JP3318246B2 - Fan motor diagnosis method and diagnosis device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a method and apparatus for diagnosing a fan motor, and more particularly to a method and apparatus suitable for diagnosing a fan motor having a rotating portion with a small offset load.

[0002]

2. Description of the Related Art As a diagnostic device for bearings of a steam turbine, a generator, a water turbine, a rolling mill, and the like, it is proposed to use acoustic emission (hereinafter referred to as AE) as described in, for example, Japanese Patent Publication No. 5-70777. Have been. Also, as described in Japanese Patent Publication No. 5-69461, A is used to diagnose the sliding part of a rotary compressor where an eccentric load acts during rotation.
The use of E has been proposed. Also, JP-A-2-236
No. 447, Japanese Patent Application Laid-Open No. 8-261995,
In a rotary compressor, there is disclosed a counting means for detecting an AE signal generated from an object by envelope detection and detecting the number of AE signals generated.

[0003]

SUMMARY OF THE INVENTION In a bearing diagnostic device such as a steam turbine, a generator, a water turbine, and a rolling mill as disclosed in Japanese Patent Publication No. 5-70777, the bearing load of a device to be diagnosed is extremely large. In a rotary compressor as described in Japanese Patent Publication No. 5-69461, there is a special characteristic that a biased load is applied once or several times during one rotation. There is a problem that it cannot be used as it is for diagnosis of the rotating part of the motor. In particular, the progress of the deterioration of the bearing of the fan motor and the change of the AE signal may behave differently from the conventional heavy load equipment or the one where one or several biased loads are applied during one rotation. And the results of experiments by the inventors.

It is an object of the present invention to provide a method and an apparatus for diagnosing a fan motor having a light-load rotating portion, which can reliably determine a state before the rotation stops.

[0005]

An object of the present invention is to obtain a waveform average level, a waveform fluctuation width, and the number of sudden waves per unit time as diagnostic parameters by using an AE signal detected from a rotating portion of a fan motor. Achieved by comparing these parameters with preset values to determine the steady state where there is no problem with the continuous specifications, the cautionary state approaching an abnormal state, the abnormal state immediately before stopping rotation, etc. Is done.

[0006]

1 to 6 show an embodiment of the present invention.
This will be described below. FIG. 1 is a diagram illustrating a configuration of a fan motor diagnostic device according to the present embodiment. FIG. 2 is a diagram illustrating a change with time of an elastic wave signal of a rotating portion of the motor when a life acceleration test of the fan motor is performed. FIG. 4 is a diagram showing an AE signal detected by an envelope detection, FIG. 4 is a diagram showing a flow of a diagnosis performed in the diagnostic unit 56, FIG. 5 is a diagram showing a temporal change of an AE signal of a normal motor, and FIG. FIG. 7 is a diagram showing a change with time of an AE signal of a motor that has been locked.

[0007] The fan motor diagnostic device of the present embodiment is configured as follows. An elastic wave detection sensor 51 (hereinafter, referred to as an AE sensor 51) is attached near a bearing portion of the fan motor 50, and the elastic wave detection sensor 51 is connected to an amplifier 52 of the fan motor diagnostic device 70. The fan motor diagnostic device 70 includes an amplifying unit 52, a waveform processing unit 53 connected to the amplifying unit 52, and a waveform processing unit 53.
A / D converter 54 connected to the A / D converter 54, a parameter calculator 55 connected to the A / D converter 54, a parameter calculator 55
And a display unit 57 connected to the diagnostic unit 56. The display unit 57 is connected to a personal computer 59 while being connected to an output unit 58 which is an output unit.

[0008] The output signal of the AE sensor 51 is taken into the amplifier 52 of the fan motor diagnostic device 70. here,
The elastic wave signal of the rotating part of the motor is hereinafter also referred to as an AE signal. The waveform signal amplified by the amplification unit 52 is
At 3, the envelope detection processing is performed, and the output signal of the AE sensor 51 is converted into an envelope signal. Here, the step of converting the signal of the AE sensor 51 into an envelope signal can be omitted, and substantially the same result can be obtained by performing the subsequent processing using a signal obtained by amplifying the output signal of the AE sensor 51. Performing this envelope detection processing helps to reduce the memory capacity in the subsequent signal processing.

