TW202244650A - Diagnosis system, diagnosis method and program - Google Patents

Abstract

Provide a diagnostic system that can diagnose the status of equipment without a threshold. The diagnostic system comprising a measurement result acquisition unit that acquires measurement values of the current supplied to each of a plurality of facilities, an analysis unit that performs frequency analysis of the measurement values, an extraction unit that extracts the frequency component values of a predetermined frequency from the analysis results of the frequency analysis as evaluation values indicating the status of the facilities, and an output unit that outputs the evaluation values for each facility in a comparable manner.

Description

Diagnostic system, diagnostic method and program

The present disclosure relates to diagnostic systems, diagnostic methods and procedures. This disclosure claims priority based on Japanese Patent Application No. 2021-025194 filed in Japan on February 19, 2021, and its content is used here.

A diagnostic method is provided for setting a threshold value in the value of the state quantity of the device, and if the value exceeds the threshold value, it is diagnosed as an abnormality. For example, Patent Document 1 discloses a state analysis device that obtains the measured values of a plurality of state quantities, predicts the range in which the value of each state quantity can be obtained after a predetermined time, and uses each of the state quantities as an axis in a coordinate space. , to display a graph corresponding to the shape of the range that can obtain the value of the complex state quantity. In the method described in Patent Document 1, the graph representing the range of obtainable state quantity values is also compared with the threshold value to determine whether the device may transition to an abnormal state in the future. [Prior Art Literature] [Patent Document]

[Patent Document 1] Japanese Patent Laid-Open No. 2018-195266

(Problem to be solved by the invention)

There are various types of equipment failures, and it is extremely important to set appropriate thresholds for each failure mode in equipment status evaluation. In the setting of the threshold value, it is necessary to have the diagnostic results under various failure modes, so the abnormal data of each failure mode must be collected. However, even if the data are collected, most of them are normal data, and it is difficult to collect abnormal data. In addition, even if abnormality data can be collected, the threshold value for abnormality determination may vary depending on the specifications of the device, operating environment, etc., so it is not easy to set an appropriate threshold value for each device.

This disclosure provides a diagnostic system, a diagnostic method, and a program that can solve the above-mentioned problems. (technical means to solve the problem)

The diagnostic system of the present disclosure includes: a measurement result acquisition unit that acquires the measured value of the current supplied to each of the plurality of devices; an analysis unit that performs frequency analysis on the measurement value; and an extraction unit that obtains the frequency An analysis result of the analysis extracts a frequency component value of a predetermined frequency as an evaluation value representing a state of the aforementioned equipment; and an output unit that outputs the aforementioned evaluation value of each of the aforementioned equipment for comparison.

The diagnostic system disclosed in the present disclosure is a diagnostic system composed of a terminal device and a diagnostic device capable of communicating with the terminal device. The terminal device is provided with: request means for requesting diagnosis of each state of a plurality of devices; and output a part for outputting the evaluation value of each of the aforementioned devices extracted by the extracting part of the aforementioned diagnostic device for comparison, and the aforementioned diagnostic device is provided with: a measurement result obtaining part which obtains a measurement result according to a request from the terminal device A measured value of the current supplied to each of the plurality of devices; an analyzing unit that performs frequency analysis on the measured value; and an extracting unit that extracts a frequency component value of a predetermined frequency from the analysis result of the frequency analysis to represent Estimated value of the status of the aforementioned device.

The diagnostic method of the present disclosure includes: a step of acquiring measured values of currents supplied to a plurality of devices; a step of performing frequency analysis on the measured values; and extracting a frequency component value of a predetermined frequency from the analysis results of the frequency analysis as a step of indicating an evaluation value of a state of the aforementioned equipment; and a step of outputting the aforementioned evaluation value extracted for each of the aforementioned equipment for comparison.

The diagnostic method of the present disclosure is a diagnostic method performed by a terminal device and a diagnostic device capable of communicating with the terminal device. The terminal device executes: a request step that requires diagnosis of each state of a plurality of devices; and output A step of outputting the evaluation value of each of the aforementioned devices extracted by the extracting step of the aforementioned diagnostic device for comparison, and the aforementioned diagnostic device executes: a step of obtaining measurement results, which is obtained by request of the aforementioned terminal device A measured value of the current supplied to each of the plurality of devices; an analyzing step of performing frequency analysis on the measured value; and an extracting step of extracting a frequency component value of a predetermined frequency from the analysis result of the frequency analysis as a value representing the aforementioned Estimated value of the state of the device.

The program of the present disclosure causes a computer to execute: a step of acquiring measured values of currents supplied to a plurality of devices; a step of performing frequency analysis on the measured values; and extracting a frequency component value of a predetermined frequency from the analysis results of the frequency analysis. a step of being an evaluation value representing the state of the aforementioned equipment; and a step of outputting the aforementioned estimated value extracted for each of the aforementioned equipment for comparison. (Effect of Invention)

With the above-mentioned diagnostic system, diagnostic method, and program, it is possible to appropriately diagnose the diagnostic object.

