JPH09318577A - Fault diagnosis device for hydraulic equipment and method thereof - Google Patents

Abstract

(57) An object of the present invention is to provide an inexpensive and highly reliable fault diagnosis device for hydraulic equipment and its method. SOLUTION: An electrode pair to which a predetermined voltage is applied is arranged in hydraulic fluid, a short-circuit current flowing between the electrodes is converted into a pulse signal, and the hydraulic fluid is based on the peak voltage value and the number of counts of the pulse signal. The particle size and the concentration of the metal particles therein are calculated, and the failure diagnosis of the hydraulic equipment is performed based on the particle size and the concentration. The failure diagnosis of the hydraulic equipment is performed based on the metal particle concentration increase rate, the average particle size increase rate, the concentration for each particle diameter, the average particle diameter, and the like. When based on the concentration increase rate or average particle size increase rate, the calculated concentration increase rate or average is obtained only when the count number within the measurement unit time T0 is greater than or equal to a predetermined value and the variation in the measured data is less than or equal to the predetermined value. Fault diagnosis is performed based on the particle size increase rate. Further, the density is obtained by correcting it according to the temperature.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a failure diagnosing apparatus for hydraulic equipment and a method for diagnosing damage and failure of hydraulic equipment based on the particle size and concentration of metal particles mixed in hydraulic fluid of hydraulic equipment. Regarding the method.

[0002]

2. Description of the Related Art For example, in a construction machine, an industrial machine or a machine tool, when hydraulic equipment is driven for a long time, metal particles such as iron powder generated from sliding parts and rotating parts of the hydraulic equipment itself are generated. It comes to be mixed in the hydraulic fluid of the hydraulic circuit. Usually, the particle size of metal particles, which increases with long-time operation of a specific hydraulic device, tends to be characteristically biased to a predetermined particle size range. Further, it is well known that when a certain hydraulic device is damaged, the number of particles having a predetermined particle size increases rapidly due to the damage. Furthermore, if such metal particles continue to be driven in a state of being mixed in the hydraulic oil, these hydraulic devices are often damaged or malfunction. Therefore, conventionally, measuring the particle size and the number (concentration) of metal particles in hydraulic oil is a very important issue for diagnosing damages and failures of hydraulic equipment and preventing serious failures. Has become. For this reason, many methods for measuring the particle size of metal particles and the number (concentration) of the particles have been proposed.

As a conventionally proposed method for measuring the particle diameter of metal particles in oil and the number of the particles, for example, a light flux when a light beam (laser light or the like) narrowed down is applied to a working oil is used. There is a light transmission method in which the amount of transmitted light is measured and the particle size and the number of metal particles are detected based on the amount of transmitted light and the amount of change.
Further, for example, in Japanese Patent Laid-Open No. 59-42441, an electrode composed of a plurality of parallel thin film resistors is provided in oil, a predetermined voltage is applied to this electrode, and metal particles are generated by a magnet provided in the vicinity of the electrode. There has been proposed a magnetic sensor that attracts and accumulates and detects the presence or absence of metal particles and the amount of particles (pollution degree) based on the amount of change in resistance when the accumulated metal particles short-circuit the electrodes.

[0004]

However, according to the above-mentioned conventional light transmission method, it is possible to detect the particle size and the number of particles of metal particles. The operator must judge. That is, the operator determines whether there is damage or failure in the hydraulic equipment, or whether the hydraulic equipment is worn based on the measured particle size and the number of particles corresponding to the measured particle diameter, thereby performing failure diagnosis or failure prediction. Need to do. Further, since the measuring device itself is large, it is difficult to install the measuring device on, for example, a construction machine, and the cost is high. Further, with the above-mentioned magnet type sensor, the pollution level can be estimated by the particle amount of the metal particles in the oil, but detailed data such as the particle size cannot be measured. Therefore, the operator has to measure the particle size and the concentration thereof again by another method such as the above-mentioned light transmission method, which makes the work for the failure diagnosis very complicated.

As described above, the conventional failure diagnosis method is one in which the operator makes a judgment based on the measurement result, and is often performed based on the empirical know-how of the operator.
Therefore, failure diagnosis requires a great deal of skill, which is difficult for beginners and the like, and the result of the diagnosis tends to be extremely unreliable, resulting in large variation in the result of diagnosis among workers. For this reason, if the diagnosis is mistaken, a serious failure such as damage to the hydraulic equipment may occur in the worst case. There are many problems.

The present invention has been made in view of the above problems, and an object thereof is to provide an inexpensive and highly reliable fault diagnosis apparatus for hydraulic equipment and a method therefor.

