Method for predictive maintenance of machine through degree of current waveform imbalance of multiple power units

Abstract

Disclosed is a method for the predictive maintenance of a machine through the degree of current waveform imbalance of multiple power units, in which, by means of collecting current waveforms on the basis of current values consumed in power units of a machine, and overlapping the collected current waveforms with each other, thereby detecting the degree of waveform imbalance, signs of mechanical abnormality in the respective power units may be detected, and at the same time, various signs of abnormality such as defects in components associated with the power units of the machine or an error in a control system for controlling the power units may also be detected.

Description

Predictive maintenance method for equipment through current waveform imbalance of multiple power units

[0001] The present invention relates to a predictive maintenance method for a device using a current waveform imbalance of multiple power units, and more specifically, to a predictive maintenance method for a device using a current waveform imbalance of multiple power units, which collects current waveforms based on the current value consumed by each power unit of the device, and detects waveform imbalance by superimposing the collected current waveforms on each other, thereby detecting mechanical abnormalities of each power unit and simultaneously detecting various abnormalities such as defects in components related to the power unit of the device or errors in a control system that controls the power unit, thereby enabling stable predictive maintenance of a device including multiple power units that operate identically.

[0002] In general, various types of equipment are used in various industrial sites, and the stable operation of these equipment is very important.

[0003] If a single piece of equipment in a large-scale transport plant fails, the entire operation of the facility may be halted, resulting in enormous losses.

[0004] Therefore, recently, a predictive maintenance method for equipment has been developed to detect abnormal signs in the power unit (motor, pump, cylinder, compressor, etc.) that actually drives the equipment in advance and prevent huge losses due to sudden equipment failure.

[0005] However, since the conventional predictive maintenance method for equipment only detects abnormal signs in the power unit of the equipment, it is difficult to reliably detect abnormal signs in equipment where two or more power units must operate in the same manner. The reasons for this are as follows.

[0006] First, if an abnormality occurs in which one of the power units operates slightly faster or slower than the other power units due to an error in the control system while multiple power units that drive the device are operating normally, there is a problem in that the conventional predictive maintenance method for the device cannot detect the abnormality of the device because the power units are operating normally.

[0007] For example, if an abnormality such as the above occurs in the power unit that provides power to each wheel on both sides of a gantry crane, a safety accident may occur, such as the gantry crane tilting to one side and falling over or changing its direction of movement.

[0008] Second, while multiple power units that drive the device are operating normally, a problem with a component associated with one of the power units may cause the power unit to operate abnormally momentarily. However, there is a problem in that it is difficult to detect this phenomenon using conventional predictive maintenance methods for devices.

[0009] For example, if the rail that guides the wheels of a gantry crane is damaged or deformed, the power unit that provides power to the wheels passing over the damaged rail may momentarily perform abnormal movements, which may cause various safety accidents.

[0010] Therefore, there is a need to develop a predictive maintenance method for equipment that can reliably perform predictive maintenance on equipment that includes multiple power units that must operate identically.

[0011] The present invention has been proposed to solve the above-mentioned problems, and its purpose is to provide a predictive maintenance method for a device using current waveform imbalance of multiple power units, which can detect mechanical abnormalities of each power unit by collecting current waveforms based on the current value consumed in each power unit of the device, and superimposing the collected current waveforms on each other to detect waveform imbalance, and at the same time, detect various abnormalities such as defects in components related to the power unit of the device or errors in the control system controlling the power unit, thereby performing stable predictive maintenance of a device including a plurality of power units that operate identically.

[0012] In order to achieve the above object, the present invention provides a predictive maintenance method for a device using current waveform imbalance of multiple power units, comprising: an information collection step (S10) of measuring and collecting current waveforms representing current values ​​consumed by each power unit of the device over time in a real-time operating state; a detection step (S20) of detecting waveform imbalance by superimposing current waveforms measured and collected from each power unit of the device in real-time in the information collection step (S10); and a judgment step (S30) of setting a threshold value for the waveform imbalance and determining the device as being in an abnormal state and giving an alarm if the waveform imbalance detected in the detection step (S20) exceeds the threshold value.

[0013] In addition, the present invention further includes a forced partitioning step (S40) for forcibly partitioning the current waveform of each power unit measured and collected in the information collection step (S10) according to a set time interval, and setting the partitioned section as a unit partition section to form a plurality of unit partition sections on the current waveform; wherein the detection step (S20) detects waveform imbalance by superimposing the current waveforms of each power unit on each other, and independently detects the waveform imbalance for the current waveforms of the plurality of unit partition sections partitioned in the forced partitioning step (S40), and the judgment step (S30) is characterized in that if the waveform imbalance for the current waveform of each unit partition section detected in the detection step (S20) exceeds a threshold value, the device is judged to be in an abnormal state and an alarm is generated.