The diagnostic system of the embodiment will be described in detail below while referring to FIGS. 1 to 8 . ＜First Embodiment＞ (System Components) Fig. 1 is a block diagram showing an example of a diagnosis system of the embodiment. The diagnosis system 100 includes devices 10A, 10B, . . . and a diagnosis device 20 to be diagnosed. The equipment 10A and the equipment 10B are of the same specification. The same specification means that the equipment included in the facility 10A has the same specifications as the equipment included in the facility 10B, or that the specifications of the equipment are only different to the extent that the specifications of the equipment are regarded as the same. Specifications refer to, for example, the material, size, type, function or performance of a machine. For example, the facility 10A includes a power source 1A, a motor 2A, a transmission device 3A, a load device 4A, and a current measurement device 5A. The motor 2A is connected to the transmission device 3A by a shaft 6A, and the transmission device 3A is connected to the load device 4A by a shaft 7A. The power source 1A supplies electric current to the motor 2A through the electric wire 8A. The motor 2A is rotationally driven by the electric current supplied from the electric power source 1A, and rotates the shaft 6A. The transmission device 3A transmits the rotation of the shaft 6A to the shaft 7A. The load device 4A is driven by the rotation of the shaft 7A. The transmission device 3A is, for example, a reduction gear, a belt drive device, or the like. The loading device 4A is, for example, a fan or a centrifugal separator. The current measurement device 5A measures the current flowing through the electric wire 8A, and transmits the measurement result of the current to the diagnosis device 20 . The current measuring device 5A converts the measured analog current waveform into digital current data and sends it to the diagnostic device 20 . The power source 1A, the motor 2A, the transmission device 3A, the load device 4A, the current measuring device 5A, the shaft 6A, and the shaft 7A are examples of machines.

Although not shown in the figure, the facility 10B is also equipped with the power source 1B, motor 1B and motor of the same specifications as the power source 1A, motor 2A, transmission device 3A, load device 4A, current measuring device 5A, shafts 6A, 7A of the facility 10A. 2B, the transmission device 3B, the load device 4B, the current measurement device 5B, the shafts 6B, 7B, and these have the same configuration as the equipment 10A. For example, the current measurement device 5B of the facility 10B transmits the measurement result of the current to the diagnosis device 20 .

Although the devices 10A and 10B are illustrated in FIG. 1 , the diagnostic system 100 may include three or more devices 10 of the same specification. For example, if the diagnostic system 100 includes four devices, each will be described as devices 10A, 10B, 10C, and 10D. Hereinafter, unless distinction is necessary, the equipment 10A, 10B, etc. may be described as the equipment 10 , and the motors 2A, 2B, etc. may be described as the motor 2 . The same goes for other machines.

(Configuration of diagnostic device) The diagnostic device 20 includes a measurement result acquisition unit 21 , an analysis unit 22 , a diagnostic processing unit 23 , an input unit 24 , a display unit 25 , and a memory unit 26 . The measurement result acquisition unit 21 acquires the measurement result of the current flowing through the motor 2 . The measurement result acquisition unit 21 is configured using an input interface or a communication interface for inputting measurement results obtained by the current measurement device 5 , and acquires digital current data transmitted from the current measurement device 5 . The analysis unit 22 decomposes the measurement result acquired by the measurement result acquisition unit 21 into complex frequency components by FFT (Fast Fourier Transform).

The diagnosis processing unit 23 executes a process of diagnosing the state of equipment (for example, the motor 2 , the communication device 3 , and the load device 4 ) included in the equipment 10 . For example, the diagnosis processing unit 23 extracts information indicating the state of the motor 2A and the like from the analysis result obtained by the analysis unit 22 and displays it on the display unit 25 . Specifically, the analysis result obtained after the FFT is performed by the analysis unit 22 is in frequencies other than the frequency of the power supply such as 50 kHz and 60 kHz, and the corresponding device or a part of the configuration device (referred to as a specific part) is reflected in the frequency component. ) state change. For example, in the case of the load device 4 , the rotation frequency generated in the sideband from the power supply frequency of the load device 4 among the frequency components included in the current measurement value indicates a change in the state of the load device 4 . For example, when the state of the load device 4 deteriorates, the frequency component value of the rotation frequency of the load device 4 increases. Using this property, the diagnosis processing unit 23 extracts frequency component values that contribute to the diagnosis of each device from the analysis results of the analysis unit 22 . For example, if the state of the motor 2 deteriorates, the frequency component value near the frequency f1 increases, if the state of the communication device 3 deteriorates, the frequency component value near the frequency f2 increases, and if the state of the load device 4 deteriorates, the frequency component value near the frequency f3 increases. Composition value increased. The diagnosis processing unit 23 extracts a frequency component value near the frequency f1 from the FFT analysis result, and displays the value on the display unit 25 as an evaluation value for diagnosing the state of the motor 2 . For example, the diagnosis processing unit 23 creates a diagnosis chart illustrated in FIGS. 2A to 2F described later, and displays it on the display unit 25 .

The input part 24 is comprised using input devices, such as a keyboard, a mouse, and a touch panel. The input unit 24 accepts an input of an operation of the diagnostic device 20 . The input unit 24 outputs the content of the received operation input to the diagnostic processing unit 23 . The display unit 25 is configured using a display device such as a liquid crystal display or an organic EL (Electro-luminescence) display. The display unit 25 displays arbitrary information according to an instruction from the diagnostic processing unit 23 .