[0007]

In order to achieve the above-mentioned object, the invention according to claim 1 is arranged in hydraulic fluid of hydraulic equipment, and a predetermined voltage is applied between electrodes. An applied electrode pair and a determination means for determining the presence or absence of metal particles in the hydraulic oil by detecting that metal particles mixed in the hydraulic oil short-circuit the electrodes are provided, and the result of this determination means In a failure diagnosing device for hydraulic equipment that performs failure diagnosis based on, pulsed means for pulsing a short-circuit current generated between the electrodes due to metal particles in the hydraulic oil, and a peak voltage of a pulse signal from the pulsing means. The signal processing unit 30 that detects the value and the peak voltage value from the signal processing unit 30 are input, and the particle size and concentration of the metal particles in the hydraulic oil are determined based on the peak voltage value and the count number of the pulse signal. Data to calculate A processing section 40, based on the particle size and concentration of the metal particles by the data processing unit 40 is calculated, and a configuration in which a control unit 50 for performing failure diagnosis of hydraulic equipment.

According to the first aspect of the present invention, when the electrode pair to which a predetermined voltage is applied is arranged in the hydraulic oil, a short-circuit current is generated between the electrodes due to the metal particles in the hydraulic oil adsorbed by the electric field between the electrodes. Occurs, and the pulsing means converts this short-circuit current into a pulse voltage signal. Then, when the peak value of this pulse voltage signal is detected by the signal processing unit 30,
The data processing unit 40 inputs this peak value and counts the number of counts of this pulse signal. This measurement is performed for a predetermined measurement unit time, and the particle diameter and concentration of the metal particles in the hydraulic oil, that is, the particle diameter distribution is calculated based on the collected peak value and count data. The above measurement unit time is continuously measured, and the particle size distribution is calculated for each measurement unit time. And the controller 50
Then, the failure of the hydraulic device is diagnosed and predicted based on the average size and the increasing rate of the calculated particle size and concentration of the particle size distribution. Therefore, it is not necessary to use an expensive optical device or the like in the conventional light transmission method, so that the structure can be constructed at low cost and highly reliable failure diagnosis can be performed.

According to a second aspect of the present invention, an electrode pair disposed in hydraulic fluid of a hydraulic device and having a predetermined voltage applied between the electrodes and metal particles mixed in the hydraulic fluid are present between the electrodes. And a determination means for determining the presence or absence of metal particles in the hydraulic oil by detecting the short-circuiting of the Pulsed means for pulsing a short-circuit current generated between the electrodes by the metal particles, a signal processing section 30 for detecting a peak voltage value of a pulse signal from the pulsing means, and a peak voltage value from the signal processing section 30. And a controller 50 for performing a failure diagnosis of the hydraulic equipment based on the peak voltage value and the count number of the pulse signal.

According to the second aspect of the present invention, when the electrode pair to which a predetermined voltage is applied is disposed in the hydraulic oil, a short-circuit current is generated between the electrodes due to the metal particles in the hydraulic oil adsorbed by the electric field between the electrodes. Occurs, and the pulsing means converts this short-circuit current into a pulse voltage signal. Then, when the peak value of this pulse voltage signal is detected by the signal processing unit 30,
The controller 50 inputs this peak value and counts the number of counts of this pulse signal. Then, without converting the peak value and the count number into the particle size and its concentration,
Fault diagnosis can be performed directly based on the peak value and the number of counts. That is, the above measurement is performed for a predetermined measurement unit time, and a distribution corresponding to the particle size distribution of the metal particles is created based on the data of the peak value and the count number collected during this time. The above measurement unit time is continuously measured, and this distribution is created for each measurement unit time.
Then, the failure of the hydraulic device is diagnosed and predicted based on the peak value of the created distribution, the average size of the count number, the increase rate, and the like. Therefore, it is not necessary to use an expensive optical device or the like in the conventional light transmission method, so that the structure can be constructed at low cost and highly reliable failure diagnosis can be performed.

According to a third aspect of the present invention, there is provided a method for diagnosing a failure in a hydraulic device based on a measurement result of the presence / absence of metal particles mixed in the hydraulic oil in the hydraulic device. A pair of electrodes to which a predetermined voltage is applied is arranged, the short-circuit current flowing between the electrodes is converted into a pulse signal, and the particle size of the metal particles in the hydraulic oil is calculated based on the peak voltage value and the count number of the pulse signal. And its concentration are calculated, and the failure diagnosis of the hydraulic equipment is performed based on this particle size and concentration.

