradation index values ​​calculated for each steering valve based on the operating time data set for a specific unit time interval after operating for a predetermined unit time interval within the inspection target period, assign a predetermined score to steering valves that have a higher value than a predetermined range among the ranked terminal degradation index values, and determine which steering valve is likely to fail based on the sum of the predetermined scores.

[0022] As another example, the determination unit averages the end-stage deterioration index values calculated for the operation time data group of a specific unit time interval after operating only for a predetermined unit time interval within the inspection target period, and serializes the average end-stage deterioration index values for each direction change valve. A predetermined score is given to a direction change valve having a top value within a predetermined range or more among the serialized average end-stage deterioration index values, and a failure prediction direction change valve can be determined based on the total of the predetermined scores.

[0023] As another example, a difference value obtained by subtracting the end-stage deterioration index value from the initial deterioration index value for the operation time data group of the initial unit time interval within the inspection target period, or the average value of the initial deterioration index values obtained for the operation time data group of the initial unit time interval, can be introduced as an additional statistical deterioration index that can substitute for the failure of the direction change valve.

[0024] As another example, a difference value obtained by subtracting the average end-stage deterioration index value from the initial deterioration index value for the operation time data group of the initial unit time interval within the inspection target period, or the average value of the initial deterioration index values obtained for the operation time data group of the initial unit time interval, can be introduced as an additional statistical deterioration index that can substitute for the failure of the direction change valve.

[0025] As another aspect of the present invention, a failure inspection system for a direction change valve includes the failure prediction system for the direction change valve and an inspection unit that measures the presence or absence of air leakage in the direction change valve determined to be a failure prediction direction change valve by the determination unit.

[0026] As another aspect of the present invention, a method for predicting a failure of a direction-changing valve communicates with a cylinder provided with a piston rod and changes the operating direction of the piston rod by changing the supply direction of the operating fluid supplied to the cylinder. The method repeatedly detects the operating times of a plurality of direction-changing valves over the facility operation elapsed time, and obtains a plurality of operating time data for each direction-changing valve. Then, it selects a plurality of statistical deterioration indicators that can substitute for the failure of the direction-changing valve, and calculates the deterioration indicator values of the selected statistical deterioration indicators based on the operating time data. Next, it serializes the respective deterioration indicator values according to their magnitudes for each direction-changing valve. Then, it assigns a predetermined score to the direction-changing valve having an upper value within a predetermined range or more among the serialized deterioration indicator values, and determines a failure-predicted direction-changing valve based on the total of the predetermined scores.

[0027] As a specific example, a change value of one or more selected statistical deterioration indicators among the plurality of statistical deterioration indicators can be introduced as an additional statistical deterioration indicator for determining a failure-predicted direction-changing valve.

[0028] As another aspect of the present invention, a method for inspecting a failure of a direction-changing valve includes inspecting the direction-changing valve determined to be a failure-predicted direction-changing valve by the method for predicting a failure of the direction-changing valve, and replacing the direction-changing valve in which a failure is found by the inspection.

Effects of the Invention

[0029] According to the present invention, it is possible to predict in advance the presence or absence of a failure before an actual failure occurs in the direction-changing valve, and replace in advance the direction-changing valve with a high possibility of failure. Therefore, by removing in advance the direction-changing valve predicted to fail, it is possible to prevent a situation where the entire factory or manufacturing system is interrupted (Break down).

[0030] Furthermore, by predicting the failure of the directional valve, which is the driving force for the cylinder, before predicting the cylinder failure, the judgment error that occurs when determining cylinder failure can be reduced. In addition, by predicting the failure of the directional valve, which has much shorter operating time data than the operating time data used when predicting cylinder failure, the time required for failure prediction can be significantly reduced.

[0031] Furthermore, the present invention makes it possible to more accurately predict abnormalities in the directional control valve by statistically calculating an operating time that is greater than or equal to the operating time required to indicate a failure of the directional control valve.

[0032] Furthermore, the present invention can significantly reduce the number of directional valves that need to be inspected, thereby drastically reducing the personnel, workload, and time required for maintenance. [Brief explanation of the drawing]

[0033] [Figure 1] This is a schematic diagram showing that the piston rod moves in a linear motion when the direction of the working fluid supply is changed by a direction change valve. [Figure 2] This is a schematic diagram showing the location of a malfunction in the direction change valve. [Figure 3] This graph shows the cumulative operating time distribution of a normal directional control valve and a non-normal directional control valve. [Figure 4] This is a block diagram illustrating the concept of failure prediction in this invention. [Figure 5] This is a schematic diagram showing a failure prediction system for a direction change valve according to one embodiment of the present invention. [Figure 6] This graph shows the operation time data for the direction change valve grouped and statistically visualized. [Figure 7] This is a schematic diagram showing the failure prediction mechanism of a failure prediction system for a direction change valve according to one embodiment of the present invention. [Figure 8] This is a schematic diagram illustrating an example of a statistical degradation index based on the operating time of a direction change valve. [Figure 9]This is a schematic diagram showing the failure prediction mechanism of a failure prediction system for a direction change valve according to a modified example of one embodiment of the present invention. [Figure 10] This is a schematic diagram showing a fault prediction system for a direction change valve according to another embodiment of the present invention. [Figure 11] This is a schematic diagram showing changes in statistical deterioration indicators. [Figure 12] This is a schematic diagram showing a failure prediction mechanism by a failure prediction system for a direction change valve according to another embodiment of the present invention. [Figure 13] This is a schematic diagram showing a failure prediction mechanism by a failure prediction system for a direction change valve according to another embodiment of the present invention. [Figure 14] This is a schematic diagram showing a fault inspection system for a direction change valve according to the present invention. [Modes for carrying out the invention]

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

[0035] In this application, terms such as “includes” and “have” should be understood as intending to specify the existence of features, numbers, stages, actions, components, parts, or combinations thereof described in the specification, without prejudice to the existence or possibility of adding one or more other features, numbers, stages, actions, components, parts, or combinations thereof. Furthermore, when a part such as a layer, film, region, or plate is said to be “on top” of another part, this includes not only when it is “directly on top” of the other part, but also when there is another part in between. Conversely, when a part such as a layer, film, region, or plate is said to be “below” another part, this includes not only when it is “directly below” the other part, but also when there is another part in between. Also, in this application, being “located on top” may include being located not only at the top but also at the bottom.