The storage unit 26 is constituted using a storage device such as HDD or flash memory. The memory unit 26 stores various information necessary for diagnosing the state of the equipment, for example, information for setting the frequency of the current measurement value indicating the state of the equipment for each equipment. Specifically, in the memory unit 26, the motor 2 stores information such as the frequency f1, the transmission device 3 stores the frequency f2, and the load device 4 stores information such as the frequency f3. It is also possible to set two or more frequencies for one machine, or to set the frequency for each specific part of the machine. Specifically, the memory unit 26 associates the frequency f11 for diagnosing the state of the rotor bar of the electric motor 2 and the frequency f12 for diagnosing the state of the rotating shaft with respect to the motor 2 with each specific portion (rotor bar ( rotor bar), rotation axis) to establish a correspondence for memory.

(diagnosis method) 2A to 2F are the first to sixth diagrams respectively showing an example of the diagnostic chart of the embodiment. The vertical axis of the graphs shown in Fig. 2A ~ Fig. 2F is the frequency component value (dB) of a specific part based on the power frequency component value, and the horizontal axis is used for other equipment. FIG. 2A is a diagnostic graph showing frequency component values of currents reflecting the states of the planetary gears of the speed reducers a to c. The reduction gear a is an example of the communication device 3 of the equipment 10A, the reduction gear b is an example of the communication device 3B of the equipment 10B, and the reduction gear c is an example of the communication device 3C of the equipment 10C. An example of a specific part of a planetary gear train. The measured values measured by the current measuring device 5A are described as measured values A. The diagnosis processing unit 23 extracts the peak of the frequency component value of frequency f2 from the analysis result of the measurement value A obtained by the analysis unit 22, and extracts the frequency of the frequency f2 from the analysis result of the measurement value B obtained by the analysis unit 22. As for the peak value of the component value, the peak value of the frequency component value of the frequency f2 is extracted from the analysis result of the measured value C obtained by the analysis unit 22 . The selected values are evaluation values representing the states of the planetary gears of the reduction gear a, the reduction gear b, and the reduction gear c, respectively. The diagnostic processing unit 23 creates the diagnostic graph shown in FIG. 2A using the extracted three frequency component values, and outputs it to the display unit 25 . A skilled technician will refer to the diagnostic chart of FIG. 2A and compare each with the frequency component values reflecting the state of the reducer of other equipment 10 . The magnitude of the frequency component value reflects the state of the planetary gears of the reducer a~c. Specifically, the worse the state, the larger the frequency component value. This is also the same for other machines and other specific parts. As a result of mutual comparison, the technician judged that the frequency component value of the reducer c whose frequency component value was clearly larger than the others had a high possibility of abnormality, and selected it as a candidate for recommended maintenance. Among them, in this example, one machine is selected as a candidate for maintenance recommendation, but for example, if the frequency component values of reducer a and c are clearly greater than the frequency component value of reducer b, reducer a and reducer c can also be selected As a recommended candidate for maintenance.

2B is a diagnostic graph showing frequency component values of current reflecting the state of the rotor bars of the motors a to b. The motor a is an example of the motor 2A of the device 10A, and the motor b is an example of the motor 2B of the device 10B. The diagnostic processing unit 23 extracts the peak value of the frequency component value of frequency f11 from the analysis result of the measurement value A obtained by the analysis unit 22, and extracts the frequency component of the frequency f11 from the analysis result of the measurement value B obtained by the analysis unit 22. The peak value of the value is prepared as a diagnostic graph in FIG. 2B and output to the display unit 25 . The technician refers to the diagnostic chart in FIG. 2B , and selects a motor a whose frequency component value is clearly larger than the others as a candidate for maintenance recommendation.

FIG. 2C is a diagnostic graph showing frequency component values of currents reflecting the state of the rotating shafts of the centrifuges a to g. The centrifuge a is an example of the loading device 4A of the facility 10A, and the centrifuge b is an example of the loading device 4B of the facility 10B. The same is true about centrifuges c~g. The diagnostic processing unit 23 extracts the peak value of the frequency component value of the frequency f3 from the analysis results of the measured values A to G obtained by the analyzing unit 22 , creates the diagnostic graph shown in FIG. 2C , and outputs it to the display unit 25 . The technician refers to the diagnostic chart in FIG. 2C , and selects the centrifuge d whose frequency component value is clearly larger than the others as a candidate for maintenance recommendation.