According to the third aspect of the invention, the electrode pair to which a predetermined voltage is applied is disposed in the hydraulic fluid, and the electric field of the electrode pair causes a short circuit between the electrodes due to the metal particles in the hydraulic fluid adsorbed. When a current is generated, the adsorbed metal particles scatter due to resistance heat or discharge due to the short-circuit current, and the short-circuit state is released. Thus, the peak value of the pulse voltage signal generated between the electrodes is detected each time the pulse voltage signal is generated, and the count number of the pulse signal is counted.
This measurement is performed for a predetermined measurement unit time, and the particle size and concentration of the metal particles in the hydraulic oil, that is, the particle size distribution, is calculated based on the collected peak value and count data. The measurement of the measurement unit time is continuously performed, and the particle size distribution is calculated for each measurement unit time.
Then, the failure of the hydraulic device is diagnosed and predicted based on the average size and rate of increase of the particle size and concentration of the calculated particle size distribution. Therefore, since it is not necessary to use expensive optical equipment or the like in the conventional light transmission type method, it can be configured at low cost,
In addition, highly reliable fault diagnosis is possible.

According to a fourth aspect of the present invention, in the fault diagnosis method for hydraulic equipment according to the third aspect, an increase rate of the concentration of the metal particles is obtained, and the fault diagnosis of the hydraulic equipment is performed based on the concentration increase rate. I am going to do it.

According to the invention described in claim 4, it is possible to monitor the increase rate of the concentration of the metal particles measured for each measurement unit time, and judge the failure when the increase rate suddenly increases. it can. This improves the reliability of failure diagnosis.

According to a fifth aspect of the present invention, in the failure diagnosis method for hydraulic equipment according to the third aspect, an increase rate of the average value of the particle diameters of the metal particles is obtained, and based on the average particle diameter increase rate. The method is used to diagnose failures in hydraulic equipment.

According to the invention described in claim 5, the average particle size of the metal particles is calculated for each measurement unit time, the rate of increase of the average particle size is monitored, and the rate of increase suddenly increases. It can be judged as a failure. This improves the reliability of failure diagnosis.

According to a sixth aspect of the present invention, in the fault diagnosis method for hydraulic equipment according to the third aspect, the concentration of metal particles for each particle size is obtained, and the fault diagnosis of the hydraulic equipment is performed based on this concentration. I have a method.

According to the sixth aspect of the invention, the concentration of the metal particles measured for each measurement unit time is monitored, and based on the size of the concentration, for example, the concentration of a specific particle size is measured. It is possible to diagnose the wear or failure of a specific hydraulic device when the value becomes larger than a predetermined value. Therefore, the reliability of failure diagnosis is improved.

According to a seventh aspect of the present invention, in the failure diagnosis method for hydraulic equipment according to the third aspect, an average value of the particle diameters of the metal particles is obtained, and the failure diagnosis of the hydraulic equipment is performed based on the average particle diameter. To do.

According to the invention described in claim 7, the average particle size for each measurement unit time is calculated based on the particle size of the metal particles measured for each measurement unit time and the concentration size for each particle size. Calculate and monitor this average particle size. When the average particle size becomes larger than a predetermined value, it can be diagnosed as wear or failure of a specific hydraulic device, for example. Therefore, the reliability of failure diagnosis is improved.

The invention according to claim 8 is the invention according to claim 4 or 5.
In the failure diagnosis method of the hydraulic device described, when performing failure diagnosis based on the concentration increase rate or the average particle size increase rate,
Fault diagnosis of hydraulic equipment based on the calculated concentration increase rate or average particle size increase rate only when the number of pulses counted within the measurement unit time T0 is greater than or equal to a predetermined value and the variation in measured data is less than or equal to the predetermined value. To do.

According to the eighth aspect of the invention, in the case of failure diagnosis based on the increase rate of the concentration or the average particle size,
When the amount of data, that is, the number of pulse counts is less than or equal to a predetermined value, the variation in the increase rate to be calculated becomes large, so that the reliability of failure diagnosis decreases. Therefore, the failure diagnosis is performed based on the rate of increase in concentration or the rate of increase in average particle diameter only when the count number equal to or larger than the predetermined value is obtained. Further, the concentration increase rate or the average particle size increase rate calculated from the particle size distribution obtained in a certain measurement unit time is correlated with the concentration increase rate or the average particle size increase rate calculated from the particle size distribution in the preceding and following measurement unit time. The value of the calculated concentration increase rate or average particle size increase rate is regarded as valid only when the value is large (the variation is small). As a result, false alarms due to the increase rate can be eliminated and the reliability of failure diagnosis can be improved.

According to a ninth aspect of the present invention, in the failure diagnosis method for hydraulic equipment according to any one of the third to eighth aspects, when the concentration of metal particles is calculated based on the count number, the temperature is The density corrected by is calculated, and the failure diagnosis of the hydraulic equipment is performed based on this density.