[0014] In addition, in the information collection step (S10), instead of the current value measured and collected from the power unit, one of vibration, noise generated from the power unit, frequency of power supplied to the power unit, temperature, humidity, and pressure of the power unit is selected to measure and collect a waveform such as a current waveform, and the detection step (S20) detects a waveform imbalance based on the waveform measured and collected from the power unit, and the judgment step (S30) is characterized in that it detects an abnormality sign of the device based on the waveform imbalance detected in the detection step (S20) and a threshold value.

[0015] As described above, according to the predictive maintenance method of a device using the current waveform imbalance of multiple power units according to the present invention, the current waveform is collected based on the current value consumed in each power unit of the device, and the waveform imbalance is detected by superimposing the collected current waveforms on each other, thereby detecting mechanical abnormalities of each power unit, and at the same time, various abnormalities such as defects in components related to the power unit of the device or errors in the control system controlling the power unit can be detected together, thereby having the effect of performing stable predictive maintenance of a device including multiple power units that operate identically.

[0016] FIG. 1 is a block diagram of a method for predictive maintenance of a device through current waveform imbalance of a multi-power unit according to an embodiment of the present invention.

[0017] Figures 2 to 7 are drawings for explaining a predictive maintenance method of a device through the current waveform imbalance of the multiple power units illustrated in Figure 1.

[0018] A method for predictive maintenance of a device using current waveform imbalance of multiple power units according to a preferred embodiment of the present invention is described in detail with reference to the attached drawings. Detailed descriptions of well-known functions and configurations that may unnecessarily obscure the gist of the present invention are omitted.

[0019] FIGS. 1 to 7 illustrate a predictive maintenance method for a device using a current waveform imbalance of a multi-power unit according to an embodiment of the present invention. FIG. 1 is a block diagram of a predictive maintenance method for a device using a current waveform imbalance of a multi-power unit according to an embodiment of the present invention, and FIGS. 2 to 7 are drawings each illustrating a predictive maintenance method for a device using a current waveform imbalance of a multi-power unit shown in FIG. 1.

[0020] As illustrated in FIG. 1, the predictive maintenance method (100) of a device using current waveform imbalance of a multi-power unit according to an embodiment of the present invention includes an information collection step (S10), a detection step (S20), and a judgment step (S30).

[0021] The above information collection step (S10) is a step of measuring and collecting a current waveform that represents the current value consumed by each power unit over time in a real-time operating state of a device including at least two or more power units that operate identically.

[0022] Examples of devices that typically have two or more power units that operate identically include a gantry crane, which has a drive motor that provides equal power to each wheel on both sides for linear forward and backward movement, or a train, which has a brake device that provides braking power to each wheel on both sides of the train for braking.

[0023] Of course, in a gantry crane, the power unit would be the drive motor that provides power to the wheels, and in a train, the power unit would be the brake device.

[0024] For convenience of explanation, the method (100) for predictive maintenance of a device through current waveform imbalance of multiple power units of the present invention will be explained based on a gantry crane in which one power unit (drive motor) is formed on each side to provide power to the wheels on both sides, but the technology of the present invention is not limited to such devices.

[0025] That is, when the current waveform is measured and collected from each power unit of the gantry crane operating in real time in the above information collection step (S10), the current waveform of each power unit is collected as shown in Fig. 2, and it can be seen that current waveforms of similar shapes are measured and collected due to the characteristic of each power unit operating in the same manner.

[0026] The above detection step (S20) is a step for detecting waveform imbalance (Unbalance Score) by superimposing current waveforms measured and collected from each power unit of the real-time device in the above information collection step (S10).

[0027]

[0028] *Here, the waveform imbalance indicates the degree of similarity of the current waveforms that are overlapped with each other, and the degree of similarity is indicated by a number from 0 to 100 depending on the similarity of the current waveforms. The lower the number, the higher the similarity of the current waveforms, and the higher the number, the lower the similarity of the current waveforms.

[0029] Therefore, if the value of the waveform imbalance is “0”, the current waveforms are completely identical to each other, and if the value of the waveform imbalance is “100”, the current waveforms are completely different from each other.

[0030] Here, the numerical range representing the waveform imbalance is set to 0 to 100, with a lower number indicating high similarity and a higher number indicating low similarity, but it is of course possible to set the numerical range representing the waveform imbalance or the meaning of similarity of a low number or a high number in various ways.

[0031] That is, the above detection step (S20) can detect real-time waveform imbalance by superimposing current waveforms measured and collected from each power unit of the real-time gantry crane. As shown in Fig. 3, if the current waveforms measured and collected from each power unit are similar to each other, the numerical value of the waveform imbalance is detected to be very low.