FIG. 2D is a diagnostic graph showing frequency component values (dB) of currents reflecting the states of the belts of fans a to c. The fan a is an example of the load device 4A of the equipment 10A, the belt a of the fan a refers to the belt part of the belt drive device, and is an example of a specific part of the transmission device 3A. The same applies to the belt b of the fan b and the belt c of the fan c. The diagnostic processing unit 23 extracts the peak value of the frequency component value of the frequency f21 from the analysis results of the measured values A to C obtained by the analyzing unit 22 , creates the diagnostic graph shown in FIG. 2C , and outputs it to the display unit 25 . Here, f21 is, for example, the frequency of rotation of the fans a to c. The rotation frequencies of the fans a to c are the same. Referring to FIG. 2D , compared with the frequency component values of other devices illustrated in FIGS. 2A to 2C , the overall values are higher. It is difficult to determine that the value of a specific frequency component is clearly greater than that of other devices through mutual comparison. As shown in FIG. 2D , in the case of a belt, due to the influence of the rotation of the fan, even in a normal state, the value of the primary component of the frequency reflecting the state of the belt appears high. Therefore, when evaluating the state of the belt, not only the peak value of the rotation frequency of the corresponding part, but also the peak value of its high harmonic components (n=1, 2, 3, ... times) are also evaluated. The diagnostic graph in FIG. 2D is a graph when the fundamental wave (n=1) is extracted. FIG. 2E shows the result obtained by the diagnostic processing unit 23 from the analysis result obtained by the analysis unit 22, assuming that the frequency of the side wave band of the power supply frequency is f21, and extracting the peak value of the frequency component value at a frequency twice the power supply frequency. Diagnostic chart. FIG. 2F shows a diagnostic graph created by the diagnostic processing unit 23 by extracting the peak value of the frequency component value at a frequency three times the power supply frequency from the analysis result obtained by the analyzing unit 22 . When diagnosing the state of the belt of the belt drive device, for example, a diagnostic chart is prepared for high harmonics of the 1st to nth order (preferably 1 to 10th order) and compared with each other to comprehensively evaluate the state of the belt. Although the illustration of the diagnostic chart for the 4th to nth order high harmonics is omitted, technicians make a comprehensive assessment based on the diagnostic charts of the 1st to nth order to identify the belt that has deteriorated. For this example, the technicians compared the diagnostic charts in Figure 2D to Figure 2F, because there is a significant difference in the frequency peaks of the three times of fan B (Figure 2F), so the state of the belt of fan B is the worst , the judgment must be maintained.

(action) The operation of the diagnostic system 100 will be described below. Fig. 3 is a flow chart showing an example of the operation of the diagnosis system of the embodiment. A user of the diagnosis system 100 sets information for specifying a diagnosis object in advance in the diagnosis device 20 . For example, the user sets the planetary gear of the reducer (transmitter 3), the rotor guide bar of the motor 2, the rotating shaft of the centrifuge (load device 4), the belt (transmitter) of the fan (load device 4) in the diagnosis device 20 part of the device 3), etc., as the information specifying the object of diagnosis. The memory unit 26 stores information representing these diagnostic objects. The memory unit 26 stores frequency information reflecting the state of the object of diagnosis (rotor bar frequency f11 of the motor 2, etc.).

First, the measurement result acquisition unit 21 acquires a measurement result from the current measurement device 5 included in each of the plurality of devices 10 of the same specification (step S1 ). For example, the measurement result acquisition unit 21 is connected to the current measuring device 5A of the equipment 10A and the current measuring device 5B of the equipment 10B through a connection line, and obtains digital current data from the equipment 10A and 10B at all times. The measurement result acquisition unit 21 records the acquired measurement results in the memory unit 26 for each device. Next, the analyzing unit 22 performs FFT analysis on the measurement result acquired in step S1 (step S2). For example, the analysis unit 22 reads out measurement results for a predetermined period of time for each of the devices 10A and 10B from the storage unit 26 , executes FFT analysis for each, and records the analysis results in the storage unit 26 for each device.

Next, the diagnosis processing unit 23 extracts the peak value of the frequency component value of the diagnosis object (step S3). The diagnostic processing unit 23 reads the FFT analysis result from the storage unit 26 for each device. The diagnosis processing unit 23 reads out the frequency information corresponding to the diagnosis object from the memory unit 26 . For example, the diagnostic processing part 23 uses the memory part 26 to read frequency f2 for the reducer, read frequency f11 for the rotor bar of the motor 2, read frequency f3 for the centrifuge, and read frequency f21 for the belt of the belt drive device. And its high harmonic (1~n times) and other information. Next, the diagnostic processing unit 23 refers to the data of the frequency f2 from among the FFT analysis results of the current measurement value of the device 10A, and extracts the peak value therefrom. This value corresponds to the frequency component value of the reducer a in the diagnostic chart of FIG. 2A . Similarly, the diagnostic processing unit 23 also extracts the peak value of the corresponding frequency component value for the reduction gear b of the facility 10B. If the object of diagnosis is the belt of the belt drive device, the diagnosis processing unit 23 refers to the data of the frequency f21 among the FFT analysis results of the current measurement value of the equipment 10A, and extracts the peak value therefrom. In addition, the diagnostic processing unit 23 refers to data of f21x2 times frequency, f21x3 times frequency, ..., f21x7 times frequency data from the FFT analysis result, and extracts the peak value of the frequency component value for each frequency of 2nd to 7th order. The diagnosis processing unit 23 also extracts the peak value of the frequency component value of the corresponding frequency for each diagnosis object for the remaining equipment 10B and the like.

Next, the diagnostic processing unit 23 creates a diagnostic graph using the peak values of the frequency component values extracted for each diagnostic object by device in step S3 (step S4 ). For example, the diagnostic processing unit 23 arranges peak values of frequency component values extracted for a certain diagnostic object for all devices to create a diagnostic graph. Next, the diagnostic processing unit 23 outputs the created diagnostic graph to the display unit 25 (step S5). The diagnostic graphs illustrated in FIGS. 2A to 2F are displayed on the display unit 25 . The diagnostic processing unit 23 can also output the created diagnostic chart to an electronic file, paper (printer), or other computers.