The envelope signal is converted into a digital signal by the A / D converter 54 and stored in the RAM for a predetermined period (not shown). The parameter calculating section 55 calculates the average level of the waveform of the signal detected by the AE sensor 51, the waveform fluctuation width, and the number of occurrences of the sudden wave by a method described later. The diagnosing unit 56 compares these parameters calculated by the parameter calculating unit 55 with preset values, and based on the result, determines whether the fan motor 50 to be diagnosed is in a steady state, a caution state, or an abnormal state. Is displayed on the display unit 57. The display result of the display unit 57 is output from the output unit 58 connected to the fan motor diagnostic device 70.
Is printed out.

A personal computer 59 (hereinafter, referred to as a personal computer 59) is connected to the fan motor diagnostic device 70 via a data bus, and each device to be diagnosed is analyzed by the trend management software 60 installed in the personal computer 59. A trend or the like of the diagnosis result is created.

FIG. 2 (a) showing the change with time of the elastic wave signal of the rotating part of the motor when the life acceleration test of the fan motor is performed, FIG. 2 (a) shows that the motor in a new state is rotating. The waveform at the time is shown. FIG. 2B shows a waveform when time has elapsed, and FIG. 2C shows a waveform when time has further elapsed. FIG. 2 (b), FIG.
Although there is a variation in the time until the waveform of each pattern shown in (c) appears, this tendency is the same even if the type and size of the fan motor are changed. This means that the progress of the deterioration of the rotating part in the fan motor is A
This shows that a certain degree of prediction can be obtained by looking at the pattern of the E signal.

According to the knowledge of the present inventors, first, the lubricating oil such as grease is deteriorated and metal-to-metal contact occurs between the shaft and the bearing, and the bearing is deteriorated.
An irregular burst wave as shown in (d) appears. Although the sliding surface is roughened by the contact between the metals, the unevenness of the surface disappears with the passage of time, and the occurrence of sudden waves is reduced as shown in FIG. However, since the gap between the sliding surfaces increases, the average waveform level of the AE signal gradually increases.
FIG. 2 (f) shows that a 10-fold accelerated test was performed for about one year (actual
Although the waveform is shown after a lapse of 0 years (corresponding to 0 years), it is only a matter of time until the rotation stops (locks) in such a state.

From the results of the acceleration test, a more accurate diagnosis can be performed by taking into account the waveform fluctuation width and the number of occurrences of the sudden wave as parameters for the diagnosis of the fan motor in addition to the average level of the waveform of the AE signal. I understood that.

Based on the results of such an acceleration test, a method of diagnosing a fan motor will now be described in detail. First, the parameters calculated by the parameter calculation unit 55 will be described using an example. An average value of the envelope-detected AE signal shown in FIG. 3 for a predetermined time (for example, 0.4 seconds) is obtained, and this average value is continuously obtained for a predetermined number of times (for example, six times).
The average is taken as the waveform average level. Since this waveform average level is almost equal to the time average value of the AE signal continuously acquired for 2.4 seconds, which is the same time as the acquisition time of 0.4 seconds × 6 times, the time average value of 2.4 seconds is obtained. May be substituted. In the example shown in FIG. 3, the waveform average level is
0.317V is calculated.

The waveform fluctuation width is calculated as a difference between the maximum value and the minimum value of each average value taken in a predetermined number of times (for example, six times). In the example shown in FIG. 3, the voltage is 0.4V. This waveform fluctuation width can also be calculated as the difference between the maximum value and the minimum value of the AE signal within a certain time (for example, 2.4 seconds). However, in this case, the tendency is the same as the difference between the above-mentioned average values, but the absolute value is different. Therefore, it is necessary to change a reference value to be described later.

The number of occurrences of sudden waves is determined by counting the number of sudden waves exceeding the slice level per unit time, using a value obtained by multiplying the lowest value of the envelope detection signal by a coefficient as a slice level. Regarding the counting of the number of occurrences of sudden waves, Japanese Patent Laid-Open Publication No. 2-336447 discloses a means for counting the number of AE signals, and the means for counting the number of occurrences of sudden waves in the present embodiment is performed in the same manner as this method. ing.