[0036] Figure 1 is a schematic diagram showing that the piston rod changes direction and moves in a linear motion according to the supply direction of the working fluid, which has been changed by the direction change valve.

[0037] Referring to Figures 1(a) and 1(b), the directional valve 10 communicates with a working fluid source 30 and a cylinder 20 to change the direction of supply of working fluid from the working fluid source 30 to the cylinder 20. The working fluid may be oil or air, and the working fluid source 30 may be a fluid storage tank or a pump, etc. The directional valve 10 comprises a plurality of ports 11 in which flow paths 111 are formed through which working fluid flows in or out; a case 12 in which the plurality of ports 11 are installed and an internal flow path 121 is formed that communicates with the flow paths of the plurality of ports 11; a spool 13 positioned in the internal flow path 121 of the case and controlling the flow direction of the working fluid by closing or opening the plurality of ports and blocking a portion of the internal flow path; and a spool drive unit 15 that applies 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 comprise a packing 14 for shielding.

[0038] The spool drive unit 15 described above may consist of a solenoid coil and a movable plunger 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 identical in that the movable plunger moves in a linear motion due to the magnetic field generated by the solenoid coil. However, the former differs in that the movable plunger is directly connected to the spool 13, and the spool 13 operates due to the linear motion of the movable plunger, while the latter operates the spool 13 due to the pressure of the high-pressure fluid that flows in through the pilot valve when the movable plunger opens the pilot valve. The spool drive unit 15 may be located at one end or both ends of the case 12. If the spool drive unit 15 is located at only one end of the case 12, an elastic body such as a spring (not shown) may be located at the other end of the case 12. In this case, when the spool drive unit 15 is turned on by an ON operation signal automatically or manually issued by the control unit, the spool 13 can resist the pressure applied to the elastic body and move toward the elastic body. Conversely, when the spool drive 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 drive unit 15 due to the restoring force of the elastic body. The operation signal is an electrical signal applied by the control unit to the solenoid coil.

[0039] Figure 1(a) is a schematic diagram showing that the piston rod 21 moves forward due to the operation of a direction change 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 operating signal to the spool drive unit 15. The spool drive unit 15 can be operated remotely by automation or directly by an operator for equipment inspection or maintenance. When the spool drive unit 15 is operated remotely, the operating signal may be a remote signal applied to the spool drive unit 15 via a process control unit (not shown). When operated directly by an operator, the operating signal may be the operator's valve power on / off operation. Meanwhile, once the movement of the spool 13 is complete, the working fluid's flow direction is restricted by the spool 13, and it flows from the fourth port 11d towards the second port 11b. The working fluid is supplied through the second port 11b, pressurizing the piston rod 21 to the left, causing the piston rod 21 to move forward. In the present invention, the operating time of the direction change valve means that from the start of the operating signal, the direction of supply of the working fluid is changed, and the changed direction of supply of the working fluid is maintained until sufficient working fluid is supplied to provide hydraulic pressure capable of linear motion to the piston rod.

[0040] In this specification, the operating time or time required for the direction change valve means the time from the start of the operating signal applied to the spool drive unit until sufficient hydraulic pressure is transmitted to the piston rod, enabling the spool to be driven and the direction of the piston rod to be changed.

[0041] Figure 1(b) is a schematic diagram showing that the piston rod 21 moves backward due to the operation of a direction change valve 10 having five ports 11a-11e. First, an operating signal is applied to the spool drive unit 15 to move the spool 13 to the right on the internal flow path 121. Once the movement of the spool 13 is complete, the working fluid's flow direction is restricted by the spool 13, and it flows from the fourth port 11d towards the first port 11a. The working fluid is supplied through the first port 11a, pressurizing the piston rod 21 to the right, causing the piston rod 21 to move backward.

[0042] The left-right movement of the spool 13 described above is merely one example; depending on the design of the directional valve, the piston rod 21 may also move backward when the spool 13 moves to the left. Furthermore, although the directional valve 10 with five ports 11a-11e was described as a reference for convenience of explanation in Figures 1(a) and 1(b), the present invention is not necessarily limited to this.

[0043] Figure 2 is a schematic diagram showing the location of the failure in the direction change valve 10.

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

[0045] Figure 3 is a graph showing the operating time distribution of a normal directional control valve and a non-normal directional control valve.

[0046] Figure 3(a) is a graph showing the number of times the operating time of a normal directional control valve was measured over a predetermined period of time. As shown, in the case of a normal directional control valve, a normal distribution curve appears in the normal range (approximately 0.2 seconds to 0.5 seconds). In contrast, Figure 3(b) is a graph showing the number of times the operating time of a non-normal directional control valve was measured over a predetermined period of time. As shown, in the case of a non-normal directional control valve, a non-normal distribution is shown in the range outside the normal range (more than approximately 0.5 seconds). Thus, the operating time of a directional control valve is closely related to the deterioration of its operation. The present invention selects the operating time of such a directional control valve as a factor that can represent the failure of the directional control valve, and, as described later, calculates a statistical deterioration index and its degradation index value based on the above operating time data of the directional control valve, and uses this degradation index value to predict a directional control valve that is likely to fail. The above statistical deterioration index is based on operating time data that can represent the failure of the directional control valve, and therefore can similarly represent the failure of the directional control valve. In this respect, it differs from conventional techniques that diagnose directional valve malfunctions simply based on the number of times they are opened and closed.

[0047] Figure 4 is a block diagram illustrating the concept of failure prediction according to the present invention.

[0048] As shown in Figure 4(a), the parts of the steering valve exhibit abnormal symptoms before failure occurs. If failure of a part cannot be predicted from these abnormal symptoms, the failure may occur, potentially causing a breakdown (BM) of part or all of the factory's manufacturing system. Replacing the part after a breakdown is highly uneconomical and reduces manufacturing efficiency.

[0049] On the other hand, as shown in Figure 3(b), the present invention allows for the detection of abnormal symptoms in the steering valve components in advance using a steering valve failure prediction system or method that employs a steering valve failure prediction algorithm unique to the present invention. In other words, by predicting the failure of the steering valve in advance before a failure occurs, it is possible to inspect the steering valve components for abnormalities and replace the problematic components, thereby preventing the interruption of system operation that occurred in the past. The technical idea of ​​the present invention is not to diagnose whether or not a steering valve is faulty, or to analyze the cause of the failure, but rather to predict in advance which steering valves are expected to fail or have a high probability of failing before a failure occurs. Therefore, even if a steering valve is currently normal and not faulty, it may be determined to be a steering valve expected to fail. In this respect, it differs from technologies that diagnose failures or only determine whether or not a steering valve is normal.