(Effect) As described above, with the diagnostic system 100 , the evaluation value indicating the state of the equipment (the motor 2 and the equipment connected to the motor 2 ) is analyzed using the current measurement value supplied to the motor 2 . This process is executed for a plurality of machines of the same specification, by comparing them with each other, attaching a sequence of states, and evaluating the states of the machines. This makes it possible to evaluate the state of the machine even if no threshold values have been set for the individual failure modes. Based on the evaluation results, it is possible to make prior arrangements for parts required for inspection or repair, or to create a maintenance plan by attaching maintenance priorities. Therefore, according to this embodiment, it is possible to save labor such as collecting abnormality data for threshold value setting, or setting threshold values in accordance with various specifications or operating environments. Take the belt as an example, if it is difficult to evaluate the state only by mutual judgment and evaluation of the peak value of the frequency component value corresponding to the machine, the diagnostic accuracy of the equipment state can be improved by evaluating the peak value of the high harmonic component value including the frequency .

In the above-mentioned embodiment, the diagnostic processing unit 23 outputs the diagnostic graph, but the diagnostic processing unit 23 may output the comparison result in another format. For example, the diagnosis processing unit 23 may also arrange the peak value of the frequency component value of each device in order of large and small to display the value of the peak value of the frequency component value of each device, and will display the value of the device and the next sequenced device The information of the difference of the peak values of the two is output to the display unit 25 . The diagnosis processing unit 23 may also calculate the difference between the maximum value and the minimum value of the peak value of the frequency component value of each device, and if the difference value exceeds a certain value, it is determined that a device with a deteriorated state exists among the evaluation objects, and the comparison result (for example, devices with large difference values and their evaluation values) are output to the display unit 25 .

In the above-mentioned embodiment, the equipment unit with the same specification is used to compare the equipment of other equipment. However, if one equipment has a plurality of equipment with the same specification, the frequency can also be extracted for these equipment. peak values of the components and compare them to each other. The diagnosis system using high-frequency components is not only suitable for belts, but also for the diagnosis of planetary gears of reducers, rotor bars of electric motors, and rotating shafts of centrifuges.

The diagnostic method of the present embodiment is applicable to the cutting of the rotor guide bar of the motor 2, the eccentricity of the rotating shaft of the motor 2, the abnormality of the bearing of the motor 2, the deviation of the joint core of the transmission device 3, the wear of the gear of the reducer, the wear of the belt, etc. Diagnosis of belt slack in the drive unit, shaft contact/bending/unbalance of the load-side machine, etc.

In the above-mentioned embodiment, the apparatuses of the same specification are compared with each other, but the comparison may also be made between machines of the same specification and the same operating conditions (surrounding environment, operating time, operating load, etc.). The same operating conditions mean that not only the operating conditions are completely the same, but also include the range where the evaluation values are considered to be the same when compared with each other, or the case where there is only a difference of a degree that does not fail to make a comparison. For example, if there are multiple equipment of the same specification in the same power plant (coal thermal power, natural gas thermal power, onshore windmill, offshore windmill, geothermal), the operating conditions (temperature, humidity, site conditions, etc.) are treated the same. Applying the diagnostic method of this embodiment to each device under the conditions shown above, by comparing the peak values of the frequency component values for devices of the same specification, it is possible to accurately evaluate the status of the device even if there is no threshold value. By comparing with each other, the sequence of equipment status is attached, so that the priority of maintenance can be attached when establishing the maintenance plan in the same power plant.

<Second Embodiment> A diagnosis system 100' according to a second embodiment will be described below with reference to Fig. 4 to Fig. 7 . In the first embodiment, the evaluation value (the peak value of the frequency component value) indicating the state of the machine is compared among the machines, thereby evaluating the state of the machine without a threshold value. On the other hand, the diagnostic device 20' in the second embodiment has a function of obtaining threshold values through learning.

(constitute) Fig. 4 is a block diagram showing an example of the diagnostic system of the second embodiment. Among the configurations of the second embodiment of the present disclosure, those having the same functions as those constituting the diagnostic system 100 of the first embodiment are denoted by the same reference numerals, and their descriptions are omitted. The diagnostic system 100' of the second embodiment includes: equipment 10A, 10B, ..., and a diagnostic device 20' to be diagnosed. The diagnostic device 20' includes a measurement result acquisition unit 21, an analysis unit 22, a diagnostic processing unit 23', an input unit 24, a display unit 25, a memory unit 26, and a learning unit 27.

The learning unit 27 learns learning materials with labels such as "abnormal", "caution", and "normal" by machine learning or the like for the peak value of the frequency component value extracted by the same method as that of the first embodiment, Threshold values (respectively, state judgment threshold values 1 and 2) are set for judging what value the peak value of the frequency component value is, which is regarded as an abnormal state or a state requiring attention. The diagnostic processing unit 23' is provided with a function of creating and displaying a diagnostic graph including the threshold value set by the learning unit 27, in addition to the function of the diagnostic processing unit 23 of the first embodiment. Alternatively, the diagnostic processing unit 23' can also determine the state of the machine according to the threshold value set by the learning unit 27.