In the diagnosis section 56, diagnosis is performed according to the diagnosis flow shown in FIG. When the diagnosis starts, A
In step 20, it is determined whether or not the waveform average level of E is equal to or more than the first set value aV. The first set value aV is, for example, 0.5 V, and if the average level is higher than this, it is determined that there is an abnormal state without observing a fluctuation width or a sudden wave.
If the average level is equal to or lower than aV, it is determined in step 22 whether the waveform fluctuation width is equal to or higher than the set value bV. The set value of the fluctuation width is set to, for example, 0.17V. If the fluctuation width is bV or more, even if the average level is aV or less,
The deterioration of the motor is progressing, and it is determined that the motor is in an abnormal state. The abnormal state is a state where rotation stop may occur at any time, and indicates that it is time to replace the fan motor. If the fluctuation width is equal to or smaller than bV, in step 24, the AE waveform average level is set to the second set value cV.
Compare with If the average level is equal to or more than cV, it is determined in step 26 whether or not the number of occurrences of the sudden wave is equal to or more than the first set number e. If the number of occurrences of the sudden wave is equal to or more than e, it is determined that the state is abnormal, and if it is less than e, it is determined that the state requires attention. The caution state is a state in which the rotation is not immediately stopped, but if the operation is continued as it is, the lock will be reached in the near future. In this embodiment, the set number e is set to, for example, 50 pieces per one data fetching time (2.4 seconds).

When the average level of the AE waveform is equal to or less than cV, it is determined that the AE waveform is in a steady state. This steady state is a state in which the rotating part is slightly deteriorated compared to the new state, but even if it is used as it is for the time being (until the next inspection time)
This is a state where no problem occurs. In the flow shown in FIG. 4, the steady state is divided into two states in step 28 according to the number of occurrences of sudden waves. That is, when the number of occurrences is greater than d smaller than the first set value, the state is the caution state, and when the number is less than d, the state is normal. In the present embodiment, for d, the first set value of the number of occurrences is set to, for example, 25.

In this embodiment, the state of the fan motor is classified into four states. However, it is often unnecessary to distinguish the normal state from the cautionary state when using the motor. In other words, it is essential that the user can be informed of the motor replacement time before locking occurs by distinguishing between an arbitrary number of states such as steady state, caution, and abnormality.

FIG. 5 and FIG. 6 show data obtained by measuring the average level of the waveform, the number of occurrences of the sudden wave, and the width of fluctuation of the waveform every month in the life promotion test for one and a half years (corresponding to five years of actual operation). FIG. 5 shows an example of a motor having no abnormality after one and a half years. In this motor, the waveform average level was cV or less, the number of sudden waves generated was extremely small, and the fluctuation width was bV or less.

FIG. 6 shows an example of a measurement result of a motor that has caused locking immediately before the end of the life test. In this motor, the average level of the waveform, the number of occurrences of the sudden wave, and the fluctuation width are all small until 8 months from the start of the test, but thereafter, the increase and decrease are repeated and the overall tendency is to increase, and finally the motor is locked.

When the state of the motor at each point in time is determined by the determination algorithm shown in FIG. 4 based on the measured values, as shown in FIG. That is, before the abnormal state, it is confirmed that there is a state in which the average level is relatively low and the number of sudden waves increases, and the cautionary state before reaching the abnormal state is determined by the method shown in FIG. It was confirmed that it was possible.

[0023]

As is apparent from the above description, according to the present invention, the state of deterioration of a lightly loaded fan motor can be discriminated into an arbitrary number of states such as a steady state, a cautionary state, and an abnormal state. The user can be properly notified of the time to replace the motor.

[Brief description of the drawings]

FIG. 1 is a diagram showing a configuration of a fan motor diagnostic device according to an embodiment of the present invention.

FIG. 2 is a diagram showing a temporal change of an elastic wave signal of a rotating portion of a motor when a life acceleration test of a fan motor is performed.

FIG. 3 is a diagram showing an AE signal subjected to envelope detection.

FIG. 4 is a diagram showing a diagnosis flow.

FIG. 5 is a diagram showing a change over time of an AE signal of a normal motor.

FIG. 6 is a diagram showing a change over time of an AE signal of a motor that has been locked.

[Explanation of symbols]

51: elastic wave detection sensor, 53: waveform processing unit, 54: A
/ D converter, 55: parameter calculation unit, 56: diagnosis unit,
57: display unit, 58: output unit, 59: personal computer, 70 ...
Fan motor diagnostic device.

