Method for predictive maintenance of device using difference value between current waveforms of multiple power units

Abstract

Disclosed is a method for predictive maintenance of a device using a difference value between current waveforms of multiple power units, wherein, by collecting current waveforms on the basis of a current value consumed in each power unit of a device and detecting a difference value between the current waveforms through the overlapping of the collected current waveforms, it is possible to detect abnormal mechanical signs of each power unit, while detecting various abnormal signs such as defects in components related to the power units of the device or errors in a control system which controls the power units.

Description

Predictive maintenance method of equipment through difference values ​​between current waveforms of multiple power units

[0001] The present invention relates to a predictive maintenance method for a device using a difference value between current waveforms of multiple power units, and more specifically, to a predictive maintenance method for a device using a difference value between current waveforms of multiple power units, which collects current waveforms based on current values ​​consumed in each power unit of the device, superimposes the collected current waveforms on each other, and detects the difference value between the current waveforms, 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 a plurality of 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 the difference value between the current waveforms 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, superimposing the collected current waveforms on each other, and detecting the difference value between the current waveforms, 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 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 method for predictive maintenance of a device using a difference value between current waveforms of multiple power units according to the present invention comprises: an information collection step (S10) of measuring and collecting a current waveform representing a current value consumed by each power unit of the device over time in a real-time operating state; a detection step (S20) of repeatedly detecting a difference value between the current waveforms by overlapping the current waveforms measured and collected from each power unit of the device in the information collection step (S10) with each other and comparing the current value of the current waveform with the current value of another current waveform at the same time; and a judgment step (S30) of setting an alarm threshold value for the difference value and determining the device as being in an abnormal state and giving an alarm if the difference value detected in the detection step (S20) exceeds the alarm threshold value.

[0013] In addition, the above judgment step (S30) further sets a threshold maintenance time for the time during which the difference value between current waveforms exceeds the alarm threshold value.

[0014] The above detection step (S20) is characterized in that if the difference value between the detected current waveforms exceeds the alarm threshold value and is maintained for a threshold maintenance time or longer, the device is judged to be in a dangerous state and an alarm is generated.

[0015] In addition, 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;

[0016] The above detection step (S20) superimposes the current waveforms of each power unit on each other to detect the difference value between the current waveforms, and independently detects the difference value between the current waveforms of the current waveforms of the multiple unit sections divided in the forced division step (S40).

[0017] The above judgment step (S30) is characterized in that if the difference value between the current waveforms of each unit section detected in the above detection step (S20) exceeds the alarm threshold value, the device is judged to be in an abnormal state and an alarm is generated.

[0018] In addition, in the above information collection step (S10), instead of the current value measured and collected from the power unit, one of the vibrations, noises 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.

[0019] The above detection step (S20) is characterized by detecting a difference value between waveforms based on waveforms measured and collected from the power unit, and the above judgment step (S30) is characterized by detecting an abnormality sign of the device based on a difference value between waveforms detected in the detection step (S20) and an alarm threshold value.

[0020] As described above, according to the method for predictive maintenance of a device using the difference value between the current waveforms 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 difference value between the current waveforms 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 that controls 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.

[0021] FIG. 1 is a block diagram of a method for predictive maintenance of a device using a difference value between current waveforms of multiple power units according to an embodiment of the present invention.

[0022] FIGS. 2 to 9 are drawings for explaining a predictive maintenance method of a device through a difference value between the current waveforms of the multiple power units illustrated in FIG. 1.

[0023] A method for predictive maintenance of a device based on the difference value between the current waveforms 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.

[0024] FIGS. 1 to 9 illustrate a predictive maintenance method for a device using a difference value between current waveforms of multiple power units according to an embodiment of the present invention. FIG. 1 is a block diagram of a predictive maintenance method for a device using a difference value between current waveforms of multiple power units according to an embodiment of the present invention, and FIGS. 2 to 9 are drawings each illustrating a predictive maintenance method for a device using a difference value between current waveforms of multiple power units illustrated in FIG. 1.

[0025] As illustrated in FIG. 1, the predictive maintenance method (100) of a device using a difference value between current waveforms of multiple power units according to an embodiment of the present invention includes an information collection step (S10), a detection step (S20), and a judgment step (S30).

[0026] 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 of the device over time in a real-time operating state of the device including at least two or more power units that operate identically.

[0027] 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.

[0028] 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.

[0029] For convenience of explanation, the method (100) for predictive maintenance of a device using the difference value between the current waveforms of multiple power units of the present invention will be described 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. However, the technology of the present invention is not limited to such devices.

[0030] 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.

[0031] The above detection step (S20) is a step of repeatedly detecting the difference value between the current waveforms by overlapping the current waveforms measured and collected from each power unit of the real-time device in the above information collection step (S10) and comparing the current value of one current waveform with the current value of another current waveform at the same time.

[0032] That is, the above detection step (S20) can repeatedly detect the difference value between the real-time current waveforms by superimposing the 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 difference value between the current waveforms is detected to be very low.

[0033] 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 difference value between the current waveforms should be detected as "0". However, the difference value between the current waveforms may be detected due to various variables such as the period of use, operating status, and operating conditions of each power unit.

[0034] If the current waveforms measured and collected from each power unit are dissimilar to each other as shown in Fig. 4, the difference value between the current waveforms is detected to be very high.

[0035] Here, the difference values ​​between current waveforms in the real-time current waveform are regularly and repeatedly detected at regular unit time intervals, but it is of course possible to detect the difference values ​​between current waveforms at irregular time intervals, taking into account the type of device, working environment, usage conditions, etc.

[0036] The above judgment step (S30) is a step for setting an alarm threshold for the difference value, and if the difference value detected in the detection step (S20) exceeds the alarm threshold, the device is judged to be in an abnormal state and an alarm is generated.

