WO2021157111A1 - Fluid system abnormality monitoring and diagnosis method for fluid rotary machine - Google Patents
Fluid system abnormality monitoring and diagnosis method for fluid rotary machine Download PDFInfo
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- the diagnostic current waveform obtained by measuring the current of one of the three phases of the three-phase induction motor 10 during operation is A / D converted and transmitted to the processing unit for predetermined sampling.
- the amplitude probability density function ft (x) at the time of diagnosis is obtained from a plurality of point data obtained over time and stored in a storage means (second step).
- the current measurement time (sampling time) is, for example, about 8 to 16 seconds.
- the amplitude probability density function (reference amplitude probability density function and amplitude probability density function at the time of diagnosis) finds the probability that a fluctuating signal exists at a specific amplitude level, and determines how much fluctuation occurs near which amplitude. It is to be analyzed.
- the peak of the spectrum at the power supply frequency is sharp in a predetermined region (N data) including the power supply frequency (see the upper graph of FIG. 2 (A)), so that the value of the sharpness ⁇ is
- N data a predetermined region including the power supply frequency
- the spectral peak of the power supply frequency decreases and its surroundings (power supply). No prominent peaks are seen in the spectrum group (predetermined region before and after the frequency), and the entire spectrum group has a raised shape (see the graph in the upper part of FIG. 2B), so that the value of sharpness ⁇ becomes small. ..
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Abstract
This fluid system abnormality monitoring and diagnosis method for a fluid rotary machine is used to detect fluid system abnormalities that occur in a fluid rotary machine 11 driven by an induction motor 10, and involves calculating the value of kurtosis β based on a spectral group in a prescribed range including the power supply frequency of the induction motor 10, which is calculated by a frequency analysis of a diagnostic-time current waveform obtained by measuring the current in the induction motor 10 during the diagnostic; if the value of the kurtosis β is less than a preset reference kurtosis or is decreasing with the passage of time, it is determined that there is a possibility that a fluid system abnormality has occurred.
Description
本発明は、流体回転機械を駆動する誘導電動機の電流信号（電流波形）を計測し、解析することにより、流体回転機械の流体系異常を診断する流体回転機械の流体系異常監視診断方法に関する。
The present invention relates to a method for monitoring and diagnosing a fluid system abnormality of a fluid rotating machine for diagnosing a fluid system abnormality of the fluid rotating machine by measuring and analyzing a current signal (current waveform) of an induction motor for driving the fluid rotating machine.
従来、電動機、又は電動機によって駆動されるポンプや減速機（歯車装置）等の各種回転機械における軸受の異常、歯車の噛合せ異常、軸心ずれ（ミスアライメント）、ベルトのたわみ若しくはほころび等の機械系異常の診断には、診断精度が高いという理由から、測定パラメータとして振動を利用した方法及び装置が用いられていた。しかし、回転機械の設置位置又は環境によっては、振動センサー等の設置が困難な場合や、人が容易に近付くことができず、振動測定が困難な場合がある。そこで、現場にセンサー等を設置する必要がなく、現場から離れた電気室等で必要なデータを取得して診断を行うものとして、例えば、特許文献１～４のような、電動機の電流信号を解析して各種回転機械の状態監視（異常検出）を行う電流診断の方法及び装置が提案されている。
Conventionally, machines such as bearing abnormalities, gear meshing abnormalities, misalignment, belt bending or fraying in various rotating machines such as electric motors or pumps and reduction gears (gear devices) driven by electric motors. For the diagnosis of system abnormalities, a method and an apparatus using vibration as a measurement parameter have been used because the diagnostic accuracy is high. However, depending on the installation position or environment of the rotating machine, it may be difficult to install a vibration sensor or the like, or it may be difficult for a person to easily approach and measure vibration. Therefore, it is not necessary to install a sensor or the like at the site, and the current signal of the motor as in Patent Documents 1 to 4 is used to acquire the necessary data and perform the diagnosis in an electric room or the like away from the site. A current diagnosis method and device for analyzing and monitoring the state of various rotating machines (abnormality detection) have been proposed.
特許文献１～３では、電動機と、電動機によって駆動される回転機械（負荷設備）が診断の対象であり、その回転機械には、ポンプ、ブロワ（送風機）、圧縮機等の流体回転機械が含まれるが、診断されるのは、前述のような機械系の異常のみであり、ポンプのキャビテーション、ブロワ若しくは圧縮機のサージング或いは旋回失速のような流体系異常を診断することは想定されていない。
一方、特許文献４には、特許文献１～３と同様の機械系の異常（回転系異常）に加え、ポンプ等の負荷装置（流体回転機械）の流体的異常を検出することが記載されている。ここでの流体的異常は、例えばポンプの流体内に空気が入り込むことによって流れが乱れるといったような、負荷装置の流体を通じて生じうる異常を指しているが、より具体的には、バルブやフランジからのエア巻き込みを想定したものであり、キャビテーションやサージング等の現象（流体系異常）の検出については言及していない。また、特許文献４では、測定した電流波形の周波数解析結果のスペクトルを正常時のスペクトルで除して倍率を算出し、その倍率を予め設定した判定基準と照合することにより、異常を判定しているが、診断には事前に正常時の電流波形のスペクトルを取得し、記憶しておく必要がある。またキャビテーションやサージング等の流体系異常が電流波形に及ぼす影響は複雑であり、上記のようなスペクトルの倍率だけでは流体系異常の発生（兆候）を見逃すおそれがある。
以上のことから、流体回転機械で発生するキャビテーションやサージング等の流体系異常の検出に有効な監視診断方法の確立が望まれていた。
本発明は、かかる事情に鑑みてなされたもので、流体回転機械を駆動する誘導電動機の電流信号を監視し、解析することにより、流体回転機械に発生するキャビテーションやサージング等の流体系異常の兆候を確実に検出し、流体回転機械の劣化傾向を管理して、適切なメンテナンスを行うことができる流体回転機械の流体系異常監視診断方法を提供することを目的とする。 InPatent Documents 1 to 3, an electric motor and a rotating machine (load equipment) driven by the electric motor are the objects of diagnosis, and the rotating machine includes a fluid rotating machine such as a pump, a blower (blower), and a compressor. However, only mechanical abnormalities such as those mentioned above are diagnosed, and fluid system abnormalities such as pump cavitation, blower or compressor surging or swirling stall are not expected to be diagnosed.
On the other hand, Patent Document 4 describes that in addition to the same mechanical system abnormality (rotational system abnormality) as inPatent Documents 1 to 3, a fluid abnormality of a load device (fluid rotating machine) such as a pump is detected. There is. The fluid anomaly here refers to anomalies that can occur through the fluid of the load device, such as turbulence due to air entering the fluid of the pump, but more specifically from valves and flanges. It is assumed that air is involved in the air, and does not mention the detection of phenomena such as cavitation and surging (fluid system abnormality). Further, in Patent Document 4, an abnormality is determined by dividing the spectrum of the frequency analysis result of the measured current waveform by the spectrum at the normal time to calculate the magnification, and collating the magnification with a preset determination standard. However, it is necessary to acquire and store the spectrum of the normal current waveform in advance for diagnosis. In addition, the effects of fluid system abnormalities such as cavitation and surging on the current waveform are complicated, and the occurrence (signs) of fluid system abnormalities may be overlooked only by the above-mentioned spectral magnification.