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

[0051] (First Embodiment) Figure 5 is a schematic diagram showing a failure prediction system for a direction change valve according to one embodiment of the present invention.

[0052] The present invention includes a data acquisition unit 110 that repeatedly detects the operating time of multiple direction change valves 10 that communicate with a cylinder 20 equipped with a piston rod 21 and change the direction of operation 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 multiple operating time data for each direction 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 direction change valve 10 based on the operating time data; and a determination unit 130 that ranks the deterioration index values ​​calculated for each direction change valve 10 by magnitude, and determines that the direction change valve 10 having a higher value above a predetermined range among the ranked deterioration index values ​​is a direction change valve 10 expected to fail.

[0053] The operating time of the direction change valve 10 referred to in this invention includes one or more of the following: a first time, which is the time it takes for the direction of supply of the working fluid to be changed by the operating signal of the direction change valve 10 and for the piston rod 21 to start moving forward; a second time, which is the time it takes for the direction of supply of the working fluid to be changed by the operating signal of the direction change valve 10 and for the piston rod 21 to start moving backward; and the sum of the first and second times. As shown in Figure 2, when the operation of the direction change valve 10 deteriorates, not only the first and second times, which are the times when the piston rod 21 starts moving forward or backward, but also the sum of the first and second times will all be delayed. Therefore, the first time, the second time, and the sum of the first and second times, as well as any combination of the first and second times, can all be used as operating time data to form the basis for calculating the deterioration index value. In this embodiment, for the convenience of calculation, the first time and the second time are treated as separate and independent operating time data. In other words, since the time it takes for the piston rod 21 to start moving forward and the time it takes to start moving backward due to the direction change valve are usually about the same, the first time data and the second time data obtained during one reciprocating motion of the piston rod 21 were considered as separate data. This makes it possible to obtain two operating time data for the reciprocating motion of one piston rod 21. For example, assuming there are 50 direction change valves to be predicted to fail, the direction change valve must operate twice for the piston rod of each cylinder to reciprocate, so 100 operating time data can be obtained for the reciprocating motion of each piston rod. In other words, in this embodiment, the first time and the second time are each considered as one statistical data to determine which direction change valve is likely to fail. Of course, it is possible to predict a failure by obtaining only one of the first or second time as operating time data. However, obtaining both data includes data that encompasses all operations of the direction change valve related to the reciprocating motion of the piston rod 21, which has the advantage of making the failure determination of the direction change valve more rigorous and improving the predictability of failures.

[0054] Operating 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 Figure 5. Sensor S1 installed at the end detects when the piston rod 21 reaches its forward end. Similarly, it detects when the piston rod 21 moves away from its forward end. Sensor S2 installed at the start end detects when the piston rod 21 reaches its reverse end. Similarly, it detects when the piston rod 21 moves away from its reverse end. These sensors can be installed inside or outside the cylinder. These sensors could be, for example, limit switches that indicate the position of the piston at the tip of the piston rod by switching them on or off.

[0055] The data acquisition unit 110 can acquire as operating time data the time elapsed from when an operating signal is applied to the spool drive unit 15 until when the sensors S1 and S2 detect the disengagement of the piston rod 21. For example, the time elapsed from when an operating signal is applied to the spool drive unit 15 until the piston rod disengagement detection signal is generated by the sensor S2 installed at the starting end can be defined as the first time. The time elapsed from when an operating signal is applied to the spool drive unit 15 until the piston rod disengagement detection signal is generated by the sensor S1 installed at the end can be defined as the second time. The directional change valve operates continuously throughout the equipment operating time. The reciprocating motion of the cylinder is performed by the operation of the directional change valve. Therefore, when one cylinder reciprocates, the data acquisition unit 110 can acquire the first time and the second time as data for the number of reciprocating motions. Since the present invention determines which directional change valve is likely to fail by relatively comparing the operating times of each directional change valve, multiple operating time data are acquired for each directional change valve. For this purpose, the data acquisition unit 110 may include a data collection device and a database for storing the data.

[0056] The above operating time data is acquired multiple times for each directional valve over the elapsed time of equipment operation. For example, if one cylinder moves back and forth 1,800 times per hour, 3,600 operating time data points can be obtained per hour, 10,800 after 3 hours, and 86,400 after 24 hours. Also, if a directional valve operates repeatedly over 30 days, 86,400 x 30 operating time data points can be obtained. If statistical indicators are calculated using such a large amount of data at once, the amount of data that needs to be processed becomes excessively large. In this case, a heavy load is placed on the algorithm or program for failure prediction, making it impossible to quickly determine failures. Furthermore, as the number of directional valves to be predicted for failure increases, the amount of data to be processed increases even further, and the above problems become more pronounced.

[0057] Therefore, when acquiring data for failure prediction and when calculating degradation index values ​​using that data, the so-called grouping technique is used. Grouping is a statistical technique for reducing the amount of data, which involves grouping data by subject, period, or characteristic, and treating each group as a single data point, thereby reducing the amount of data that needs to be processed.

[0058] Figure 6 is a graph showing the operation time data for a change of direction valve grouped and statistically visualized. Referring to Figure 6(a), there are 3,600 operation time data points per hour for a change of direction valve, and 10,800 points for 3 hours of operation. However, as shown in Figure 6(b), the data can be grouped into three data groups. When the overall data regarding the operation time of the change of direction valve is shown as in Figure 6(a), it is not possible to clearly grasp the trend. However, as shown in Figure 6(b), grouping the data and visually displaying it has the advantage of allowing one to grasp at a glance the change in operation time data according to the elapsed time of equipment operation. Furthermore, if statistical indicators such as standard deviation and first quartile are calculated based on the total number of data points as in Figure 6(a), the amount of data processing or computation increases, as mentioned above. However, as shown in Figure 6(b), by calculating statistical indicators such as standard deviation for each data group for each time period and averaging the standard deviation values ​​of the three data groups, it is possible to obtain a standard deviation value corresponding to the total number of data points while significantly reducing the amount of data processing.