According to the ninth aspect of the present invention, it is possible to eliminate the variation in the concentration obtained from the pulse signal count number due to the temperature, so that the reliability of the failure diagnosis is improved. That is, generally, as the oil temperature rises, the viscosity of the oil decreases, and the velocity of the metal particles in the oil also rises, so that the velocity of particles attracted to the electric field between the electrodes increases. As a result, the number of particles captured between the electrodes per unit time also increases, so that the frequency of pulse signal generation increases. Therefore, when the concentration of the metal particles is obtained based on the count number of the pulse signal, it is necessary to correct the temperature. In the present invention, since the failure diagnosis is performed based on the temperature-corrected concentration, the reliability of the failure diagnosis is improved.

[0025]

DETAILED DESCRIPTION OF THE INVENTION A detailed description will be given below with reference to the drawings. First, the structure and operation of a metal particle detection sensor of a failure diagnosis device for hydraulic equipment according to the present invention will be described with reference to FIGS.

FIG. 1 is a front view showing an embodiment of a sensor body of a metal particle detecting sensor. The sensor body 10 is composed of a plug having a hexagonal head portion 11 at the upper portion and a tapered screw portion 13 at the lower portion, and can be screwed into a screw hole provided in a side wall of a tube such as a hydraulic pipe.
A liquid contact portion surface 15 that is tapered is provided at the lower end of the screw portion 13, and the inside of the sensor body 10 is hollowed from the head portion 11 to the liquid contact portion surface 15 (not shown). ) Is provided. Liquid contact surface 1
An electrode pair 2 made of platinum foil is exposed inside the electrode 5, and the electrode pair 2 and the sensor body 10 are insulated from each other by the insulator 3 between the electrodes 2a and 2b constituting the electrode pair 2. . The lead wires 1a, 1b of the electrodes 2a, 2b are guided to the outside from the head 11 through the through holes and connected to a connector (not shown) or the like. It is connected to the processing unit. The lead wires 1a and 1b and the sensor body 10 are similarly insulated by the insulator 3. Further, although a comb-shaped electrode is shown as an electrode in FIG. 1, the present invention is not limited to the comb-shaped electrode, and may be configured with a flat counter electrode, for example.

FIG. 2 is a block diagram showing an example of the failure diagnosis apparatus according to the present invention. The electrode pair 2 is formed by arranging electrodes 2a and 2b having a predetermined width D2 (for example, 50 .mu.m) and a length L on an insulator by a predetermined electrode pair distance D1 (for example, 25 .mu.m). Lead wires 1a and 1b are respectively connected to 2b. Lead wire 1b
Is connected to the ground, and the lead wire 1a is connected to the DC power supply 6 via the resistor 5. Also, resistor 5 and lead wire 1
The connection point with a is connected to the signal processing unit 30 via the capacitor 7, and the output of the signal processing unit 30 is fetched by the controller 50 via the data processing unit 40. The resistor 5, the DC power source 6 and the capacitor 7 form a pulsing means. The signal processing unit 30 can be composed of, for example, an electronic circuit such as an operational amplifier or a microcomputer. In addition, the data processing unit 40 and the controller 5
0 is composed of, for example, a computer system mainly composed of a microcomputer, which is independent of each other, or
Both may be configured by one computer system.

The pulsing means is for generating a pulse signal by a short-circuit current flowing between the electrodes when the metal particles in the hydraulic oil are trapped between the electrodes. Here, FIG.
The operation of the pulsing means will be described with reference to. This figure is an explanatory view of the action when a pulse voltage is generated by the metal particles on the electrodes 2a, 2b. When a predetermined DC voltage (for example, DC50V) is applied between the electrodes 2a and 2b by the DC power supply 6, the metal particles such as iron powder floating in the hydraulic oil are ionized and attracted to the electric field between the electrodes, It is adsorbed by the electrode 2b on the cathode side. At this time, since the distance between the adsorbed metal particles and the electrode 2a becomes short, the electric field between them becomes large, whereby other metal particles in the hydraulic oil are further adsorbed by the metal particles. In this way, FIG.
As shown in (1), the metal particles are adsorbed in a chain form one after another. Then, as shown in FIG. 3 (2), when a bridge is finally formed between the electrodes 2a and 2b by the chain-shaped metal particles, a short-circuit current flows through the bridge. The magnitude of this short-circuit current has a correlation with the particle size of the metal particles. The short-circuit current causes a voltage drop across the resistor 5, and the potential of the positive electrode 2a decreases. After that, as shown in FIG. 3C, the metal particles forming the bridge are scattered by resistance heat of short-circuit current, discharge, etc., and the electrode state returns to the state before the particle adsorption. As a result, the electric potential of the electrode 2a returns to the original level, which means that the pulse voltage is generated. By repeating the above process,
A pulse voltage signal appears at the potential of the electrode 2a.