From the above, it has been desired to establish a monitoring and diagnostic method effective for detecting fluid system abnormalities such as cavitation and surging that occur in a fluid rotating machine.
The present invention has been made in view of such circumstances, and by monitoring and analyzing the current signal of the induction motor that drives the fluid rotating machine, signs of fluid system abnormalities such as cavitation and surging that occur in the fluid rotating machine. It is an object of the present invention to provide a fluid system abnormality monitoring and diagnosis method for a fluid rotating machine, which can reliably detect the above, manage the deterioration tendency of the fluid rotating machine, and perform appropriate maintenance.
一方、特許文献４には、特許文献１～３と同様の機械系の異常（回転系異常）に加え、ポンプ等の負荷装置（流体回転機械）の流体的異常を検出することが記載されている。ここでの流体的異常は、例えばポンプの流体内に空気が入り込むことによって流れが乱れるといったような、負荷装置の流体を通じて生じうる異常を指しているが、より具体的には、バルブやフランジからのエア巻き込みを想定したものであり、キャビテーションやサージング等の現象（流体系異常）の検出については言及していない。また、特許文献４では、測定した電流波形の周波数解析結果のスペクトルを正常時のスペクトルで除して倍率を算出し、その倍率を予め設定した判定基準と照合することにより、異常を判定しているが、診断には事前に正常時の電流波形のスペクトルを取得し、記憶しておく必要がある。またキャビテーションやサージング等の流体系異常が電流波形に及ぼす影響は複雑であり、上記のようなスペクトルの倍率だけでは流体系異常の発生（兆候）を見逃すおそれがある。
以上のことから、流体回転機械で発生するキャビテーションやサージング等の流体系異常の検出に有効な監視診断方法の確立が望まれていた。
本発明は、かかる事情に鑑みてなされたもので、流体回転機械を駆動する誘導電動機の電流信号を監視し、解析することにより、流体回転機械に発生するキャビテーションやサージング等の流体系異常の兆候を確実に検出し、流体回転機械の劣化傾向を管理して、適切なメンテナンスを行うことができる流体回転機械の流体系異常監視診断方法を提供することを目的とする。 In
On the other hand, Patent Document 4 describes that in addition to the same mechanical system abnormality (rotational system abnormality) as in
From the above, it has been desired to establish a monitoring and diagnostic method effective for detecting fluid system abnormalities such as cavitation and surging that occur in a fluid rotating machine.
The present invention has been made in view of such circumstances, and by monitoring and analyzing the current signal of the induction motor that drives the fluid rotating machine, signs of fluid system abnormalities such as cavitation and surging that occur in the fluid rotating machine. It is an object of the present invention to provide a fluid system abnormality monitoring and diagnosis method for a fluid rotating machine, which can reliably detect the above, manage the deterioration tendency of the fluid rotating machine, and perform appropriate maintenance.
前記目的に沿う本発明に係る流体回転機械の流体系異常監視診断方法は、誘導電動機で駆動される流体回転機械に発生する流体系異常を検出するために用いられる流体回転機械の流体系異常監視診断方法であって、
診断しようとする前記誘導電動機の定格電流値より求めた基準正弦波信号波形と、稼働時（診断時）に前記誘導電動機の電流を計測して得られる診断時電流波形を解析し、比較することにより、前記流体系異常を検出するものである。
ここで、誘導電動機は、三相誘導電動機でも単相誘導電動機でもよい。 The method for monitoring and diagnosing a fluid system abnormality of a fluid rotating machine according to the above object according to the above object is to monitor a fluid system abnormality of a fluid rotating machine used for detecting a fluid system abnormality generated in a fluid rotating machine driven by an induction motor. It ’s a diagnostic method,
Analyze and compare the reference sine wave signal waveform obtained from the rated current value of the induction motor to be diagnosed and the current waveform at the time of diagnosis obtained by measuring the current of the induction motor during operation (during diagnosis). The above-mentioned fluid system abnormality is detected.
Here, the induction motor may be a three-phase induction motor or a single-phase induction motor.
診断しようとする前記誘導電動機の定格電流値より求めた基準正弦波信号波形と、稼働時（診断時）に前記誘導電動機の電流を計測して得られる診断時電流波形を解析し、比較することにより、前記流体系異常を検出するものである。
ここで、誘導電動機は、三相誘導電動機でも単相誘導電動機でもよい。 The method for monitoring and diagnosing a fluid system abnormality of a fluid rotating machine according to the above object according to the above object is to monitor a fluid system abnormality of a fluid rotating machine used for detecting a fluid system abnormality generated in a fluid rotating machine driven by an induction motor. It ’s a diagnostic method,
Analyze and compare the reference sine wave signal waveform obtained from the rated current value of the induction motor to be diagnosed and the current waveform at the time of diagnosis obtained by measuring the current of the induction motor during operation (during diagnosis). The above-mentioned fluid system abnormality is detected.
Here, the induction motor may be a three-phase induction motor or a single-phase induction motor.
本発明に係る流体回転機械の流体系異常監視診断方法において、診断時に前記誘導電動機の電流を計測して得られる診断時電流波形を周波数解析して求めた前記誘導電動機の電源周波数を含む所定範囲のスペクトル群による尖り度βの値を以下の式（１）と式（２）により算出して、該尖り度βの値が、予め設定した基準尖り度より小さいか、時間経過と共に減少傾向にあるときに、前記流体系異常が発生している可能性があると判定することができる。
In the fluid system abnormality monitoring and diagnosis method of the fluid rotating machine according to the present invention, a predetermined range including the power supply frequency of the induction motor obtained by frequency analysis of the current waveform at the time of diagnosis obtained by measuring the current of the induction motor at the time of diagnosis. The value of the sharpness β according to the spectrum group of is calculated by the following equations (1) and (2), and the value of the sharpness β is smaller than the preset reference sharpness or tends to decrease with the passage of time. At some point, it can be determined that the fluid system abnormality may have occurred.
ここで、ｘｉは電源周波数を含む所定範囲に分布するＮ個のデータの中のｉ番目のデータ、ｘavgは前記Ｎ個のデータの平均値、ｘrmsは前記Ｎ個のデータの不偏標準偏差である。
Here, x i is the i-th data among the N data distributed in a predetermined range including the power supply frequency, x avg is the average value of the N data, and x rms is the unbiased standard of the N data. It is a deviation.