[0059] In Figure 6, operating time data acquired over a one-hour period is grouped into a single data set. However, the unit time used as the basis for acquiring the grouped data sets can be 3 hours, 8 hours, 24 hours, or even longer. For example, multiple 24-hour intervals can be defined as a single unit time interval, and the operating time data of the directional control valves that operated within each unit time interval can be grouped into a single data set. In this case, one data set will be a group of operating time data for a single directional control valve that operated repeatedly over a 24-hour period of equipment operation. Using this method, multiple data sets can be obtained over a specific inspection period, such as one week, several weeks, or one month. For example, to predict the failure of a directional control valve that has been in operation for 30 days in a factory, if data sets are acquired using one day (24 hours) as the unit time interval, the data acquisition unit can acquire 30 data sets for each directional control valve.

[0060] Figure 7 is a schematic diagram showing the failure prediction mechanism of the directional valve failure prediction system 100 according to one embodiment of the present invention.

[0061] The above diagram shows that operating time data sets were acquired for a total of n directional control valves V1 to Vn over a 30-day inspection period. In other words, in this case, one day (24 hours) is used as the unit time interval, and over the inspection period (30 days) consisting of 30 unit time intervals, the operating time data for each directional control valve was grouped for each unit time interval to acquire the operating time data sets. Therefore, 30 operating time data sets are obtained for each individual directional control valve such as V1, and these data sets are collected and stored in the data acquisition unit.

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

[0063] Statistical degradation indicators include, but are not limited to, the mean, standard deviation, skewness, kurtosis, first quartile, median, third quartile, skewness change, and kurtosis change of each directional valve's operating time data. Even if multiple directional valves operate for the same amount of time, the tendency for directional valves to exhibit failure symptoms will differ due to various causes. By measuring the above-mentioned statistical degradation indicators for such directional valves, it is possible to select directional valves that are relatively degraded. In other words, this invention does not absolutely compare the performance or operating time of individual directional valves, but rather compares the operating time data of each directional valve with the statistical degradation indicators based on it to determine directional valves that are presumed to fail as directional valves expected to fail. For example, if the operating time of a particular directional valve is longer than average, it is highly likely that its performance will deteriorate and it will be determined to be a directional valve expected to fail. Similarly, if a particular directional valve shows a difference from other directional valves in other statistical degradation indicators such as the standard deviation, skewness, and kurtosis of the operating time data, it is highly likely that it will be determined to be a directional valve expected to fail.

[0064] Of the statistical degradation indicators mentioned above, the standard deviation is a characteristic value that shows the degree of dispersion of data around the mean. The first quartile is the value at the 1 / 4 position from the bottom when the data is sorted from lowest to highest value and then divided into four equal parts. The median and third quartile are the values ​​at the 1 / 2 position and 3 / 4 position from the bottom, respectively, when the data is sorted from lowest to highest value and then divided into four equal parts.

[0065] Figure 8 is a schematic diagram showing an example of a statistical degradation index based on the operating time of a directional valve. Figure 8(a) shows the relationship between the third quartile, median, first quartile, and mean described above. As shown in the upper graph of Figure 8(b), skewness is an index that shows the asymmetry of the data relative to the normal distribution curve, and kurtosis, as shown in the lower graph of Figure 8(b), is a measure that shows the high or low of the data relative to the normal distribution curve. The above statistical degradation indices can be quantified and calculated as degradation index values ​​by a predetermined computing program based on the operating time data of each directional valve. Since the operating time of a directional valve is a factor that can reflect or represent the degradation, failure, or failure symptoms of the directional valve, the above statistical degradation index calculated based on its operating time can also represent the failure of the directional valve. The degradation index value calculation unit of the present invention is equipped with a predetermined computing program, so that it can calculate the degradation index value of the statistical degradation index of individual directional valves for each group of operating time data for each unit time interval as shown in Figure 7.

[0066] On the other hand, in this invention, a faulty direction change valve is determined using at least multiple statistical degradation indices. No matter how much data is available to form the basis for fault determination, if a fault is determined by comparing only one statistical degradation indice, the probability of fault prediction will inevitably decrease. Therefore, two or more statistical degradation indices are selected from among the statistical degradation indices based on operating time data, and the degradation index value is calculated. When selecting statistical degradation indices, it is best to select indices with as different statistical characteristics as possible. For example, by selecting one or more indices that show quantitative changes in data, such as the mean, standard deviation, first quartile, median, and third quartile, and one or more indices that show the asymmetry or trend of change in data, such as skewness and kurtosis, the accuracy of fault prediction can be further improved.

[0067] Referring again to Figure 5, the present invention includes a determination unit 130 that determines a faulty steering valve based on the degradation index value of the statistical degradation index. The determination unit 130 ranks the degradation index values ​​of the statistical degradation index calculated for each steering valve according to their magnitude in order to compare multiple steering valves relatively. Furthermore, it assigns a predetermined score to steering valves that have a higher value than a predetermined range among the ranked degradation index values, and determines the faulty steering valve based on the sum of these predetermined scores.

[0068] For example, the standard deviation and skewness values ​​of operating time data obtained over the same equipment operating time for multiple target direction change valves can be calculated for each valve and a ranking can be assigned. A score of, for example, 1 point can be assigned to the standard deviation and skewness values ​​of the direction change valves with the highest rankings, and a direction change valve that has received scores for all of its standard deviation and skewness values, i.e., a score of 2 points, can be determined to be a direction change valve prone to failure. However, this is merely an example, and the specific judgment conditions, such as the type of statistical degradation index selected, the criteria for selecting the highest values, and the magnitude of the scores, can be diversely selected and determined by considering various factors such as the characteristics of the direction change valve being evaluated, equipment operating conditions, and factory operating conditions. In other words, the detailed failure prediction algorithm by the judgment unit can be adjusted in any way.

[0069] Referring again to Figure 7, the determination unit 130 can determine which directional control valve is likely to fail based on the statistical degradation index of each of the 30 operating time data sets acquired for multiple (n) directional control valves V1 to Vn. At this time, the degradation index values ​​of the statistical degradation index calculated from the total operating time data of each directional control valve for the entire 30-day inspection period are ranked, and a predetermined score is assigned to determine which directional control valve is likely to fail.