The present inventors have conducted experiments to find that the above-mentioned peak value of the pulse voltage signal has a correlation with the particle size, and that the frequency of occurrence of the pulse signal has a correlation with the concentration of metal particles having the corresponding particle size. I have confirmed it. Based on this, the particle size and concentration of the metal particles are identified as follows. That is, the above pulse voltage signal is input to the signal processing unit 30 by the action of AC coupling by the capacitor 7. In the signal processing unit 30, the voltage of the pulse voltage signal is level-converted by, for example, voltage division, the voltage is peak-held, and the peak voltage signal is output to the data processing unit 40. This peak voltage signal is reset for the next peak hold after a predetermined time. The data processing unit 40 performs A / D conversion processing on the input peak voltage signal, stores the magnitude of the converted peak voltage value, and counts up the number of pulses in the peak voltage region corresponding to the magnitude. Then, the above measurement is performed within a predetermined measurement unit time (for example, 10 minutes), and after the measurement unit time ends, the particle size is identified based on the magnitude of each stored peak voltage value, and The particle concentration is identified from the pulse count number corresponding to this particle size. In this way, the data processing unit 40 creates the particle size distribution (particle size and concentration) of the metal particles mixed in the hydraulic oil. The controller 50 performs failure diagnosis or failure prediction of hydraulic equipment based on this particle size distribution, and when it judges that there is an abnormality in the diagnosis result, for example, a warning device such as a display device, a warning lamp, a buzzer, or the like (not shown) warns the operator. To inform.

FIG. 4 shows an example of the particle size distribution created within the above measurement unit time. In the figure, the horizontal axis represents the particle size and the vertical axis represents the number of particles (concentration). In order to facilitate the creation of this particle size distribution, the data processing unit 40 counts up the number of pulses for each particle size range divided by a predetermined particle size width, as shown in FIG. In FIG. 5, the horizontal axis is, for example, 0.5 to 5, 5 to 15, and 15 to 2.
It is divided by a predetermined voltage width corresponding to each particle diameter width of 5, 25 to 50 μm, and the vertical axis represents the count number of the peak value Vp included in each voltage width. Here, each voltage segment on the horizontal axis is represented by Vi, and the count number corresponding to each voltage segment Vi (i = 1 to 4) is represented by Ci (V). The voltage classification V
If the number of divisions of i is increased, the accuracy of the particle size distribution is improved, but the computer processing time of the data processing unit 40 is increased. Therefore, it is necessary to set the number of divisions in relation to the computing ability of the computer.

Next, a method of creating a particle size distribution in the above measurement unit time will be described with reference to FIG. FIG. 6 shows an example of a processing flow chart when the particle size distribution is created in the data processing unit 40, where S represents each step number.
At S1, the timer value T and the count number Ci (V) are reset. Here, the timer value T is a variable for measuring the data measurement time for creating the particle size distribution as described above, and Ci (V) corresponds to each voltage classification Vi of this particle size distribution. It is the number of counts. Immediately before proceeding to S2, counting of the timer value T is started. Next, S2
Then, the peak value V of the pulse voltage signal from the signal processing unit 30
p is input, and in S3, the count number Ci (V) corresponding to the voltage section Vi including the input peak value Vp is incremented by one. Then, in S4, the timer value T is input,
It is determined whether or not the timer value T has exceeded the measurement unit time T0. This measurement unit time T0 is a unit time for collecting data for creating the particle size distribution, and is a predetermined value in advance,
For example, it is set to 10 minutes. When the timer value T is not equal to or greater than the measurement unit time T0 in S4, the process is returned to S2 and the processing is repeated. When the timer value T is equal to or greater than the measurement unit time T0, in S5, the data collected within the measurement unit time T0 are collected. A particle size distribution is created based on the voltage classification Vi and the count number Ci (V).

The concentration of the particle size distribution obtained in S5 is corrected and obtained by multiplying the count number Ci (V) by the conversion coefficient α (generation frequency function). This conversion coefficient α is usually a function of the electrode pair distance D1 of the electrode pair 2, the electrode area (area of the electrode pair), and the velocity of the metal particle to be measured,
It is intended to correct the difference in the proportional coefficient between the count number Ci (V) and the particle concentration depending on these sizes. Here, if the electrode pair distance D1 and the electrode area are made constant, it becomes a function only of the velocity of the metal particles. In particular, the present inventors have confirmed by experiments that the velocity of the metal particles largely depends on the oil temperature, and therefore the pulse count number greatly depends on the oil temperature. For example, a curve showing the temperature dependence as shown in FIG. 7 is obtained.