本発明に係る流体回転機械の流体系異常監視診断方法において、前記流体系異常は、ポンプのキャビテーション又はブロワ若しくは圧縮機のサージング若しくは旋回失速のいずれかであることが好ましい。
In the fluid system abnormality monitoring and diagnosis method of the fluid rotating machine according to the present invention, the fluid system abnormality is preferably either cavitation of a pump or surging or stall of a blower or compressor.
本発明に係る流体回転機械の流体系異常監視診断方法において、前記基準正弦波信号波形から求めた参照振幅確率密度関数ｆｒ（ｘ）と、前記診断時電流波形から求めた診断時振幅確率密度関数ｆｔ（ｘ）から、以下の式（３）により算出されるＫＩ（Ｋｕｌｌｂａｃｋ－Ｌｅｉｂｌｅｒ Ｉｎｆｏｒｍａｔｉｏｎ：カルバック・ライブラー情報量）の値が、予め設定した基準ＫＩ値より大きくなったとき、前記尖り度βを算出し、該尖り度βにより、前記流体系異常の発生の有無を判定することが好ましい。
In the fluid system abnormality monitoring and diagnosis method of the fluid rotating machine according to the present invention, the reference amplitude probability density function fr (x) obtained from the reference sinusoidal signal waveform and the amplitude probability density function at diagnosis obtained from the current waveform at diagnosis. When the value of KI (Kullback-Leibler Information) calculated from ft (x) by the following formula (3) becomes larger than the preset reference KI value, the sharpness β Is calculated, and it is preferable to determine the presence or absence of the occurrence of the fluid system abnormality based on the sharpness β.
本発明に係る流体回転機械の流体系異常監視診断方法において、前記誘導電動機が三相誘導電動機であるとき、前記電流の計測は、三相全てについて行うことが好ましいが、三相のうちのいずれか一相について行ってもよい。
ここで、三相全ての電流の計測を行うことにより、三相のバランスも見ることができ、異常検出の精度を高めることができる。
また、１台の三相誘導電動機に対して、三相全ての電流の計測を行う代わりに、一相のみの電流を計測するようにすれば、３台の三相誘導電動機に対して電流の計測を行うことができ、３台の三相誘導電動機でそれぞれ駆動される流体回転機械の流体系異常を同時に監視し、検出することができる。 In the fluid system abnormality monitoring and diagnosis method for a fluid rotating machine according to the present invention, when the induction motor is a three-phase induction motor, the current is preferably measured for all three phases, but any of the three phases. You may follow one phase.
Here, by measuring the currents of all three phases, the balance of the three phases can be seen, and the accuracy of abnormality detection can be improved.
Further, if the current of only one phase is measured instead of measuring the current of all three phases for one three-phase induction motor, the current of the three-phase induction motor is measured. The measurement can be performed, and the fluid system abnormality of the fluid rotating machine driven by each of the three three-phase induction motors can be simultaneously monitored and detected.
ここで、三相全ての電流の計測を行うことにより、三相のバランスも見ることができ、異常検出の精度を高めることができる。
また、１台の三相誘導電動機に対して、三相全ての電流の計測を行う代わりに、一相のみの電流を計測するようにすれば、３台の三相誘導電動機に対して電流の計測を行うことができ、３台の三相誘導電動機でそれぞれ駆動される流体回転機械の流体系異常を同時に監視し、検出することができる。 In the fluid system abnormality monitoring and diagnosis method for a fluid rotating machine according to the present invention, when the induction motor is a three-phase induction motor, the current is preferably measured for all three phases, but any of the three phases. You may follow one phase.
Here, by measuring the currents of all three phases, the balance of the three phases can be seen, and the accuracy of abnormality detection can be improved.
Further, if the current of only one phase is measured instead of measuring the current of all three phases for one three-phase induction motor, the current of the three-phase induction motor is measured. The measurement can be performed, and the fluid system abnormality of the fluid rotating machine driven by each of the three three-phase induction motors can be simultaneously monitored and detected.
本発明に係る流体回転機械の流体系異常監視診断方法は、診断しようとする誘導電動機の定格電流値より求めた基準正弦波信号波形と、診断時に誘導電動機の電流を計測して得られる診断時電流波形を比較することにより、流体系異常を検出することができるので、誘導電動機で流体回転機械を駆動している状態で、流体回転機械における流体系異常の発生状況を監視することができ、流体系異常が発生している可能性がある場合には、さらに詳細（精密）な検査等を行って流体回転機械を正常に保つことができ、流体回転機械の流体系異常検出の信頼性及び流体回転機械のメンテナンス性に優れる。
The fluid system abnormality monitoring and diagnosis method of the fluid rotating machine according to the present invention is a reference sinusoidal signal waveform obtained from the rated current value of the induction motor to be diagnosed, and a diagnosis obtained by measuring the current of the induction motor at the time of diagnosis. Since the fluid system abnormality can be detected by comparing the current waveforms, it is possible to monitor the occurrence status of the fluid system abnormality in the fluid rotating machine while the induction motor is driving the fluid rotating machine. If there is a possibility that a fluid system abnormality has occurred, a more detailed (precision) inspection can be performed to keep the fluid rotating machine normal, and the reliability of the fluid system abnormality detection of the fluid rotating machine and Excellent maintainability of fluid rotating machines.
続いて、添付した図面を参照しつつ、本発明を具体化した実施例につき説明し、本発明の理解に供する。
本発明の一実施例に係る流体回転機械の流体系異常監視診断方法は、図１に示すような三相誘導電動機（誘導電動機の一例）１０で駆動されるポンプ（流体回転機械の一例）１１のキャビテーション（流体系異常の一例）の発生を検出するものである。 Subsequently, an embodiment embodying the present invention will be described with reference to the attached drawings, and the present invention will be understood.
The method for monitoring and diagnosing a fluid system abnormality of a fluid rotating machine according to an embodiment of the present invention is a pump (an example of a fluid rotating machine) 11 driven by a three-phase induction motor (an example of an induction motor) 10 as shown in FIG. It detects the occurrence of cavitation (an example of fluid system abnormality).
本発明の一実施例に係る流体回転機械の流体系異常監視診断方法は、図１に示すような三相誘導電動機（誘導電動機の一例）１０で駆動されるポンプ（流体回転機械の一例）１１のキャビテーション（流体系異常の一例）の発生を検出するものである。 Subsequently, an embodiment embodying the present invention will be described with reference to the attached drawings, and the present invention will be understood.
The method for monitoring and diagnosing a fluid system abnormality of a fluid rotating machine according to an embodiment of the present invention is a pump (an example of a fluid rotating machine) 11 driven by a three-phase induction motor (an example of an induction motor) 10 as shown in FIG. It detects the occurrence of cavitation (an example of fluid system abnormality).