(action) (Threshold setting by learning what to do) The learning process performed by the learning unit 27 will be described using FIG. 5 . Fig. 5 is a first flowchart showing an example of the operation of the diagnostic system of the second embodiment. First, evaluation by a technician etc. is implemented and a learning material is created (step S11). For example, a maintenance plan is created by the diagnostic method of the first embodiment. In this way, the maintenance contractor performs the maintenance of the planned equipment and creates a maintenance record. The results of various measurements or inspections performed on the machine are recorded in the maintenance record system. Next, a skilled technician who has the ability to evaluate the state of the machine evaluates the state of the machine on which maintenance has been performed, referring to the maintenance record. For example, a technician evaluates "abnormal", "caution", and "normal" with respect to the machine to be maintained or a specific part of the machine based on his or her own opinion. The user of the diagnosis system 100' receives the evaluation result of the state of the machine made by the technician, and associates the evaluation result with the peak value of the frequency component value of the machine to be maintained. In this way, learning materials are prepared.

The user inputs the learning data into the diagnosis device 20'. The input part 24 acquires the input learning material (step S12). The diagnostic processing unit 23' writes the learning data acquired by the input unit 24 into the memory unit 26 and stores it. When a certain amount of learning data is accumulated, the user performs an operation of learning to indicate a threshold value. The diagnostic processing unit 23' causes the learning unit 27 to learn learning materials in accordance with the user's instruction operation. The learning part 27 is to read out the learning data with the label of "abnormal", "attention" and "normal" by the memory part 26 to carry out mechanical learning, and set the state judgment threshold value 1 (whether it is abnormal or not) respectively. Judgment Threshold Value), State Judgment Threshold Value 2 (judgment threshold value of whether it is a state requiring attention) (step S13). The learning unit 27 stores the set threshold value in the memory unit 26 .

(diagnostic processing) Next, the diagnostic method of the second embodiment will be described using FIG. 6 and FIG. 7 . Fig. 6 is a second flowchart showing an example of the operation of the diagnostic system of the second embodiment. Fig. 7 is a diagram showing an example of a diagnostic chart of the second embodiment.

The same processing as that described using FIG. 3 will be briefly described. Based on the diagnosis results of the planetary gears of the reduction gears a to c in the past and the evaluation results based on the maintenance records, the state judgment threshold value 1 ( For example, a threshold value for judging whether it is abnormal) and a state judgment threshold value 2 (for example, a threshold value for judging whether it is a state requiring attention). First, the measurement result acquisition unit 21 acquires a measurement result from the current measurement device 5 included in each of the plurality of devices 10 having the same specification or the same specification and the same operating conditions (step S1 ). Next, the analyzing unit 22 performs FFT analysis on the measurement result acquired in step S1 (step S2). Next, the diagnosis processing unit 23' extracts the peak value of the frequency component value of the diagnosis object (step S3). For example, the diagnostic processing unit 23' extracts the peak values of the frequency components reflecting the states of the planetary gears of the reduction gears a to c, respectively, by processing similar to the processing described using FIG. 2A .

Next, the diagnostic processing unit 23' uses the peak value of the frequency component value extracted in step S3 to create a diagnostic graph with threshold values (step S4'). For example, the diagnostic processing unit 23' reads out the peak values of the frequency components of the speed reducers a~c from the memory part 26, and the state judgment threshold value 1 and the state judgment threshold value 2 set for the speed reducers a~c. , create a diagnostic graph showing the state judgment threshold value 1 and the state judgment threshold value 2. Next, the diagnostic processing unit 23' outputs the created diagnostic graph to the display unit 25 (step S5'). The diagnostic graph illustrated in FIG. 7 is displayed on the display unit 25 . TH1 in FIG. 7 is the state judgment threshold 1, and TH2 is the state judgment threshold 2. The technician looks at the diagnosis graph in FIG. 7 , compares the frequency component values with each other, and compares with the status judgment threshold value 1 and the status judgment threshold value 2 to select equipment as candidates for maintenance recommendation. For example, if it is the example of Fig. 7, the technical person selects the speed reducer c as Candidates for maintenance recommended machines.

Wherein, in step S4', the diagnostic processing unit 23' can also make judgments such as "normal", "abnormal" and "caution" based on the set threshold value. It is also possible to display the judgment result in step S5'. Using the learning data created based on the maintenance results of the machine being maintained according to the diagnosis chart in FIG. 7, for example, learning at the threshold value is repeated every time maintenance is performed, thereby improving the diagnostic accuracy. For example, even if it is determined that the frequency component value has exceeded the state judgment threshold value 1, if no abnormality is found according to the actual maintenance record, the value of the frequency component becomes "normal" or "caution". Labeled learning materials. By learning the learning data, the current state judgment threshold value 1 and state judgment threshold value 2 are adjusted.

(Effect) As described above, by the diagnostic system 100', by comparing the evaluation values (peak values of the frequency components) described in the first embodiment, the maintenance of the equipment judged to be in a bad state is carried out and is performed during the maintenance. Inspection results for determining an abnormal state, a normal state, etc. are stored in association with evaluation values based on current measurement values. Next, machine learning is performed based on the accumulated data to set the threshold value. In this way, threshold value determination is performed together with mutual evaluation results, and a maintenance plan can be created. Not only mutual comparison, but also machine learning using accumulated learning data for machines with the same specification can achieve the appropriateness of the threshold value and reduce false positive and false negative judgments when judging by mutual comparison.