[0070] However, as mentioned above, in this case the amount of data to be processed increases geometrically, placing an excessive load on the system and making rapid calculation difficult. Furthermore, comparing the operating time data for the entire 30 days for each directional valve is not only inefficient but can also reduce the reliability of failure prediction. In other words, failure of a directional valve typically occurs after repeated use for a certain period. Therefore, determining a directional valve expected to fail based on a degradation index value calculated based on the operating time data group belonging to the initial unit time interval of the inspection period is inefficient in that the probability of failure is not high. It is reasonable to determine a directional valve expected to fail based on the operating time data of each directional valve that operated for a specific (unit) time interval after it had operated for at least a certain period or a predetermined unit time interval. That is, as illustrated in Figure 7, for example, a directional valve expected to fail can be determined based on the operating time data of a directional valve that operated for one day on the 30th day after it had operated for 29 days. In this case, since all directional valves were used for the same period (29 days), the deterioration trend of each directional valve becomes clear. Therefore, by comparing the deterioration index values ​​calculated for the final day, the 30th day (hereinafter referred to as the final deterioration index value), the degree of deterioration or the likelihood of failure of each directional valve can be reliably grasped. In this respect, as shown in Figure 5, the data acquisition unit 110 of the directional valve failure prediction system 100 of this embodiment needs to acquire data for the final period after use for at least a certain period among multiple unit time intervals. The deterioration index value calculation unit 120 also calculates the final deterioration index value based on this final data (group), and the determination unit 130 also ranks the above final deterioration index value for each directional valve to determine which directional valve is likely to fail. However, in the present invention, "final period" and "final deterioration index value" are not limited to the final unit time interval after repeated use for a certain period (for example, the unit time interval of the 30th day in Figure 7) or the deterioration index value calculated based on the operating time data group (D30) for that unit time interval. Referring to Figure 7, for example, a degradation index value can be calculated based on one of the operating time data sets D28, D29, or D30 after the directional valve has been in operation for 27 days.In this case, the end date can be one of 28, 29, or 30 days, and the degradation index value calculated based on the data set for the selected end date becomes the end date degradation index value. In other words, the end date in this embodiment can be any specific time period or specific unit time period after the directional valve has been used (operated) for a certain period or a predetermined unit time period, and does not necessarily mean the final unit time period immediately after use for a certain period. Furthermore, the "certain period" used can be freely selected depending on the purpose of inspection or failure prediction, the characteristics of the directional valve, etc. In Figure 7, it is assumed that the directional valve was used for 29 days, but it is also possible to predict the failure of the directional valve after use for a longer or shorter period.

[0071] Furthermore, the term "end time" does not necessarily refer to only a single unit of time interval.

[0072] Figure 9 is a schematic diagram showing the failure prediction mechanism of a directional valve failure prediction system according to a modified example of one embodiment of the present invention. Referring to Figure 9, the end-of-life degradation index values ​​calculated based on the operating time data sets D28, D29, and D30 for days 28, 29, and 30, respectively, after the directional valve has been in operation for 27 days, can be averaged, and this average end-of-life degradation index value can be adopted as the degradation index value for determining whether the directional valve is likely to fail. Therefore, in the example of Figure 9, strictly speaking, the end of life is 3 days, and the degradation index value for failure prediction is the average end-of-life degradation index value obtained by averaging the degradation index values ​​calculated based on each operating time data set for the 3 days. As shown in Figure 7, predicting failure using an average end-of-life degradation index value calculated based on multiple unit time intervals or operating time data sets may be more advantageous in terms of statistical or mathematical data reliability than predicting failure using an end-of-life degradation index value calculated based on a single unit time interval or a single unit of operating time data sets.

[0073] Referring again to Figure 7, after the directional control valves have been used (operated) for 29 days, the process of selecting standard deviation A and skewness B as statistical degradation indices for the operating time data set obtained based on the operating time data of the directional control valves on the 30th day, and determining the degradation index values ​​of the standard deviation and skewness for each directional control valve. In this case, D30 is the operating time data set of the directional control valves that operated for 24 hours on the 30th day, and as mentioned above, it is a group of 86,400 data points. Based on this operating time data set D30, the standard deviation and skewness values ​​can be determined for each directional control valve and ranked accordingly.

[0074] Referring again to Figure 9, this example shows the process of selecting standard deviation A and skewness B as statistical degradation indices based on each operating time data group D28, D29, and D30 obtained based on the operating time data of the directional valves from day 28 to day 30 after the directional valves have been used (operated) for 27 days, and then calculating the average end-of-life degradation index value for each directional valve by reaveraging the standard deviation value and skewness value calculated for each operating time data group. The above average end-of-life degradation index value is ranked for each directional valve, and a predetermined score is assigned to the directional valves that have a value above a predetermined range, and the directional valves expected to fail can be determined based on the sum of these predetermined scores.

[0075] A specific example of determining a faulty direction change valve based on the failure prediction mechanism shown in Figures 5 and 7 will be explained.

[0076] Table 1 below shows the ranking of 29 directional control valves that were operated for 29 days, based on the calculation of their final degradation index values ​​on day 30, using five statistical degradation indices: skewness, kurtosis, first quartile, third quartile, and standard deviation.

[0077] Table 2 shows the results of assigning a score of 1 point to the top 25% (7th grade, etc.) or higher of the ranked end-of-life degradation index values ​​for directional valves.

[0078] [Table 1]

[0079] [Table 2]

[0080] In Table 2, directional control valves with a total score of 2 or more were identified as directional control valves likely to malfunction. In this case, directional control valves 1 and 2 are identified as directional control valves likely to malfunction. Therefore, these directional control valves may be malfunctioning and need to be inspected.

[0081] In the above example, one point was assigned to the top 25%, and directional control valves with a total score of two points or more were identified as directional control valves likely to fail. However, the percentage values ​​for the top values, the number of points assigned, and the total score used as the criterion for identifying directional control valves likely to fail can be changed. Therefore, even when predicting the failure of a directional control valve using the failure prediction system of the present invention, a number of failure prediction algorithms can be derived for various cases. Importantly, according to the present invention, multiple statistical degradation indices can be selected based on multiple operating time data, each degradation index value can be derived from them, these values ​​can be ranked, and directional control valves likely to fail can be identified by the sum of predetermined scores. Therefore, within the scope of such a failure prediction system or failure prediction method, the detailed failure prediction algorithm can be modified to increase statistical reliability.

[0082] (Second Embodiment) Figure 10 is a schematic diagram showing a fault prediction system 200 for 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 indicators such as standard deviation, skewness, and kurtosis, it introduces additional statistical degradation indicators, such as changes in the mean, skewness, and kurtosis.