[0032] Of course, in theory, since each power unit of the gantry crane operates identically, the same current waveform should be measured and collected, and the value of the waveform imbalance should be detected as "0". However, due to various variables such as the period of use, operating status, and operating conditions of each power unit, the value may be detected as various values.

[0033] If the current waveforms measured and collected from each power unit are dissimilar to each other as shown in Fig. 4, the value of the waveform imbalance is detected to be very high.

[0034] The above judgment step (S30) is a step for setting a threshold value for the waveform imbalance, and if the waveform imbalance detected in the detection step (S20) exceeds the threshold value, the device is judged to be in an abnormal state and an alarm is issued.

[0035] That is, as illustrated in Fig. 5, the judgment step (S30) will determine that each power unit of the gantry crane is normal if the current waveforms measured and collected from each power unit of the gantry crane in real time in the detection step (S20) are similar to each other and the waveform imbalance is formed below the threshold value.

[0036] Here, the threshold value is arbitrarily set to a value of 30 to determine the status of the device, but it is obvious that this threshold value can be set to various values ​​considering the type of device, working environment, usage conditions, etc.

[0037] If, in the above detection step (S20), the current waveforms measured and collected from each power unit of the real-time gantry crane are dissimilar to each other and the waveform imbalance value exceeds the threshold value, the power unit of the gantry crane is judged to be abnormal and an alarm is sent to the surroundings to induce the power unit of the gantry crane to be inspected and managed stably.

[0038] Here, various abnormal signs can be suspected and detected as alarms through the above judgment step (S30).

[0039] First, when various mechanical problems occur in the power unit, abnormal current waveforms are measured and collected from the power unit with the problem, and the waveform imbalance is formed with a high degree of imbalance, so abnormal signs in the power unit can be quickly detected.

[0040] Second, if deformation or damage occurs in the rail that guides the wheels of the gantry crane, an abnormal load is generated on the wheels that are transported along the rail, and an abnormal current waveform is measured and collected from the power unit that provides power to the wheels, so that abnormal signs in the rail can be quickly detected through inspection.

[0041] Third, as shown in Fig. 6, even if the power unit is in a normal state but operates slightly faster or slower than other power units due to a control system (program) error, the waveform imbalance will be high, so that the occurrence of an error in the control system can be quickly detected.

[0042] Therefore, the predictive maintenance method (100) of the device through the current waveform imbalance of the multi-power unit of the present invention can easily detect various abnormal signs that may occur in the device, the components related to the operation of the device (for example, a rail guiding the movement of a gantry crane), and the control system that controls the device, thereby inducing very stable operation management of the device.

[0043] Meanwhile, in the information collection step (S10), the current waveform of each power unit measured and collected is forcibly divided according to a set time interval, and the divided section is set as a unit division section to form a plurality of unit division sections on the current waveform, and a forced division step (S40) is further included.

[0044] The above detection step (S20) detects the waveform imbalance by superimposing the current waveforms of each power unit, and independently detects the waveform imbalance for the current waveforms of the multiple unit sections divided in the forced division step (S40).

[0045] The above judgment step (S30) determines that the device is in an abnormal state and issues an alarm if the waveform imbalance of the current waveform of each unit section detected in the above detection step (S20) exceeds the threshold value.

[0046] Here, when the power unit of the gantry crane stops after operating, the waveform imbalance is detected based on the current waveform measured and collected from the power unit that performed the operation. However, if the power unit operates without a pause, the current value consumed from the power unit is continuously measured, and the current waveform is formed for a long time, so it is difficult to detect the waveform imbalance through the current waveform during the operation of each power unit.

[0047] That is, as illustrated in FIG. 7, the partition step (S40) constructs a plurality of unit partition sections by forcibly partitioning the current waveform continuously formed from each power unit at set time intervals, and the detection step (S20) independently detects the waveform imbalance of the current waveform for each of the plurality of unit partition sections constructed as described above, and the judgment step (S30) determines the gantry crane to be in an abnormal state and issues an alarm if any waveform imbalance among the waveform imbalances of the current waveforms of each unit partition section detected in the detection step (S20) exceeds a threshold value, thereby effectively detecting abnormal signs of equipment that operates without stopping.

[0048] In summary, the current waveform continuously measured and collected from the power unit operating without rest through the above-mentioned partition step (S40) is forcibly partitioned at set time intervals to build a plurality of unit partition sections, and the waveform imbalance of the current waveforms of the built unit partition sections is detected and compared, thereby enabling the detection of abnormal signs of the device in real time even during the process in which the power unit operates continuously.

[0049] Furthermore, by constructing a plurality of unit segments for the current waveforms continuously measured and collected from the power unit through the segmentation step (S40) as described above and detecting abnormal signs of the device based on the current waveforms of the constructed unit segments, the following effects can be expected.