Fig. 8 is a diagram showing an example of the hardware configuration of the diagnostic system of the embodiment. The computer 900 is equipped with: a CPU 901 , a main memory device 902 , an auxiliary memory device 903 , an input/output interface 904 , and a communication interface 905 . The above diagnostic devices 20, 20' are built in the computer 900. Next, the above-mentioned functions (the analyzing unit 22, the diagnostic processing units 23, 23', and the learning unit 27) are stored in the auxiliary memory device 903 in the form of programs. The CPU 901 reads the program from the auxiliary memory device 903 and expands it in the main memory device 902, and executes the above-mentioned processing according to the program. The CPU 901 secures a memory area in the main memory device 902 according to the program. According to the program, the CPU 901 secures a memory area for storing data being processed in the auxiliary memory device 903 . The above-mentioned diagnosis system may also be constituted by a system of plural computers such as a client terminal (not shown) or a diagnosis device 20 . In this case, some functions of the diagnostic device 20 (for example, the input unit 24 and the display unit 25 ) may be provided to the client terminal, and other functions may be provided to the diagnostic device 20 capable of communicating with the client terminal. In the case of the system as described above, each function in the diagnosis device 20 may be executed in accordance with a diagnosis request from a client terminal.

It is also possible to record the program for realizing all or part of the functions of the diagnostic device 20, 20' in a computer-readable recording medium, so that the computer system can read the program recorded in the recording medium and execute it. It is processed by each functional department. The term "computer system" as used herein refers to hardware such as an OS or peripheral devices. "Computer system" shall include a homepage providing environment (or display environment) if the WWW system is used. "Computer-readable recording media" refers to removable media such as CDs, DVDs, and USBs, and storage devices such as hard disks built into computer systems. If the program is distributed to the computer 900 through the communication line, the distributed computer 900 can also expand the program in the main memory device 902 and execute the above processing. The above-mentioned program may be used to realize a part of the above-mentioned function, or may be combined with a program already recorded in the computer system to realize the above-mentioned function.

As described above, some embodiments related to the present disclosure have been described, but all of these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in other various forms, and various omissions, substitutions, and changes can be made without departing from the gist of the invention. These embodiments and modifications thereof are included in the inventions described in the claims and their equivalent scopes as well as being included in the scope or gist of the invention.

＜Notes＞ The diagnostic system, diagnostic method, and program described in the embodiments are grasped as follows.

(1) The diagnostic systems 100 and 100' of the first aspect include: a measurement result acquisition unit 21 that acquires the measured value of the current supplied to each of the plurality of devices; frequency analysis; an extraction unit (diagnostic processing unit 23) that extracts frequency component values of predetermined frequencies (f1, f2, etc.) from the analysis results of the aforementioned frequency analysis as an evaluation value representing the state of the aforementioned equipment; and an output unit (diagnostic processing unit 23). The processing unit 23) outputs the comparison result of the evaluation value for each of the devices (the graphs in FIGS. 2A to 2F , information on devices whose difference between the maximum value and the minimum value of the evaluation value is greater than or equal to a predetermined value, etc.). By outputting the comparison result of the evaluation values of the same equipment, or outputting the evaluation values in a comparable manner, the states of the machines can be evaluated by mutual comparison without setting threshold values.

(2) The diagnostic system 100, 100' of the second aspect is the diagnostic system 100, 100' of (1), and the extraction unit extracts the high Harmonic component values (for example, 2 to n orders other than 1 order, preferably 1 to 10 orders) are used as the aforementioned evaluation values. By including high harmonic component values for mutual comparison, the diagnostic accuracy of equipment status can be improved.

(3) The diagnostic system 100, 100' of the third aspect is the diagnostic system 100, 100' of (1)~(2), and the aforementioned output unit is arranged in a comparable manner to the aforementioned evaluation extracted for each of the aforementioned devices The graphs (Figure 2A ~ Figure 2F) of the magnitude of the value are output. A technician who diagnoses the status of equipment by referring to the diagnostic chart can evaluate the status of each equipment by visually comparing it with others.

(4) The diagnostic systems 100 and 100' of the fourth aspect are the diagnostic systems 100 and 100' of (1) to (3), and the aforementioned plural devices are devices with the same specifications, or devices with the same specifications and with the same Equipment that is activated under certain operating conditions. By comparing equipment of the same specification, or equipment of the same specification and the same operating conditions, it is possible to perform highly reliable equipment status evaluation. For example, in the diagnosis of equipment driven by the motor 2 (including the motor 2), equipment of the same specification in the same power plant (coal thermal power, natural gas thermal power, land windmill, offshore windmill, geothermal) is diagnosed, and by its Compared with each other, the sequence of equipment status is attached, and the priority of equipment maintenance is attached, so that an efficient and effective maintenance plan can be made.

(5) The diagnostic system 100, 100' of the fifth aspect is the diagnostic system 100, 100' of (1)~(4), and additionally includes: a learning data acquisition unit (input unit 24), which acquires the aforementioned evaluation value And the evaluation result of the state of the aforementioned equipment shown by the evaluation value is formed as a set of learning materials; and the learning part 27 is to set a threshold value for judging the state of the aforementioned equipment by mechanical learning using the aforementioned learning materials The aforementioned output section is capable of outputting the aforementioned evaluation value of each of the aforementioned devices in comparison, and outputting the aforementioned threshold value in comparison with the aforementioned evaluation value. For the evaluation value, by attaching the evaluation result of the equipment state based on the inspection result when the inspection is actually carried out, etc., to create learning data, and making it learn the learning data, it is possible to set the state of the judgment equipment to be equivalent to The threshold value for any evaluation result (abnormal, noticeable, normal). By outputting the threshold value together with the evaluation value, technicians can evaluate the state of the equipment from two viewpoints of comparing the evaluation values with each other and comparing the evaluation value with the threshold value.