──────────────────────────────────────────────────続 き Continued on the front page (72) Yoshiyuki Sato, Inventor 3-2-2, Sachimachi, Hitachi-shi, Ibaraki Pref. Hitachi Engineering Services Co., Ltd. (72) Inventor Tohru Sugihara 3-2-2, Sachimachi, Hitachi-shi, Ibaraki (2) Inventor Kenji Nishihara 5-31 Chuo-cho, Takamatsu-shi, Kagawa Prefecture Shikoku Branch Office, Hitachi, Ltd. (72) Kenya Matsumoto 2-5 Marunouchi, Takamatsu-shi, Kagawa Prefecture Shikoku Electric Power Company Inside the company (72) Inventor Hiroshi Ochi 2-5 Marunouchi, Takamatsu City, Kagawa Prefecture Inside Shikoku Electric Power Co., Ltd. (72) Inventor Haruo Ieda 12-56, Wakaba-cho, Tadotsu-cho, Nakatado-gun, Kagawa Prefecture Inside Shikoku Keisoku Kogyo Co., Ltd. (72 Inventor Norio Miyoshi 12-56, Wakaba-cho, Tadotsu-cho, Nakatado-gun, Kagawa Prefecture Inside Shikoku Keisoku Kogyo Co., Ltd. (72) Invention Utsunomiya Terumo 12-56, Wakaba-cho, Tadotsu-cho, Nakatado-gun, Kagawa Prefecture Inside Shikoku Keisoku Kogyo Co., Ltd. (56) References JP-A-9-189644 (JP, A) JP-A 8-261995 (JP, A) 2-205728 (JP, A) JP-A-64-91033 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB name) G01N 29/00-29/28 G01M 13/04 JICST file ( JOIS)

Claims (7)

(57) [Claims] 1. An elastic wave generated from a fan motor is detected, a signal of the detected elastic wave is detected by envelope detection, and a waveform average level, a waveform fluctuation width, and a burst per unit time are calculated from the envelope detected signal. A method for diagnosing a fan motor, comprising: determining the number of generated waves; and determining whether to replace the fan motor based on the determined average waveform level, waveform fluctuation width, and the number of generated sudden waves per unit time. 2. An elastic wave generated from a fan motor is detected, a signal of the detected elastic wave is detected by envelope detection, and a waveform average level, a waveform fluctuation width, and a burst per unit time are calculated from the detected envelope signal. The number of generated waves is determined, and the calculated average level of the waveform, the waveform variation width, the number of sudden waves generated per unit time and a preset value are compared, and the state of the fan motor is set to a steady state, a caution state, A method for diagnosing a fan motor, comprising determining one of a cautionary state and an abnormal state. 3. The method according to claim 2, wherein the waveform average level is equal to or higher than a first set value.
When the waveform average level is equal to or less than the first set value and the waveform variation width is equal to or greater than a preset value, or when the waveform average level is equal to or less than the first set value and is greater than the second set value and the number of protruding waves is the first If the number is equal to or greater than the set number, it is determined that the fan motor is in an abnormal state, and if the waveform average level is equal to or less than the first set value, greater than the second set value, and the number of sudden waves generated is equal to or less than the first set number. Is determined as a cautionary state, and is determined as a steady state when the waveform average level is equal to or less than a second set value.
3. The method for diagnosing a fan motor according to 1. 4. When the steady state is determined, the caution state is determined when the number of occurrences of the sudden wave is equal to or smaller than a first set value and larger than a second set value. 4. The method for diagnosing a fan motor according to claim 3, wherein a normal state is determined. 5. The method according to claim 1, wherein instead of performing envelope detection on the detected elastic wave signal, a waveform average level, a waveform variation width, and the number of sudden waves generated per unit time are directly obtained from the elastic wave signal. 5. The method for diagnosing a fan motor according to any one of items 1 to 4. 6. A sensor for detecting an elastic wave generated from a fan motor, a waveform processing unit for converting a signal detected by the sensor into an envelope signal, a waveform average level and a waveform based on an output signal of the waveform processing unit. A parameter calculator for calculating the fluctuation value and the average number of sudden waves generated per unit time; comparing the value calculated by the parameter calculator with a preset value to set the fan motor in a steady state; A diagnostic unit for determining which of a cautionary state and an abnormal state is present;
An output unit for outputting a diagnosis result determined by the diagnosis unit. 7. The diagnostic unit according to claim 1, wherein the waveform average level is equal to or greater than a first reference value, the waveform average level is equal to or less than the first reference value, and a waveform variation width is equal to or greater than a preset value, or the waveform average level is equal to or less than a predetermined value. If the value is equal to or less than one reference value and is larger than the second set value and the number of generated protruding waves is equal to or more than the first set value, it is determined that the fan motor is in an abnormal state, and the waveform average level is equal to or less than the first set value. When the number of occurrences of the sudden wave is larger than the second set value and the number of occurrences of the sudden wave is equal to or less than the first set number, it is determined that the caution is required. 7. The fan motor diagnostic device according to 6.