図１に示すように、三相誘導電動機１０は電源１４から給電されてポンプ１１を駆動する。このとき、ポンプ１１が正常状態（流体系異常が発生していない状態）であれば、ポンプ１１内の流体の流れは安定しており、三相誘導電動機１０に対する負荷も安定して定常状態となり、各固定子を流れる電流のピーク値と、回転子の回転周波数は一定（定数）となる。従って、このときの三相誘導電動機１０の三相のうちの一相の電流を計測して得られる電流の時系列データを高速フーリエ変換を行って電流スペクトルを求めると、図２（Ａ）のようになる。図２（Ａ）の上段に示すように、三相誘導電動機１０の電源周波数（ここでは、６０Ｈｚ）の前後（楕円で囲んだ範囲）では電源周波数のスペクトルピークはその周辺のスペクトルピークから明確に突出しており、図２（Ａ）の下段に示す電源周波数の高調波の領域でも高調波のスペクトルピークが明確に突出している。なお、この傾向は、他の二相の電流についても同様である。
As shown in FIG. 1, the three-phase induction motor 10 is supplied with power from the power supply 14 to drive the pump 11. At this time, if the pump 11 is in a normal state (a state in which no fluid system abnormality has occurred), the flow of the fluid in the pump 11 is stable, and the load on the three-phase induction motor 10 is also stable and in a steady state. , The peak value of the current flowing through each stator and the rotation frequency of the rotor are constant (constant). Therefore, when the time series data of the current obtained by measuring the current of one of the three phases of the three-phase induction motor 10 at this time is subjected to a fast Fourier transform to obtain the current spectrum, FIG. 2 (A) shows. Will be. As shown in the upper part of FIG. 2 (A), before and after the power frequency (here, 60 Hz) of the three-phase induction motor 10 (in the range surrounded by an ellipse), the spectral peak of the power frequency is clearly defined from the spectral peaks around it. It is prominent, and the spectral peak of the harmonic is clearly prominent even in the harmonic region of the power supply frequency shown in the lower part of FIG. 2 (A). This tendency is the same for the other two-phase currents.
これに対し、ポンプ１１にキャビテーションが発生している状態では、ポンプ１１内の流体の流れは不安定となり、三相誘導電動機１０に対する負荷が非定常状態となる。負荷が非定常状態となる（変動する）ことにより、三相誘導電動機１０の内部の磁界が乱れ、この磁界の乱れが各固定子の巻線に作用して微弱な逆起電力を励起する。その結果、各固定子に流れる電流の振幅変調及び回転子の周波数変調が発生し、各固定子を流れる電流のピーク値と、回転子の回転周波数は非定常（時変数）となる。従って、このときの三相誘導電動機１０の一相の電流を計測して得られる電流の時系列データを高速フーリエ変換を行って電流スペクトルを求めると、図２（Ｂ）のようになる。図２（Ｂ）の上段に示すように、三相誘導電動機１０の電源周波数（ここでは、６０Ｈｚ）の前後（楕円で囲んだ範囲）では電源周波数のスペクトルピークが減少し、その周辺のスペクトル群では突出したピークが見られずスペクトル群全体が盛り上がった形状となり、図２（Ｂ）の下段に示す電源周波数の高調波の領域でも同様の傾向が見られる。なお、この傾向は、他の二相の電流についても同様である。
On the other hand, in the state where cavitation is generated in the pump 11, the flow of the fluid in the pump 11 becomes unstable, and the load on the three-phase induction motor 10 becomes unsteady. When the load becomes unsteady (fluctuates), the magnetic field inside the three-phase induction motor 10 is disturbed, and the disturbance of this magnetic field acts on the windings of each stator to excite a weak counter electromotive force. As a result, amplitude modulation of the current flowing through each stator and frequency modulation of the rotor occur, and the peak value of the current flowing through each stator and the rotation frequency of the rotor become non-stationary (time variable). Therefore, when the time series data of the current obtained by measuring the one-phase current of the three-phase induction motor 10 at this time is subjected to the fast Fourier transform to obtain the current spectrum, it becomes as shown in FIG. 2 (B). As shown in the upper part of FIG. 2B, the spectrum peak of the power supply frequency decreases before and after the power supply frequency (60 Hz in this case) of the three-phase induction motor 10 (range surrounded by an ellipse), and the spectrum group around it. In this case, no prominent peak is seen and the entire spectrum group has a raised shape, and the same tendency can be seen in the harmonic region of the power supply frequency shown in the lower part of FIG. 2 (B). This tendency is the same for the other two-phase currents.
以上のことから、診断しようとする三相誘導電動機１０の定格電流値より求めた基準正弦波信号波形と、診断時に三相誘導電動機１０の電流を計測して得られる診断時電流波形を解析し、比較することにより、ポンプ１１の流体系異常を検出することができる。このとき、各固定子に流れる電流は、電源１４と三相誘導電動機１０（各固定子）を接続する３本の電力線１５に、例えばクランプ式の電流検出器１６をそれぞれ接続することにより、容易に計測することができる。なお、三相全てについて電流の計測を行えば、より精度の高い診断を行うことができるが、三相のうちのいずれか一相について電流の計測を行うだけでも診断は可能である。電流検出器１６で計測されたアナログの電流波形は、Ａ／Ｄ変換器（図示せず）でデジタルの電流データに変換され、処理ユニット（図示せず）で処理される。処理ユニットは、ＲＡＭ、ＣＰＵ、ＲＯＭ、Ｉ／Ｏ、及びこれらの要素を接続するバスを備えた従来公知の演算器（即ち、コンピュータ）で構成される。そして、処理ユニットでの処理は、ＣＰＵが所定のプログラムを実行することで実現される。なお、Ａ／Ｄ変換器から処理ユニットへの電流データの送信は、ＬＡＮやＵＳＢケーブル等を用いて行うことができ、処理ユニットの設置場所は適宜、選択することができる。また、処理ユニットによる診断結果を表示するモニタの設置場所及び数は適宜、選択することができ、ＬＡＮを利用して遠隔地から診断結果を確認することもできる。さらに、計測されたデータ及び処理ユニットで処理された診断結果は、クラウド環境を利用することにより複数の作業者や管理者が共有することができる。
From the above, the reference sine wave signal waveform obtained from the rated current value of the three-phase induction motor 10 to be diagnosed and the current waveform at the time of diagnosis obtained by measuring the current of the three-phase induction motor 10 at the time of diagnosis are analyzed. , The fluid system abnormality of the pump 11 can be detected by comparison. At this time, the current flowing through each stator can be easily obtained by connecting, for example, a clamp type current detector 16 to each of the three power lines 15 connecting the power supply 14 and the three-phase induction motor 10 (each stator). Can be measured. It should be noted that if the current is measured for all three phases, a more accurate diagnosis can be made, but the diagnosis can be made only by measuring the current for any one of the three phases. The analog current waveform measured by the current detector 16 is converted into digital current data by an A / D converter (not shown) and processed by a processing unit (not shown). The processing unit is composed of a conventionally known arithmetic unit (that is, a computer) including a RAM, a CPU, a ROM, an I / O, and a bus connecting these elements. Then, the processing in the processing unit is realized by the CPU executing a predetermined program. The current data can be transmitted from the A / D converter to the processing unit using a LAN, a USB cable, or the like, and the installation location of the processing unit can be appropriately selected. In addition, the installation location and number of monitors that display the diagnosis results by the processing unit can be appropriately selected, and the diagnosis results can be confirmed from a remote location using a LAN. Further, the measured data and the diagnosis result processed by the processing unit can be shared by a plurality of workers and managers by using the cloud environment.