[0050] If the power unit operates for a long time without rest, the current waveform measured and collected by the power unit will be formed very long, and when detecting the waveform imbalance for the entire current waveform formed long, even if the current waveforms are dissimilar to each other in a short period of time in some waveforms, if the entire current waveforms are similar to each other, the dissimilar portion is only a part of the whole, so there is a problem that the dissimilarity for the current waveforms formed dissimilarly in a short period of time is not properly reflected.

[0051] As described above, by dividing a current waveform that is formed over a long period of time into a number of unit segments through the segmentation step (S40), and detecting the waveform imbalance for the current waveform of each of the segmented unit segments, the dissimilarity of current waveforms that are formed dissimilarly to each other in a relatively short period of time can be accurately reflected as the waveform imbalance, thereby inducing more effective detection of abnormal signs of the device.

[0052] For example, when a gantry crane moves along a partially damaged rail, a current waveform different from that of other power units will be generated momentarily in the power unit that provides power to the wheels moving along the rail. The waveform imbalance for this momentary dissimilar current waveform can be easily reflected, allowing the manager to quickly and accurately recognize and respond to damage to the rail.

[0053] Meanwhile, in the above information collection step (S10), instead of the current value measured and collected from the power unit, one of the vibration, noise generated from the power unit, the frequency of the power supplied to the power unit, the temperature, humidity, and pressure of the power unit is selected to measure and collect a waveform such as a current waveform.

[0054] The above detection step (S20) detects waveform imbalance based on the waveform measured and collected from the power unit, and the above judgment step (S30) detects abnormal signs of the device based on the waveform imbalance and threshold value detected in the above detection step (S20), but it is of course possible to detect abnormal signs of the device as described above.

[0055] The predictive maintenance method (100) of the present invention for a device using a current waveform imbalance of multiple power units, which is performed through the above process, collects current waveforms based on the current values ​​consumed in each power unit of the device, and detects waveform imbalance by superimposing the collected current waveforms on each other, thereby detecting mechanical abnormalities of each power unit, and at the same time, detecting various abnormalities such as defects in components related to the power unit of the device or errors in the control system that controls the power unit, thereby having the effect of performing stable predictive maintenance of a device including multiple power units that operate identically.

[0056] While the present invention has been described with reference to the embodiments illustrated in the accompanying drawings, these are merely illustrative and are not limited to the above-described embodiments. Those skilled in the art will readily appreciate that various modifications and equivalent embodiments are possible. Furthermore, it should be understood that modifications are possible by those skilled in the art without departing from the spirit and scope of the present invention. Therefore, the scope of the claims in the present invention is not limited to the detailed description, but rather by the claims set forth below and their technical spirit.

[0057] The present invention can be used in the predictive maintenance industry of devices.

Claims

1. In a predictive correction method for a device including at least two power units that operate identically, An information collection step (S10) that measures and collects a current waveform that represents the current value consumed by each power unit of the device over time in a real-time operating state; A detection step (S20) for detecting the waveform imbalance (Unbalance Score) by superimposing the current waveforms measured and collected from each power unit of the real-time device in the above information collection step (S10); and A method for predictive maintenance of a device through current waveform imbalance of a multi-power unit, characterized by including a judgment step (S30) of setting a threshold value for the waveform imbalance and determining that the device is in an abnormal state and giving an alarm when the waveform imbalance detected in the detection step (S20) exceeds the threshold value.

2. In paragraph 1, In the above information collection step (S10), the current waveform of each power unit measured and collected is forcibly divided according to a set time interval, and the divided section is set as a unit division section to form a plurality of unit division sections on the current waveform, and further includes a forced division step (S40); The above detection step (S20) detects the waveform imbalance by superimposing the current waveforms of each power unit, and independently detects the waveform imbalance for the current waveforms of the multiple unit sections divided in the forced division step (S40). A method for predictive maintenance of a device through current waveform imbalance of a multi-power unit, characterized in that the above judgment step (S30) determines the device to be in an abnormal state and issues an alarm if the waveform imbalance of the current waveform of each unit section detected in the above detection step (S20) exceeds a threshold value.

3. In paragraph 1, In the above information collection step (S10), instead of the current value measured and collected from the power unit, one of the vibration, noise generated from the power unit, the frequency of the power supplied to the power unit, the temperature, humidity, and pressure of the power unit is selected to measure and collect a waveform such as a current waveform. A method for predictive maintenance of a device through current waveform imbalance of multiple power units, characterized in that the detection step (S20) detects waveform imbalance based on a waveform measured and collected from a power unit, and the judgment step (S30) detects abnormal signs of the device based on the waveform imbalance detected in the detection step (S20) and a threshold value.

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