The above temperature dependence is explained as follows. Number of pulse counts (ie pulse generation frequency)
Is considered to be proportional to the concentration of metal particles existing in the vicinity of the electrode and the velocity U of the metal particles when attracted to the electrode. Here, the velocity U of the metal particles is determined by the attractive force due to the electric field that does not depend on the particle size and the oil viscosity η, and the measured metal particles are 100 μm or less, and S
It is supposed to follow the Tokes formula. At this time, the velocity U of the metal particles is represented by the mathematical expression “velocity U∝1 / η”.
Generally, when the oil temperature rises, the viscosity η of the oil decreases, but the velocity U of the metal particles attracted to the electrodes rises according to the above equation, and the metal particles are trapped between the electrodes per unit time. The rate increases. Therefore, the frequency of pulse generation increases as the temperature rises. In order to consider the temperature dependency of such a count number, when actually calculating the concentration, it is corrected by the conversion coefficient α. In the present embodiment, as shown in FIG. 7, the pulse frequency at the oil temperature of 80 ° C. is set to the reference value “1”, and the reciprocal of the value on the correction curve for each oil temperature is set to the conversion coefficient α. And
At each measurement, the oil temperature is measured by a temperature sensor (not shown) of the hydraulic oil, the conversion coefficient α for the oil temperature is obtained, and the conversion coefficient α is converted into the count number Ci (V) corresponding to each voltage classification Vi.
The actual density Mi is calculated by multiplying by.

By the above processing, the particle size distribution corresponding to the measurement unit time T0 per time is created. This measurement is continuously performed, for example, eight times, and the particle size distributions created at each time are arranged in time series, whereby a temporal transition diagram of the particle size distribution as shown in FIG. 8 is obtained. The controller 50 can perform various kinds of failure diagnosis based on this transition diagram. FIG. 9 shows a processing flowchart at the time of this failure diagnosis, and the failure diagnosis method will be described in detail below with reference to the figure.

In S11, it is judged whether or not the stationary particle concentration calculated based on the particle size distribution of each time is equal to or higher than a predetermined concentration limit value ML, and if it is equal to or higher than the concentration limit value ML, it is considered to be abnormal, and in S12. For example, a message display, a warning lamp, a buzzer or the like is used to notify the abnormality. Also, in S11, the concentration limit value ML
If it is smaller, the process proceeds to S13. Here, the stationary particle concentration is calculated from the average value of the count numbers of the time series data for eight times for each particle size width. That is, the total value A of the count numbers for eight times is calculated for each particle size width, and the average value is calculated by the mathematical expression “total value A / 8”, and the average count number is multiplied by the conversion coefficient α to obtain the average density. Is obtained, and this is set as the stationary particle concentration for each particle size width at the present time. Further, the concentration limit value ML is preset for each particle size width,
Usually, it can be set according to the oil pollution degree evaluation standard widely used in industry. As the pollution degree evaluation standard, for example, NAS grade is specified, and 100 ml
The degree of contamination is determined from the number of particles of 5 to 15, 15 to 25, and 25 to 50 μm. In this way, the concentration limit value ML and the calculated stationary particle concentration are compared for each particle size width.

In S13, it is judged whether or not the concentration increase rate for each particle size width calculated based on the particle size distribution at each time is equal to or higher than a predetermined concentration increase rate limit value MZL, and the concentration increase rate limit value MZL or more is determined. When it is determined that there is an abnormality, the abnormality is notified in S14 in the same manner as above. When the concentration increase rate limit value MZL is smaller than
Proceed to S15. Here, the concentration increase rate represents the concentration change rate for each particle size width with respect to time, and the concentration change with respect to time is simply approximated by a linear expression, and the slope of this linear expression is used as the concentration increase rate. are doing. Specifically, the count numbers are arranged in time series for each particle size width, and the difference value between the (n-1) -th count number and the n-th count number is set as the concentration increase rate per measurement unit time T0. Further, the concentration increase rate limit value MZL is preset for each particle size width, and the standard concentration increase rate limit value MZL can be experimentally determined, for example.

At this time, if the count number is less than or equal to a predetermined value, the density increase rate calculated from this data varies greatly and the reliability is low. Therefore, it is a precondition that the count number is greater than or equal to the predetermined value. It is necessary. In addition, the reliability of the measurement data can be improved based on the degree of correlation of the concentration change with respect to the time change. For example, it is possible to obtain a value indicating the degree of correlation such as a correlation coefficient or covariance from the density increase rate data obtained for eight times. Only when the correlation coefficient is a certain value or more, the obtained density The rate of increase can be considered valid. Therefore, when the concentration increase rate calculated in a certain measurement unit time exceeds the specified value, the correlation coefficient is calculated including the concentration increase rate calculated in the subsequent measurement unit time, and the previous concentration Only when the correlation coefficient of the increase rate is large (the variation is small), the value of the previously calculated density increase rate is regarded as valid. As a result, it is possible to eliminate false alarms at the time of diagnosis due to the increase rate and to improve reliability.