本発明の流体回転機械の流体系異常監視診断方法は、流体系異常の診断を簡易的かつ定量的に行うために適用される。以下、本実施例に係る流体回転機械の流体系異常監視診断方法（以下、単に流体系異常監視診断方法ともいう）の詳細について説明する。なお、ここでは、三相誘導電動機１０の三相のうちの一相のみの電流（１つの固定子に流れる電流）に着目して診断を行う。
まず、三相誘導電動機１０の定格電流値より求めた基準正弦波信号波形から参照振幅確率密度関数ｆｒ（ｘ）を求めて、記憶手段（ＲＡＭ又はＲＯＭ）に保存する（第１のステップ）。基準正弦波信号波形は、電源周波数（ここでは、６０Ｈｚ）で振動する定格電流の歪みのない波形である。 The fluid system abnormality monitoring and diagnosis method of the fluid rotating machine of the present invention is applied to perform a simple and quantitative diagnosis of a fluid system abnormality. Hereinafter, the details of the fluid system abnormality monitoring and diagnosis method (hereinafter, also simply referred to as the fluid system abnormality monitoring and diagnosis method) of the fluid rotating machine according to this embodiment will be described. Here, the diagnosis is performed by paying attention to the current of only one of the three phases of the three-phase induction motor 10 (the current flowing through one stator).
First, the reference amplitude probability density function fr (x) is obtained from the reference sinusoidal signal waveform obtained from the rated current value of the three-phase induction motor 10, and is stored in the storage means (RAM or ROM) (first step). The reference sinusoidal signal waveform is a waveform without distortion of the rated current that oscillates at the power supply frequency (here, 60 Hz).
まず、三相誘導電動機１０の定格電流値より求めた基準正弦波信号波形から参照振幅確率密度関数ｆｒ（ｘ）を求めて、記憶手段（ＲＡＭ又はＲＯＭ）に保存する（第１のステップ）。基準正弦波信号波形は、電源周波数（ここでは、６０Ｈｚ）で振動する定格電流の歪みのない波形である。 The fluid system abnormality monitoring and diagnosis method of the fluid rotating machine of the present invention is applied to perform a simple and quantitative diagnosis of a fluid system abnormality. Hereinafter, the details of the fluid system abnormality monitoring and diagnosis method (hereinafter, also simply referred to as the fluid system abnormality monitoring and diagnosis method) of the fluid rotating machine according to this embodiment will be described. Here, the diagnosis is performed by paying attention to the current of only one of the three phases of the three-phase induction motor 10 (the current flowing through one stator).
First, the reference amplitude probability density function fr (x) is obtained from the reference sinusoidal signal waveform obtained from the rated current value of the three-
次に、稼働時（診断時）の三相誘導電動機１０の三相のうち一相の電流を計測して得られる診断時電流波形をＡ／Ｄ変換して処理ユニットに送信し、所定のサンプリング時間で得られる複数の点データから診断時振幅確率密度関数ｆｔ（ｘ）を求めて、記憶手段に保存する（第２のステップ）。
なお、第２のステップで電流の計測時間（サンプリング時間）は、例えば、８～１６秒程度である。
振幅確率密度関数（参照振幅確率密度関数及び診断時振幅確率密度関数）は、変動する信号が特定の振幅レベルに存在する確率を求めるもので、どの振幅付近でどの程度の変動を起こしているかを解析するものである。 Next, the diagnostic current waveform obtained by measuring the current of one of the three phases of the three-phase induction motor 10 during operation (during diagnosis) is A / D converted and transmitted to the processing unit for predetermined sampling. The amplitude probability density function ft (x) at the time of diagnosis is obtained from a plurality of point data obtained over time and stored in a storage means (second step).
In the second step, the current measurement time (sampling time) is, for example, about 8 to 16 seconds.
The amplitude probability density function (reference amplitude probability density function and amplitude probability density function at the time of diagnosis) finds the probability that a fluctuating signal exists at a specific amplitude level, and determines how much fluctuation occurs near which amplitude. It is to be analyzed.
なお、第２のステップで電流の計測時間（サンプリング時間）は、例えば、８～１６秒程度である。
振幅確率密度関数（参照振幅確率密度関数及び診断時振幅確率密度関数）は、変動する信号が特定の振幅レベルに存在する確率を求めるもので、どの振幅付近でどの程度の変動を起こしているかを解析するものである。 Next, the diagnostic current waveform obtained by measuring the current of one of the three phases of the three-
In the second step, the current measurement time (sampling time) is, for example, about 8 to 16 seconds.
The amplitude probability density function (reference amplitude probability density function and amplitude probability density function at the time of diagnosis) finds the probability that a fluctuating signal exists at a specific amplitude level, and determines how much fluctuation occurs near which amplitude. It is to be analyzed.
次に、参照振幅確率密度関数ｆｒ（ｘ）と診断時振幅確率密度関数ｆｔ（ｘ）から、前述の式（３）により、ＫＩを算出する（第３のステップ）。
Next, the KI is calculated from the reference amplitude probability density function fr (x) and the amplitude probability density function ft (x) at the time of diagnosis by the above equation (3) (third step).
そして、式（３）により算出されるＫＩの値が、予め設定した基準ＫＩ値より大きくなったときに、ポンプ１１の流体系異常が発生している可能性があると判定することができる（第４のステップ）。このとき、第１の基準ＫＩ値と第２の基準ＫＩ値を設定しておき、算出されたＫＩの値が第１の基準ＫＩ値（例えば０．５）に近付けば注意を促し、第２の基準ＫＩ値（例えば１）に近付けば危険であることを通知するようにしてもよい。この通知はモニタ上に表示してもよいし、管理者等にメールで送信してもよい。
Then, when the KI value calculated by the equation (3) becomes larger than the preset reference KI value, it can be determined that the fluid system abnormality of the pump 11 may have occurred (). Fourth step). At this time, the first reference KI value and the second reference KI value are set, and if the calculated KI value approaches the first reference KI value (for example, 0.5), attention is drawn and the second It may be notified that it is dangerous if it approaches the standard KI value (for example, 1) of. This notification may be displayed on the monitor or sent by e-mail to the administrator or the like.