[0084] In other words, among the degradation index values ​​used to determine a faulty steering valve, not only the average value but also how much the average has changed, or how much the degradation index values ​​for strain and kurtosis have changed, are closely related to the operational degradation of the steering valve. Therefore, if we use the changes in these statistical degradation index values ​​as new statistical degradation indexes along with existing statistical degradation indexes to determine the degradation index values, the reliability of failure prediction can be further improved.

[0085] Figure 11 is a schematic diagram illustrating the changes in such statistical degradation indicators. Figure 11(a) shows a change in skewness, and Figure 11(b) shows a change in kurtosis. In this embodiment, when selecting multiple statistical degradation indicators for failure prediction, one or more of the usual statistical degradation indicators (e.g., standard deviation) may be selected, and one or more of the changes in the statistical degradation indicators (e.g., changes in skewness) may be selected as new statistical degradation indicators.

[0086] In order to add the change in a statistical degradation index to a new statistical degradation index, it is necessary to know the values ​​of that degradation index before and after the change. For this reason, the data acquisition unit 210 of the failure prediction system 200 in this embodiment needs to acquire at least all of the initial and final operating time data for each steering valve.

[0087] Figures 12 and 13 are schematic diagrams showing the failure prediction mechanism of the directional valve failure prediction system according to the embodiment of Figure 10.

[0088] As shown in Figure 12, based on the operating time data set D1 from the first day, which is the initial day of the 30-day inspection period, statistical degradation indices such as standard deviation A and skewness B can be selected, and their degradation index values ​​can be calculated. Similarly, based on the operating time data set D30 from the end of the 30th day, after the 29 days of use of the directional valve, statistical degradation indices such as standard deviation A and skewness B can be selected, and their degradation index values ​​can be calculated. In addition, skewness values ​​based on the D1 data set and skewness values ​​based on the D30 data set can be determined, and the difference between them can be used as the skewness change value. This skewness change value C can be used as a new statistical degradation index along with the standard deviation and skewness degradation indices.

[0089] Specifically, as shown in Figures 10 and 12, the degradation index calculation unit 220 calculates three parameters as degradation index values: the standard deviation A and skewness B at the final stage (day 30), and the skewness change value C, which is the difference in skewness values ​​between day 1 and day 30. The determination unit 230 ranks these three degradation index values, assigns a predetermined score to the directional control valves that have higher values ​​above a predetermined range among the ranked values, and determines which directional control valves are likely to fail based on the sum of the predetermined scores.

[0090] On the other hand, the initial data set that forms the basis for calculating the change in the statistical degradation index, or the initial statistical degradation index value calculated based on the initial data set, is not limited to a single unit time interval or the initial statistical degradation index value based thereon.

[0091] Referring to Figure 13, for example, a set of operating time data D1 to D7 for seven unit time intervals of one week, from day 1 to day 7, can be used as the basic data for calculating the initial degradation index value. In this case, a degradation index value (e.g., mean, skewness) is calculated for each of the data sets D1 to D7, and the average of these degradation index values, which is the initial degradation index value, is taken as the initial degradation index value. Then, the final degradation index value (mean, standard deviation A, skewness value B) on day 30 after 29 days of use is calculated, and the difference (e.g., change in mean or change in skewness C') obtained by subtracting the final degradation index value from the average of the initial degradation index values ​​can be introduced as an additional statistical degradation index.

[0092] Furthermore, in this case, similar to Figure 9, the end-of-life degradation index value used as the basis for calculating the above difference value is not only based on a single unit time interval, but can also be an average end-of-life degradation index value based on multiple operating time data sets from multiple unit time intervals. Therefore, the difference obtained by subtracting the end-of-life degradation index value or the average end-of-life degradation index value from the initial degradation index value for the operating time data set of the initial unit time interval within the inspection period, or the average value of the initial degradation index values ​​obtained for the operating time data set of the initial unit time interval, can be introduced as an additional statistical degradation index that can represent the failure of the steering valve.

[0093] A specific example of determining a faulty direction change valve based on the fault prediction mechanism shown in Figures 10 and 13 will be explained.

[0094] Similar to the example in the first embodiment, five statistical degradation indicators were selected: skewness, kurtosis, first quartile, third quartile, and standard deviation. The final degradation indicator values ​​on the 30th day were calculated and ranked for 29 directional valves that had been in operation for 29 days.

[0095] On the other hand, in this example, the initial degradation index value was calculated by averaging the skewness, kurtosis, and mean over the initial 7-day unit time interval. The difference (absolute value) between this value and the skewness, kurtosis, and mean value (final degradation index value) on day 30 was determined, and the resulting changes in skewness, kurtosis, and mean were used as a new statistical degradation index. This deteriorated surface value was then ranked along with the degradation index values ​​of the five statistical degradation indices mentioned above and is shown in Table 3.

[0096] Table 4 shows the results of assigning a score of 1 point to the top 25% (7th place, etc.) or higher of the eight ranked end-of-life degradation index values, including these differences.

[0097] [Table 3]

[0098] [Table 4]

[0099] In Table 4, a steering valve with a total score of 3 or more was identified as a steering valve likely to malfunction. In this case, steering valve number 1 is identified as the steering valve likely to malfunction. Therefore, this steering valve may be malfunctioning and needs to be inspected.

[0100] The data acquisition units 110 and 210 of the failure prediction systems 100 and 200 of the present invention may include a data collection device and a database for storing the data, as described above. The data acquisition units 110 and 210 may include a predetermined statistical program for grouping data into groups. The degradation index value calculation units 120 and 220 may include a predetermined computing program to calculate a selected statistical degradation index or the difference between statistical degradation indexes. The determination units 130 and 230 may include a data reading device, an analysis device, and a calculation device, etc., to rank the calculated degradation index values, assign predetermined scores, and determine the failure prediction direction change valve by calculating the sum of these scores. Alternatively, the data acquisition units 110 and 210, the degradation index value calculation units 120 and 220, and the determination units 130 and 230 may be a computing device 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 configured to communicate with each other.

[0101] Furthermore, the present invention provides a method for predicting failures of a directional control valve, using the directional control valve failure prediction system described above.