At S15, it is judged whether or not the average particle size calculated based on the particle size distribution of each time is equal to or more than a predetermined average particle size limit value RL. , S16, the abnormality is notified in the same manner as above. When it is smaller than the average particle size limit value RL, the process proceeds to S17. Here, the average particle size is an average value of all particle sizes for each time (measurement unit time T0) and is calculated as follows. First, a representative value for each particle size width is set. For this representative value, for example, “5” is set in the range of 5 to 15 μm and is set to 15 to 2
“15” can be adopted in the range of 5 μm and “25” can be adopted in the range of 25 to 50 μm. Then, the product of the count number of each particle size width and the representative value is calculated, and this product is summed for all particle size widths in the same measurement time, and this total value is calculated as the total count number in the same measurement time ( It corresponds to the number of particles) divided by. As a result, a parameter that artificially represents the average particle size of the particle size distribution at that measurement time is obtained. The representative value is not limited to the above value, but may be, for example, the median value of the particle size width. In addition, the above-mentioned pseudo parameter can be made closer to the true average particle size by dividing the particle size width into four, which is not the same as in the present embodiment. To obtain the average particle size with higher accuracy, at the time of measurement, the particle size corresponding to this peak value is calculated for each peak value input, and this value is integrated, and this integrated value is calculated after the measurement unit time T0 ends. It is also possible to obtain by dividing by the total number of counts.

In S17, the average particle size increase rate calculated based on the particle size distribution of each time is the predetermined average particle size increase rate limit value RZL.
Whether or not it is above is judged, and when it is equal to or larger than the average particle size increase rate limit value RZL, it is considered that there is an abnormality, and the abnormality is notified in the same manner as above in S18. When it is smaller than the average particle size increase rate limit value RZL, the diagnosis process is ended at the end and the above-described measurement process flow is executed. Here, the average particle size increase rate represents the temporal change rate of the average particle size obtained in the previous step, and is specifically calculated as follows. That is, the average particle diameters obtained in each time are arranged in time series, and the difference value between the (n-1) th and nth average particle diameters is taken as the average particle diameter increase rate per measurement unit time T0. Further, the average particle size increase rate limit value RZL is preset, and for example, the standard average particle size increase rate limit value RZL can be experimentally determined. As in the case of the concentration increase rate described above, in order to improve the reliability of the diagnosis result, it is necessary to use the correlation coefficient of the measurement data or the predetermined count number as a precondition for diagnosis.

In the above description, the measured peak value and its pulse count number are converted into the particle size and its concentration by the data processing unit 40, and the controller 50 diagnoses the failure based on this particle size and its concentration. However, the present invention is not limited to this. That is, the peak value and the pulse count number thereof uniquely correspond to the particle size and the concentration of the metal particles. Therefore, based on the peak value and the pulse count number thereof, for example, the peak value and the count number may be multiplied to obtain the average peak value, and the average particle size may be substituted. As a result, the same failure diagnosis can be performed, and the calculation time can be shortened. Further, the setting of the measurement time, the particle size width, etc. is not limited to the above-mentioned values, but can be changed depending on the relation with the calculation processing capacity and the reliability of each calculated data.

As described above, based on the particle size distribution measured in a time series, the average value of the particle size of the metal particles in the oil and its concentration and the temporal increase rate were obtained, and these results were obtained. The failure prediction and diagnosis of hydraulic equipment are performed by. Therefore, since the diagnosis can be made without depending on the experience and intuition of the operator, the variation of the diagnosis result is eliminated and the reliability is improved. Further, since no expensive optical equipment or the like is used, an inexpensive failure diagnosis device can be constructed.

[Brief description of drawings]

FIG. 1 is a front view of an example of a sensor body of a failure diagnosis device according to the present invention.

FIG. 2 is a configuration diagram of an example of a failure diagnosis device according to the present invention.

FIG. 3 is an operation explanatory diagram when a pulse voltage is generated in the failure diagnosis device according to the present invention.

FIG. 4 is an example of a particle size distribution created by the failure diagnosis apparatus according to the present invention.

FIG. 5 is an explanatory diagram of particle size distribution creation by the failure diagnosis device according to the present invention.

FIG. 6 shows an example of a flowchart for creating a particle size distribution according to the present invention.

FIG. 7: Particle concentration (pulse count number) according to the present invention
And the oil temperature.