また、所定の時間間隔で第２、第３のステップを繰り返し行うことにより、時間経過と共に変化するＫＩの値を知ることができるので、ＫＩの値が時間経過と共に増加傾向にあるときに、ポンプ１１の流体系異常が発生している可能性があると判定することもできる。この場合、ＫＩの値が基準ＫＩ値（第１又は第２の基準ＫＩ値）に達する前でもポンプ１１の劣化傾向を把握することができ、流体系異常による深刻なダメージを受ける前にメンテナンスが可能となる。
なお、時間経過と共に変化するＫＩの値をグラフ化してモニタに表示した場合、管理者は、ポンプの劣化傾向（流体系異常の兆候）を目視で容易に確認することができ、劣化傾向管理の簡便性及び信頼性に優れる。 Further, by repeating the second and third steps at predetermined time intervals, the KI value that changes with the passage of time can be known. Therefore, when the KI value tends to increase with the passage of time, the pump It can also be determined that the fluid system abnormality of 11 may have occurred. In this case, the deterioration tendency of thepump 11 can be grasped even before the KI value reaches the reference KI value (first or second reference KI value), and maintenance is performed before the pump 11 is seriously damaged by the fluid system abnormality. It will be possible.
When the KI value that changes with the passage of time is graphed and displayed on the monitor, the administrator can easily visually confirm the deterioration tendency (sign of fluid system abnormality) of the pump, and the deterioration tendency management. Excellent in convenience and reliability.
なお、時間経過と共に変化するＫＩの値をグラフ化してモニタに表示した場合、管理者は、ポンプの劣化傾向（流体系異常の兆候）を目視で容易に確認することができ、劣化傾向管理の簡便性及び信頼性に優れる。 Further, by repeating the second and third steps at predetermined time intervals, the KI value that changes with the passage of time can be known. Therefore, when the KI value tends to increase with the passage of time, the pump It can also be determined that the fluid system abnormality of 11 may have occurred. In this case, the deterioration tendency of the
When the KI value that changes with the passage of time is graphed and displayed on the monitor, the administrator can easily visually confirm the deterioration tendency (sign of fluid system abnormality) of the pump, and the deterioration tendency management. Excellent in convenience and reliability.
次に、診断時に三相誘導電動機１０の電流を計測して得られる診断時電流波形を周波数解析し、三相誘導電動機１０の電源周波数を求める。診断時電流波形の周波数解析は、従来公知の方法で行われ、サンプリングした診断時電流波形（電流の時系列データ）につき、必要に応じてフィルター処理を行い、高速フーリエ変換を行うことにより、電流スペクトルが得られる。電流スペクトルのピークから電源周波数（ここでは６０Ｈｚ）を求め（図２（Ｂ）上段のグラフを参照）、この電源周波数を含む所定範囲（例えば電源周波数を中心する所定の領域）におけるスペクトル群の尖り度βを前述の式（１）と式（２）により算出する。ここで、ｘｉは電源周波数を含む所定範囲に分布するＮ個のデータの中のｉ番目のデータ、ｘavgはＮ個のデータの平均値、ｘrmsはＮ個のデータの不偏標準偏差である（第５のステップ）。
Next, the current waveform at the time of diagnosis obtained by measuring the current of the three-phase induction motor 10 at the time of diagnosis is frequency-analyzed, and the power frequency of the three-phase induction motor 10 is obtained. The frequency analysis of the current waveform at the time of diagnosis is performed by a conventionally known method, and the sampled current waveform at the time of diagnosis (time series data of the current) is filtered as necessary and fast Fourier transform is performed to perform the current. The spectrum is obtained. The power supply frequency (60 Hz in this case) is obtained from the peak of the current spectrum (see the graph in the upper part of FIG. 2B), and the sharpness of the spectrum group in a predetermined range including this power supply frequency (for example, a predetermined region centered on the power supply frequency). The degree β is calculated by the above equations (1) and (2). Here, x i is the i-th data among the N data distributed in a predetermined range including the power supply frequency, x avg is the mean value of the N data, and x rms is the unbiased standard deviation of the N data. There is (fifth step).
正常時は、電源周波数を含む所定の領域（Ｎ個のデータ）の中で、電源周波数でのスペクトルのピークが鋭い（図２（Ａ）上段のグラフを参照）ため、尖り度βの値が大きくなるのに対し、ポンプ１１に流体系異常が発生し、ポンプ１１内の流体の流れが不安定（非定常）になっている場合は、電源周波数のスペクトルピークが減少し、その周辺（電源周波数の前後の所定領域）のスペクトル群では突出したピークが見られず、スペクトル群全体が盛り上がった形状となる（図２（Ｂ）上段のグラフを参照）ため、尖り度βの値が小さくなる。
よって、式（１）により算出される尖り度βの値が、予め設定した基準尖り度より小さいか、時間経過と共に減少傾向にあるときに、ポンプ１１の流体系異常が発生している可能性があると判定することができる（第６のステップ）。このとき、第１の基準尖り度と第２の基準尖り度を設定しておき、算出された尖り度βの値が第１の基準尖り度（例えば正常時の尖り度の８０％）に近付けば注意を促し、第２の基準尖り度（例えば正常時の尖り度の７０％）に近付けば危険であることを通知するようにしてもよい。この通知はモニタ上に表示してもよいし、管理者等にメールで送信してもよい。 In the normal state, the peak of the spectrum at the power supply frequency is sharp in a predetermined region (N data) including the power supply frequency (see the upper graph of FIG. 2 (A)), so that the value of the sharpness β is On the other hand, when a fluid system abnormality occurs in thepump 11 and the flow of the fluid in the pump 11 becomes unstable (non-stationary), the spectral peak of the power supply frequency decreases and its surroundings (power supply). No prominent peaks are seen in the spectrum group (predetermined region before and after the frequency), and the entire spectrum group has a raised shape (see the graph in the upper part of FIG. 2B), so that the value of sharpness β becomes small. ..
Therefore, there is a possibility that a fluid system abnormality of thepump 11 has occurred when the value of the sharpness β calculated by the equation (1) is smaller than the preset reference sharpness or tends to decrease with the passage of time. It can be determined that there is (sixth step). At this time, the first reference sharpness and the second reference sharpness are set, and the calculated sharpness β value approaches the first reference sharpness (for example, 80% of the normal sharpness). For example, you may call attention and notify that it is dangerous if you approach the second reference sharpness (for example, 70% of the normal sharpness). This notification may be displayed on the monitor or sent by e-mail to the administrator or the like.