[0102] Specifically, the method includes the steps of: repeatedly detecting the operating time of multiple direction change valves that communicate with a cylinder equipped with a piston rod, supply fluid to the cylinder, and change the direction of operation of the piston rod by changing the direction of fluid supply, over the elapsed time of equipment operation, and acquiring multiple operating time data for each direction change valve; selecting multiple statistical degradation indices that can represent the failure of the direction change valve, and calculating the degradation index value of the selected statistical degradation indices based on the operating time data; ranking each degradation index value for each direction change valve according to its magnitude; assigning a predetermined score to direction change valves that have a higher value above a predetermined range among the ranked degradation index values, and determining which direction change valve is likely to fail based on the sum of the predetermined scores.

[0103] In the stage of acquiring the above-mentioned multiple operating time data, the first time when the piston rod begins to move forward due to the operating signal of the direction change valve, the second time when the piston rod begins to move backward due to the operating signal of the direction change valve, or the sum of these times can be acquired as operating time data. In this case, if the inspection period consists of multiple unit time intervals in order to reduce the amount of data to be processed, the operating time data for each direction change valve can be grouped for each unit time interval to acquire individual sets of operating time data.

[0104] Subsequently, based on the above operating time data, several statistical degradation indices that can represent the failure of the directional valve are selected. Examples of such statistical degradation indices include the mean, standard deviation, first quartile, median, third quartile, skewness, and kurtosis of the operating time data for each directional valve. Once the statistical degradation indices are selected, the degradation index values ​​for each selected statistical degradation indice are calculated. In this case, if the operating time data is grouped as described above into individual operating time data sets, the degradation index value for each directional valve can be calculated for each operating time data set.

[0105] Next, the calculated degradation index values ​​are ranked according to the size of each steering valve. Since these are degradation index values, the steering valves with the highest values ​​among the ranked degradation index values ​​are most likely to be the steering valves expected to fail.

[0106] Subsequently, a predetermined score is assigned to the directional control valves that have a value above a predetermined range among the ranked deterioration index values, and the directional control valves expected to fail are determined based on the sum of the predetermined scores.

[0107] When determining which direction change valve is likely to fail, it is preferable that the underlying degradation index value is calculated based on operating time data for a specific time interval after the direction change valve has been used repeatedly for a certain period. In this case, if the inspection period consists of multiple unit time intervals, the final degradation index value calculated for the group of operating time data for a specific unit time interval after operation for a predetermined unit time interval within the inspection period, or the average value of the final degradation index value for the group of operating time data for the specific unit time interval, can be ranked and used as the basis for determining which direction change valve is likely to fail.

[0108] On the other hand, the change in one or more statistical degradation indicators selected from the above-mentioned multiple statistical degradation indicators may be introduced as an additional statistical degradation indicator for determining the failure prediction direction change valve. In this case, in order to obtain the above change in value, the difference obtained by subtracting the final degradation indicator value or the average value of the final degradation indicator values ​​from the initial degradation indicator value or the average value of the initial degradation indicator values ​​calculated for the initial unit time interval or operating time data group within the inspection period may be introduced as the change in the above-mentioned statistical degradation indicator.

[0109] Figure 14 is a schematic diagram showing the fault inspection system 1000 for a direction change valve according to the present invention.

[0110] The above-mentioned fault inspection system for the direction change valve includes the direction change valve fault prediction system 100, 200 of the present invention, which comprises data acquisition units 110, 210, deterioration index value calculation units 120, 220, and determination units 130, 230, as shown in the figure. Furthermore, the direction change valve fault inspection system 1000 is provided with an inspection unit 300 which is connected to the determination units 130, 230 of the direction change valve fault prediction system 100, 200 and measures whether or not there is an air leak in a direction change valve that has been determined by the determination unit to be a direction change valve with a predicted failure.

[0111] The inspection unit 300 described above could be, for example, an ultrasonic acoustic camera. An ultrasonic acoustic camera is an industrial camera that can measure ultrasonic waves, which are inaudible to humans, and capture images of gas leaks and electric arcs in real time. It detects the ultrasonic energy generated at the point of air leakage using a sensor array, and displays the leak location against a visible light image of the area under inspection, allowing for rapid detection of the leak location. The images can also be saved in JPEG or MP4 video format.

[0112] The present invention also provides a method for inspecting a turn signal valve failure, which includes a method for predicting the failure of the turn signal valve described above. The inspection method includes the steps of inspecting a turn signal valve that has been determined to be a turn signal valve with a predicted failure by the turn signal valve failure prediction method described above, and replacing a turn signal valve in which a failure has been found during the inspection.

[0113] With this invention, by having the inspection unit inspect only the directional control valves that are determined to be malfunctioning, the inspection time for the directional control valves can be significantly reduced, and the cost and personnel required for inspecting the directional control valves can be significantly reduced.

[0114] <Examples> The present invention's failure prediction system for direction change valves was used to determine which direction change valves were likely to fail, based on a cylinder that operates a folding unit that alternately folds two types of bi-cells (negative and positive electrodes) and a separation membrane, and a plurality of direction change valves connected to the cylinder that change the direction of operation of the cylinder. The actual number of direction change valve failures was also evaluated.

[0115] Table 5, Example 1, shows the results of evaluating a total of 29 directional control valves at different evaluation dates (evaluation order). Table 6, Example 2, shows the results of evaluating using an algorithm that modified and supplemented detailed evaluation conditions (such as selection criteria for the top percentage) based on the results of the second evaluation.

[0116] <Example 1> [Table 5]

[0117] In Table 5, the over-detection rate, under-detection rate, and detection rate are expressed by the following formulas.

[0118] Failure rate = (Total number of recommendations - Actual number of failures out of total recommendations) / Total number of checks Unchecked rate = (Total number of failures - Number of recommended failures) / Total number of inspections Detection rate = Actual number of failures out of total recommendations / Total number of recommendations

[0119] As shown in Table 5 above, in the second evaluation, the over-detection rate decreased compared to the first evaluation, but the undetected rate and detection rate increased. Therefore, the selection criteria for the top percentage were changed during 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 third and fourth orders evaluated with the complementary algorithm, the rate of uninspected items was 0%, and the rate of over-inspected items was 25% or less. Therefore, when evaluating the failure of the steering valve using the complementary algorithm, the number of inspections and inspection time can be significantly reduced.

[0122] The above description is merely illustrative of the technical concept of the present invention, and a person with ordinary skill in the art to which the present invention pertains will be able to make various modifications and variations without departing from the essential characteristics of the present invention. Therefore, the drawings disclosed herein are for illustrative purposes only, not to limit the technical concept of the present invention, and the scope of the technical concept 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 concepts within an equivalent scope should be interpreted as being included within the scope of the present invention.