[0037] 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 difference value between the current waveforms is formed to be less than the alarm threshold value.

[0038] Here, the alarm threshold value is set to a value of 5 to determine the status of the device, but it is obvious that this alarm threshold value can be set to various values ​​considering the type of device, working environment, usage conditions, etc.

[0039] If, as shown in Fig. 6, the current waveforms measured and collected from each power unit of the real-time gantry crane in the detection step (S20) are dissimilar to each other and the difference value between the current waveforms exceeds the alarm threshold, the power unit of the gantry crane is judged to be abnormal and an alarm is issued to the surroundings to induce stable inspection and management of the power unit of the gantry crane.

[0040] Here, various abnormal signs can be suspected and detected as alarms through the above judgment step (S30).

[0041] 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 difference between the current waveforms is large, so that abnormal signs in the power unit can be quickly detected.

[0042] 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.

[0043] Third, as shown in Fig. 7, 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 difference between the current waveforms will be large, so that the occurrence of an error in the control system can be quickly detected.

[0044] Therefore, the predictive maintenance method (100) of the device through the difference value between the current waveforms 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.

[0045] Meanwhile, the above judgment step (S30) further sets a threshold maintenance time for the time during which the difference value between current waveforms exceeds the alarm threshold value.

[0046] The above detection step (S20) determines that the device is in a dangerous state and issues an alarm if the difference value between the detected current waveforms exceeds the alarm threshold and is maintained for a longer than the threshold maintenance time.

[0047] That is, as shown in Fig. 8, if the difference value between the current waveforms measured and collected from each power unit of the real-time gantry crane exceeds the alarm threshold value, and at the same time, the difference value between the current waveforms exceeding the alarm threshold value is maintained for longer than the threshold maintenance time, the power unit of the gantry crane is judged to be in a dangerous state, which is an abnormal state of a somewhat high level, and an alarm is immediately issued.

[0048] In summary, if the difference between the current waveforms of the real-time gantry crane exceeds the alarm threshold, the device is judged to be in an abnormal state and an alarm is issued. At the same time, if the difference between the current waveforms exceeds the threshold holding time, the device is judged to be in a dangerous state and an alarm is issued. Therefore, it is possible to form various alarm levels and, of course, to warn of abnormal signs of the device in stages.

[0049] 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.

[0050] The above detection step (S20) superimposes the current waveforms of each power unit on each other to detect the difference value between the current waveforms, and independently detects the difference value between the current waveforms of the current waveforms of the multiple unit sections divided in the forced division step (S40).

[0051] The above judgment step (S30) determines that the device is in an abnormal state and issues an alarm if the difference value between the current waveforms of each unit section detected in the above detection step (S20) exceeds the alarm threshold value.

[0052] Here, when the power unit of the gantry crane stops after operating, the difference value between the current waveforms 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 difference value through the current waveform during the operation of each power unit.

[0053] That is, as illustrated in FIG. 9, 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 difference values ​​of the current waveforms 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 difference value among the difference values ​​between the current waveforms for the current waveforms of each unit partition section detected in the detection step (S20) exceeds the alarm threshold value, so that abnormal signs of a device that operates without stopping are effectively detected.

[0054] 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 difference values ​​between the current waveforms of the built unit partition sections are each 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.

[0055] 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.

[0056] The above detection step (S20) detects the difference value between waveforms based on the waveforms measured and collected from the power unit, and the above judgment step (S30) detects abnormal signs of the device based on the difference value between the waveforms detected in the above detection step (S20) and the alarm threshold value, but it goes without saying that it is possible to detect abnormal signs of the device as described above.

[0057] The method (100) for predictive maintenance of a device using the difference value between the current waveforms of multiple power units of the present invention, which is performed through the above process, collects current waveforms based on the current value consumed in each power unit of the device, and superimposes the collected current waveforms to detect the difference value between the current waveforms. This method detects mechanical abnormalities of each power unit, and at the same time, can detect 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.

[0058] 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.

[0059] 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 repeatedly detecting the difference between the current waveforms by overlapping the current waveforms measured and collected from each power unit of the real-time device in the above information collection step (S10) and comparing the current value of the current waveform with the current value of another current waveform at the same time; and A method for predictive maintenance of a device using a difference value between current waveforms of multiple power units, characterized in that it comprises a judgment step (S30) of setting an alarm threshold value for the above difference value and judging the device as being in an abnormal state and giving an alarm if the difference value detected in the detection step (S20) exceeds the alarm threshold value.

2. In paragraph 1, The above judgment step (S30) further sets a threshold maintenance time for the time during which the difference value between current waveforms exceeds the alarm threshold value. A method for predictive maintenance of a device using a difference value between current waveforms of a multi-power unit, characterized in that the detection step (S20) determines the device to be in a dangerous state and issues an alarm if the difference value between the detected current waveforms exceeds the alarm threshold value and is maintained for a threshold maintenance time or longer.

3. In paragraph 1 or 2, 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) superimposes the current waveforms of each power unit on each other to detect the difference value between the current waveforms, and independently detects the difference value between the current waveforms of the current waveforms of the multiple unit sections divided in the forced division step (S40). A method for predictive maintenance of a device using a difference value between current waveforms 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 difference value between current waveforms of each unit section detected in the above detection step (S20) exceeds an alarm threshold value.

4. 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 using a difference value between current waveforms of multiple power units, characterized in that the detection step (S20) detects a difference value between waveforms based on waveforms measured and collected from a power unit, and the judgment step (S30) detects an abnormality of the device based on the difference value between waveforms detected in the detection step (S20) and an alarm threshold value.

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