よって、式（１）により算出される尖り度βの値が、予め設定した基準尖り度より小さいか、時間経過と共に減少傾向にあるときに、ポンプ１１の流体系異常が発生している可能性があると判定することができる（第６のステップ）。このとき、第１の基準尖り度と第２の基準尖り度を設定しておき、算出された尖り度βの値が第１の基準尖り度（例えば正常時の尖り度の８０％）に近付けば注意を促し、第２の基準尖り度（例えば正常時の尖り度の７０％）に近付けば危険であることを通知するようにしてもよい。この通知はモニタ上に表示してもよいし、管理者等にメールで送信してもよい。 In the normal state, the peak of the spectrum at the power supply frequency is sharp in a predetermined region (N data) including the power supply frequency (see the upper graph of FIG. 2 (A)), so that the value of the sharpness β is On the other hand, when a fluid system abnormality occurs in the
Therefore, there is a possibility that a fluid system abnormality of the
また、所定の時間間隔で第５のステップを繰り返し行うことにより、時間経過と共に変化する尖り度βの値を知ることができるので、尖り度βの値が時間経過と共に減少傾向にあるときに、ポンプ１１の流体系異常が発生している可能性があると判定することができる。この場合、尖り度βの値が基準尖り度（第１又は第２の基準尖り度）に達する前でもポンプ１１の劣化傾向を把握することができ、流体系異常による深刻なダメージを受ける前にメンテナンスが可能となる。
なお、時間経過と共に変化する尖り度βをグラフ化してモニタに表示した場合、管理者は、ポンプの劣化傾向（流体系異常の兆候）を目視で容易に確認することができ、劣化傾向管理の簡便性及び信頼性に優れる。 Further, by repeating the fifth step at a predetermined time interval, the value of the sharpness β that changes with the passage of time can be known. Therefore, when the value of the sharpness β tends to decrease with the passage of time, It can be determined that there is a possibility that a fluid system abnormality of thepump 11 has occurred. In this case, the deterioration tendency of the pump 11 can be grasped even before the value of the sharpness β reaches the reference sharpness (first or second reference sharpness), and before serious damage due to the fluid system abnormality is received. Maintenance is possible.
When the sharpness β that changes with the passage of time is graphed and displayed on the monitor, the administrator can easily visually check the deterioration tendency (sign of fluid system abnormality) of the pump, and the deterioration tendency management. Excellent in convenience and reliability.
なお、時間経過と共に変化する尖り度βをグラフ化してモニタに表示した場合、管理者は、ポンプの劣化傾向（流体系異常の兆候）を目視で容易に確認することができ、劣化傾向管理の簡便性及び信頼性に優れる。 Further, by repeating the fifth step at a predetermined time interval, the value of the sharpness β that changes with the passage of time can be known. Therefore, when the value of the sharpness β tends to decrease with the passage of time, It can be determined that there is a possibility that a fluid system abnormality of the
When the sharpness β that changes with the passage of time is graphed and displayed on the monitor, the administrator can easily visually check the deterioration tendency (sign of fluid system abnormality) of the pump, and the deterioration tendency management. Excellent in convenience and reliability.
特に、流体系異常を検出するためのパラメータとして、ＫＩと尖り度βを併用し、ＫＩの値が、予め設定した基準ＫＩ値より大きいか、時間経過と共に増加傾向にあり、尖り度βの値が、予め設定した基準尖り度より小さいか、時間経過と共に減少傾向にあるときに、流体系異常が発生している可能性があると判定することにより、高い精度での診断を実現できる。
また、この流体系異常監視診断方法は、診断の対象となるポンプ１１に近付く必要がなく、電気室や制御盤（電気盤）の近く、或いは現場から離れた（遠隔の）事務所等で監視、診断を行うことができ、作業性に優れる。 In particular, as a parameter for detecting a fluid system abnormality, KI and sharpness β are used in combination, and the KI value is larger than the preset reference KI value or tends to increase with the passage of time, and the sharpness β value. However, when it is smaller than the preset reference sharpness or tends to decrease with the passage of time, it is possible to realize a diagnosis with high accuracy by determining that a fluid system abnormality may have occurred.
In addition, this fluid system abnormality monitoring and diagnosis method does not require approaching thepump 11 to be diagnosed, and is monitored in an electric room, a control panel (electric panel), or a (remote) office away from the site. , Diagnosis can be performed, and workability is excellent.
また、この流体系異常監視診断方法は、診断の対象となるポンプ１１に近付く必要がなく、電気室や制御盤（電気盤）の近く、或いは現場から離れた（遠隔の）事務所等で監視、診断を行うことができ、作業性に優れる。 In particular, as a parameter for detecting a fluid system abnormality, KI and sharpness β are used in combination, and the KI value is larger than the preset reference KI value or tends to increase with the passage of time, and the sharpness β value. However, when it is smaller than the preset reference sharpness or tends to decrease with the passage of time, it is possible to realize a diagnosis with high accuracy by determining that a fluid system abnormality may have occurred.
In addition, this fluid system abnormality monitoring and diagnosis method does not require approaching the
以上、本発明を、実施例を参照して説明してきたが、本発明は何ら上記した実施例に記載した構成に限定されるものではなく、特許請求の範囲に記載されている事項の範囲内で考えられるその他の実施例や変形例も含むものである。
例えば、上記実施例では、流体回転機械としてポンプを対象とし、流体系異常としてキャビテーションを対象としたが、流体回転機械としては、ブロワ（送風機）、圧縮機等も対象とすることができ、流体系異常としては、サージングや旋回失速等も対象とすることができる。
また、上記実施例では、三相誘導電動機の三相のうちのいずれか一相のみの電流を計測して診断を行う場合について説明したが、三相全ての電流を計測し、それぞれについて同様の解析を行い、診断を行うこともできる。その場合、三相のバランスも含めて総合的な判断を行うことができ、診断の精度を高めることができる。よって、診断対象装置の重要度又は稼働年数等に応じて、計測の対象とする相数を選択してもよい。また、三相誘導電動機ではなく単相誘導電動機で駆動される流体回転機械にも、この流体系異常監視診断方法は適用される。
なお、ＫＩの値による流体系異常の判定を行わず、尖り度βの値のみで流体系異常の判定を行うこともできる。 Although the present invention has been described above with reference to Examples, the present invention is not limited to the configuration described in the above-described Examples, but is within the scope of the claims. It also includes other examples and modifications that can be considered in.
For example, in the above embodiment, the pump is targeted as the fluid rotating machine, and the cavitation is targeted as the fluid system abnormality, but the blower (blower), the compressor, etc. can also be targeted as the fluid rotating machine. As systematic abnormalities, surging, turning stall, etc. can also be targeted.
Further, in the above embodiment, the case where the diagnosis is performed by measuring the current of only one of the three phases of the three-phase induction motor has been described, but the currents of all three phases are measured and the same applies to each of them. It is also possible to perform analysis and make a diagnosis. In that case, it is possible to make a comprehensive judgment including the balance of the three phases, and it is possible to improve the accuracy of the diagnosis. Therefore, the number of phases to be measured may be selected according to the importance of the device to be diagnosed, the number of years of operation, and the like. Further, this fluid system abnormality monitoring and diagnosis method is also applied to a fluid rotating machine driven by a single-phase induction motor instead of a three-phase induction motor.
It is also possible to determine the fluid system abnormality only by the value of the sharpness β without determining the fluid system abnormality based on the KI value.