[0123] On the other hand, while terms indicating direction such as up, down, left, right, front, and back are used in this specification, these terms are merely for convenience of explanation, and it is self-evident that they can change depending on the position of the object in question, the observer's position, etc. [Explanation of symbols]

[0124] 10: Direction change valve 11: Port 11a: Port 1, 11b: Port 2, 11c: Port 3, 11d: Port 4, 11e: Port 5 111: Flow channel 12: Case 121: Internal flow path S1, S2: Sensors 100, 200: Directional valve failure prediction system 110, 210: Data acquisition unit 120, 220: Degradation index value calculation unit 130, 230: Judgment section 300: Inspection Department 1000: Directional control valve fault inspection system

Claims

1. A data acquisition unit repeatedly detects the operating time of multiple direction change valves that communicate with a cylinder equipped with a piston rod and change the direction of operation of the piston rod by changing the direction of supply of the working fluid supplied to the cylinder, over the elapsed time of equipment operation, and acquires operating time data for each direction change valve. A deterioration index value calculation unit calculates deterioration index values ​​for multiple statistical deterioration indices that represent a failure of the direction change valve based on the aforementioned operating time data. A failure prediction system for a steering valve, comprising: a determination unit that ranks the degradation index values ​​of the statistical degradation index calculated for each steering valve according to their magnitude, assigns a predetermined score to steering valves that have a higher value than a predetermined range among the ranked degradation index values, and determines which steering valves are likely to fail based on the sum of the predetermined scores.

2. The failure prediction system for a direction change valve according to claim 1, wherein the data acquisition unit selects one or more of the following as the operating time of the direction change valve and acquires data: a first time required for the piston rod to start moving forward in response to the operating signal of the direction change valve, a second time required for the piston rod to start moving backward in response to the operating signal of the direction change valve, and the sum of the first and second times.

3. The data acquisition unit considers the first time and the second time as separate and independent operating time data, A fault prediction system for a directional valve according to claim 2, wherein two operating time data, a first time and a second time, are acquired during one reciprocating movement of the piston rod provided in one cylinder.

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

5. One or more values ​​selected from the group consisting of the mean, standard deviation, first quartile, median, third quartile, skewness, and kurtosis of the operating time data for each direction change valve, The change in one or more statistical degradation indices selected from the group is defined as the statistical degradation index. The failure prediction system for a change of direction valve according to claim 1, wherein the change value is the difference obtained by subtracting the final deterioration index value or the average value of the final deterioration index value calculated for a specific unit time period after operation for a predetermined unit time period from the initial deterioration index value or the average value of the initial deterioration index value calculated for the initial unit time period or the unit time data group within the inspection period.

6. The failure prediction system for a steering valve according to claim 1, wherein the degradation index value of the statistical degradation index is calculated based on the operating time data of each steering valve that operated during a specific time interval after the steering valve was repeatedly used for a certain period of time.

7. The data acquisition unit groups the operating time data for each direction change valve for each unit time interval within the inspection period consisting of multiple unit time intervals, creating individual operating time data sets. The failure prediction system for a directional valve according to claim 1, wherein the deterioration index value calculation unit calculates a deterioration index value for each directional valve for each operating time data group.

8. The determination unit ranks the final deterioration index values ​​calculated for each direction change valve based on the operating time data set for a specific unit time interval after it has operated for a predetermined unit time interval within the inspection target period, assigns a predetermined score to direction change valves that have a higher value than a predetermined range among the ranked final deterioration index values, and determines which direction change valve is likely to fail based on the sum of the predetermined scores, the direction change valve failure prediction system according to claim 7.

9. The determination unit ranks each steering valve by averaging the terminal deterioration index values ​​calculated for each terminal deterioration index value obtained from the group of operating time data for a specific unit time interval after operating for a predetermined unit time interval within the inspection target period, assigns a predetermined score to steering valves that have a higher value above a predetermined range among the ranked average terminal deterioration index values, and determines which steering valve is likely to fail based on the sum of the predetermined scores, the steering valve failure prediction system according to claim 7.

10. A failure prediction system for a directional valve according to claim 8, wherein the initial degradation index value for the operating time data set for the initial unit time interval of the inspection period, or the difference obtained by subtracting the final degradation index value from the average value of the initial degradation index values ​​obtained for the operating time data set for the initial unit time interval, is introduced as an additional statistical degradation index that represents the failure of the directional valve.

11. A failure prediction system for a directional valve according to claim 9, wherein the initial degradation index value for the operating time data set for the initial unit time interval of the inspection period, or the difference obtained by subtracting the average final degradation index value from the average value of the initial degradation index values ​​obtained for the operating time data set for the initial unit time interval, is introduced as an additional statistical degradation index that represents the failure of the directional valve.

12. A fault prediction system for a steering valve according to any one of claims 1 to 11, A fault inspection system for a directional control valve, comprising: an inspection unit that measures whether or not there is an air leak in a directional control valve that has been determined by the determination unit to be a faulty directional control valve.

13. The process involves repeatedly detecting the operating time of multiple direction-changing valves, which communicate with a cylinder equipped with a piston rod and change the direction of operation of the piston rod by changing the direction of supply of the working fluid supplied to the cylinder, over the elapsed time of equipment operation, and acquiring multiple operating time data for each direction-changing valve. The steps include selecting a number of statistical degradation indicators that represent a failure of the aforementioned direction change valve, and calculating the degradation indicator value of the selected statistical degradation indicators based on the operating time data, The first step is to rank the respective deterioration index values ​​for each direction change valve according to their size. A method for predicting failure of a steering valve, comprising the steps of: assigning a predetermined score to steering valves that have upper values ​​above a predetermined range among the ordered deterioration index values; and determining which steering valve is likely to fail based on the sum of the predetermined scores.

14. The method for predicting failure of a direction change valve according to claim 13, wherein the change values ​​of one or more statistical degradation indicators selected from the aforementioned plurality of statistical degradation indicators are introduced as additional statistical degradation indicators for determining the direction change valve that is likely to fail.

15. A step of inspecting a direction change valve that has been determined to be a direction change valve with a predicted failure according to the direction change valve failure prediction method described in claim 13 or 14, A method for inspecting a steering valve, including the step of replacing a steering valve that has been found to be faulty during inspection.

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