FIG. 8 shows a particle size distribution transition diagram at the time of failure diagnosis according to the present invention.

FIG. 9 shows an example of a processing flowchart at the time of failure diagnosis according to the present invention.

[Explanation of symbols]

 1a, 1b Lead wire 2 Electrode pair 2a, 2b Electrode 3 Insulator 5 Resistance 6 DC power supply 7 Capacitor 10 Sensor body 11 Head 13 Screw part 15 Liquid contact part surface 30 Data processing part 40 Data processing part 50 Controller Vp peak voltage Value Vi Voltage category Ci (V) Count number

Claims (9)

[Claims] Claims: 1. Arranged in hydraulic fluid of hydraulic equipment, and
Equipped with a pair of electrodes to which a predetermined voltage is applied between the electrodes, and a determination means for determining the presence or absence of metal particles in the hydraulic oil by detecting that metal particles mixed in the hydraulic oil short-circuit the electrodes. In a failure diagnosis device for a hydraulic device that performs failure diagnosis based on the result of the determination means, a pulsing means for pulsing a short-circuit current generated between the electrodes by the metal particles in the working oil, and a pulsing means The signal processing unit (30) for detecting the peak voltage value of the pulse signal of, and the peak voltage value from the signal processing unit (30) is input, based on the peak voltage value and the count number of the pulse signal,
A data processing unit (40) that calculates the particle size and concentration of the metal particles in the hydraulic oil, and a control that performs failure diagnosis of hydraulic equipment based on the particle size and concentration of the metal particles calculated by the data processing unit (40). A failure diagnosis device for hydraulic equipment, characterized by comprising: 2. Arranged in hydraulic fluid of hydraulic equipment, and
Equipped with a pair of electrodes to which a predetermined voltage is applied between the electrodes, and a determination means for determining the presence or absence of metal particles in the hydraulic oil by detecting that metal particles mixed in the hydraulic oil short-circuit the electrodes. In a failure diagnosis device for a hydraulic device that performs failure diagnosis based on the result of the determination means, a pulsing means for pulsing a short-circuit current generated between the electrodes by the metal particles in the working oil, and a pulsing means The signal processing unit (30) for detecting the peak voltage value of the pulse signal of, and the peak voltage value from the signal processing unit (30) is input, based on the peak voltage value and the count number of the pulse signal,
A fault diagnosis device for a hydraulic device, comprising: a controller (50) for performing a fault diagnosis of the hydraulic device. 3. A method of diagnosing a failure of a hydraulic device based on a measurement result of the presence or absence of metal particles mixed in the hydraulic oil of the hydraulic device, wherein an electrode to which a predetermined voltage is applied in the hydraulic oil. A pair is provided, the short-circuit current flowing between the electrodes is converted into a pulse signal, and the particle size and the concentration of the metal particles in the hydraulic oil are calculated based on the peak voltage value and the count number of the pulse signal, A method for diagnosing a failure in a hydraulic device, which comprises performing a failure diagnosis for a hydraulic device based on the particle size and the concentration. 4. The failure diagnosis method for hydraulic equipment according to claim 3, wherein an increase rate of the concentration of the metal particles is obtained, and a failure diagnosis of the hydraulic equipment is performed based on the concentration increase rate. 5. The hydraulic equipment according to claim 3, wherein an increase rate of the average value of the particle diameters of the metal particles is obtained, and failure diagnosis of the hydraulic equipment is performed based on the average increase rate of the particle diameter. Failure diagnosis method. 6. The fault diagnosis method for hydraulic equipment according to claim 3, wherein the concentration of metal particles for each particle size is obtained, and the fault diagnosis for hydraulic equipment is performed based on this concentration. 7. The failure diagnosis method for hydraulic equipment according to claim 3, wherein an average value of the particle diameters of the metal particles is obtained, and failure diagnosis of the hydraulic equipment is performed based on the average particle diameter. 8. The fault diagnosis method for hydraulic equipment according to claim 4 or 5, wherein when the fault diagnosis is performed based on the concentration increase rate or the average particle size increase rate, the number of pulses counted within a measurement unit time T0 is Failure of hydraulic equipment characterized by performing a failure diagnosis of hydraulic equipment based on the calculated concentration increase rate or average particle size increase rate only when the variation in measured data is less than or equal to a predetermined value and less than a predetermined value. Diagnostic method. 9. The fault diagnosis method for hydraulic equipment according to claim 3, wherein when the concentration of metal particles is calculated based on the count number, the concentration corrected by temperature is obtained. A method for diagnosing a failure in a hydraulic device, which comprises performing a failure diagnosis in a hydraulic device based on the concentration.