例えば、上記実施例では、流体回転機械としてポンプを対象とし、流体系異常としてキャビテーションを対象としたが、流体回転機械としては、ブロワ（送風機）、圧縮機等も対象とすることができ、流体系異常としては、サージングや旋回失速等も対象とすることができる。
また、上記実施例では、三相誘導電動機の三相のうちのいずれか一相のみの電流を計測して診断を行う場合について説明したが、三相全ての電流を計測し、それぞれについて同様の解析を行い、診断を行うこともできる。その場合、三相のバランスも含めて総合的な判断を行うことができ、診断の精度を高めることができる。よって、診断対象装置の重要度又は稼働年数等に応じて、計測の対象とする相数を選択してもよい。また、三相誘導電動機ではなく単相誘導電動機で駆動される流体回転機械にも、この流体系異常監視診断方法は適用される。
なお、ＫＩの値による流体系異常の判定を行わず、尖り度βの値のみで流体系異常の判定を行うこともできる。 Although the present invention has been described above with reference to Examples, the present invention is not limited to the configuration described in the above-described Examples, but is within the scope of the claims. It also includes other examples and modifications that can be considered in.
For example, in the above embodiment, the pump is targeted as the fluid rotating machine, and the cavitation is targeted as the fluid system abnormality, but the blower (blower), the compressor, etc. can also be targeted as the fluid rotating machine. As systematic abnormalities, surging, turning stall, etc. can also be targeted.
Further, in the above embodiment, the case where the diagnosis is performed by measuring the current of only one of the three phases of the three-phase induction motor has been described, but the currents of all three phases are measured and the same applies to each of them. It is also possible to perform analysis and make a diagnosis. In that case, it is possible to make a comprehensive judgment including the balance of the three phases, and it is possible to improve the accuracy of the diagnosis. Therefore, the number of phases to be measured may be selected according to the importance of the device to be diagnosed, the number of years of operation, and the like. Further, this fluid system abnormality monitoring and diagnosis method is also applied to a fluid rotating machine driven by a single-phase induction motor instead of a three-phase induction motor.
It is also possible to determine the fluid system abnormality only by the value of the sharpness β without determining the fluid system abnormality based on the KI value.
本発明に係る流体回転機械の流体系異常監視診断方法によれば、流体回転機械に発生する流体系異常、例えば、ポンプのキャビテーション又はブロワ若しくは圧縮機のサージング若しくは旋回失速等の兆候を、誘導電動機で流体回転機械を駆動している状態で、確実に検出して、流体回転機械の劣化傾向を管理し、適切なメンテナンスを行うことができる。また、診断の対象となる流体回転機械に近付く必要がなく、電気室や制御盤の近く、或いは現場から離れた（遠隔の）事務所等で監視、診断を行うことができ、作業性に優れる。
According to the fluid system abnormality monitoring and diagnosis method of the fluid rotating machine according to the present invention, a sign of a fluid system abnormality occurring in the fluid rotating machine, such as cavitation of a pump or surging or turning stall of a blower or a compressor, is detected by an induction electric machine. While the fluid rotating machine is being driven, it can be reliably detected, the deterioration tendency of the fluid rotating machine can be managed, and appropriate maintenance can be performed. In addition, it is not necessary to approach the fluid rotating machine to be diagnosed, and monitoring and diagnosis can be performed near the electric room or control panel, or in a (remote) office away from the site, which is excellent in workability. ..
１０：三相誘導電動機（誘導電動機）、１１：ポンプ（流体回転機械）、１４：電源、１５：電力線、１６：電流検出器
10: Three-phase induction motor (induction motor), 11: Pump (fluid rotating machine), 14: Power supply, 15: Power line, 16: Current detector
Claims (3)
- 誘導電動機で駆動される流体回転機械に発生する流体系異常を検出するために用いられる流体回転機械の流体系異常監視診断方法であって、
診断時に前記誘導電動機の電流を計測して得られる診断時電流波形を周波数解析して求めた前記誘導電動機の電源周波数を含む所定範囲のスペクトル群による尖り度βの値を以下の式（１）と式（２）により算出して、該尖り度βの値が、予め設定した基準尖り度より小さいか、時間経過と共に減少傾向にあるときに、前記流体系異常が発生している可能性があると判定することを特徴とする流体回転機械の流体系異常監視診断方法。
The value of the sharpness β according to the spectrum group in a predetermined range including the power supply frequency of the induction motor obtained by frequency analysis of the current waveform at the time of diagnosis obtained by measuring the current of the induction motor at the time of diagnosis is calculated by the following equation (1). When the value of the sharpness β is smaller than the preset reference sharpness or tends to decrease with the passage of time, it is possible that the fluid system abnormality has occurred. A method for monitoring and diagnosing a fluid system abnormality of a fluid rotating machine, which comprises determining that there is.
- 請求項１記載の流体回転機械の流体系異常監視診断方法において、前記流体系異常は、ポンプのキャビテーション又はブロワ若しくは圧縮機のサージング若しくは旋回失速のいずれかであることを特徴とする流体回転機械の流体系異常監視診断方法。 In the method for monitoring and diagnosing a fluid system abnormality of a fluid rotating machine according to claim 1, the fluid system abnormality is either cavitation of a pump, surging of a blower or a compressor, or stall of turning. Fluid system abnormality monitoring and diagnosis method.
- 請求項１又は２記載の流体回転機械の流体系異常監視診断方法において、前記誘導電動機の定格電流値より求めた基準正弦波信号波形から求めた参照振幅確率密度関数ｆｒ（ｘ）と、
前記誘導電動機の稼働時の電流を計測して得られる診断時電流波形から求めた診断時振幅確率密度関数ｆｔ（ｘ）から、以下の式（３）により算出されるＫＩの値が、予め設定した基準ＫＩ値より大きくなったとき、前記尖り度βを算出し、該尖り度βにより、前記流体系異常の発生の有無を判定することを特徴とする流体回転機械の流体系異常監視診断方法。
The value of KI calculated by the following equation (3) is preset from the diagnostic amplitude probability density function ft (x) obtained from the diagnostic current waveform obtained by measuring the operating current of the induction motor. A method for monitoring and diagnosing a fluid system abnormality of a fluid rotating machine, which comprises calculating the sharpness β when the value becomes larger than the determined reference KI value and determining the presence or absence of the occurrence of the fluid system abnormality based on the sharpness β. ..
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| JP2005241089A (en) * | 2004-02-25 | 2005-09-08 | Mitsubishi Electric Corp | Apparatus diagnosing device, refrigeration cycle device, apparatus diagnosing method, apparatus monitoring system and refrigeration cycle monitoring system |
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| JPH0719245A (en) * | 1993-07-05 | 1995-01-20 | Seiko Seiki Co Ltd | Magnetic bearing type rotary machine |
| JP2005241089A (en) * | 2004-02-25 | 2005-09-08 | Mitsubishi Electric Corp | Apparatus diagnosing device, refrigeration cycle device, apparatus diagnosing method, apparatus monitoring system and refrigeration cycle monitoring system |
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