(6) The diagnostic system 100, 100' of the sixth aspect is the diagnostic system 100, 100' of (1)~(5), and the aforementioned equipment includes one or multiple machines (motor 2, transmission device 3, load device 4 ), the aforementioned extracting unit extracts the frequency component value of the aforementioned predetermined frequency depending on each aforementioned machine or the type of failure (rotor bar cut, eccentricity of the rotating shaft, etc.) that occurs in the aforementioned machine. This makes it possible to perform status diagnosis without thresholds for various failure modes of not only the entire equipment, but also individual equipment. For example, in the diagnosis of equipment driven by the motor 2, the rotor bar cut of the motor 2, the eccentricity of the rotating shaft of the motor 2, the abnormality of the bearing of the motor 2, Displacement of the joint core of the communication device 3, wear of the gear of the reducer, slack of the belt of the belt drive device, shaft contact/bending/unbalance of the load device 4 such as a fan, etc.

(7) The diagnostic system of the seventh aspect is a diagnostic system composed of a terminal device and a diagnostic device capable of communicating with the terminal device. The terminal device is equipped with request means for requesting the status of each of the plurality of devices. diagnosis; and an output unit that outputs the evaluation value of each of the aforementioned devices extracted by the extraction unit of the aforementioned diagnostic device for comparison. The aforementioned diagnostic device is equipped with: a measurement result acquisition unit that uses the aforementioned terminal The request of the device acquires the measured value of the current supplied to each of the plurality of devices; the analyzing unit performs frequency analysis on the measured value; and the extracting unit extracts a predetermined frequency from the analysis result of the frequency analysis The frequency component value serves as an evaluation value representing the state of the aforementioned device.

(8) The diagnostic method according to the eighth aspect includes: a step of acquiring measured values of currents supplied to each of the plurality of devices; a step of performing frequency analysis on the measured values; and extracting a predetermined frequency from the analysis results of the aforementioned frequency analysis. a step of using the frequency component value of the frequency component as an evaluation value representing the state of the aforementioned device; and a step of outputting a comparison result of the aforementioned evaluated value extracted for each of the aforementioned devices. This makes it possible to evaluate the status of the plant even if no threshold values have been set.

(9) The diagnostic method of the ninth aspect is a diagnostic method performed by a terminal device and a diagnostic device capable of communicating with the terminal device, and the terminal device executes: requesting a state of each of a plurality of devices diagnosis; and an output step, which is to output the evaluation value of each of the aforementioned equipment extracted by the extraction step of the aforementioned diagnostic device for comparison, and the aforementioned diagnostic device executes: a measurement result obtaining step, which is through the aforementioned terminal device According to the request, the measured value of the current supplied to each of the plurality of devices is obtained; the analysis step is to perform frequency analysis on the above-mentioned measured value; and the extraction step is to extract the frequency of a predetermined frequency from the analysis result of the above-mentioned frequency analysis The component values serve as evaluation values representing the state of the aforementioned equipment.

(10) The program of the tenth aspect causes the computer 900 to execute: the step of acquiring the measured value of the current supplied to each of the plurality of devices; the step of performing frequency analysis on the measured value; and extracting the plan from the analysis result of the frequency analysis. a step of using the frequency component value of the frequency of the frequency as an evaluation value representing the state of the aforementioned device; and a step of outputting a comparison result of the aforementioned evaluated value extracted for each of the aforementioned devices. [industrial availability]

With the above-mentioned diagnostic system, diagnostic method, and program, it is possible to appropriately diagnose the diagnostic object.

100,100': Diagnostic system 1,1A,1B: Power source 2, 2A, 2B: motor 3,3A,3B: Communication device 4, 4A, 4B: load device 5, 5A, 5B: current measuring device 6A: Shaft 7A: Shaft 8A: wire 10, 10A, 10B: Equipment 20,20': Diagnostic device 21: Measurement result acquisition department 22: Analysis Department 23,23': Diagnosis and processing department 24: Input part 25: Display part 26: Memory Department 27: Learning Department 900: computer 901:CPU 902: main memory device 903: Auxiliary memory device 904: I/O interface 905: communication interface

[ Fig. 1 ] is a block diagram showing an example of the diagnostic system of the first embodiment. [FIG. 2A] is the first diagram showing an example of the diagnostic chart of the first embodiment. [ Fig. 2B ] is a second diagram showing an example of the diagnostic chart of the first embodiment. [FIG. 2C] is a third diagram showing an example of the diagnostic chart of the first embodiment. [FIG. 2D] is a fourth diagram showing an example of the diagnostic chart of the first embodiment. [FIG. 2E] is a fifth diagram showing an example of the diagnostic chart of the first embodiment. [FIG. 2F] is a sixth diagram showing an example of the diagnostic chart of the first embodiment. [ Fig. 3 ] is a flow chart showing an example of the operation of the diagnostic system of the first embodiment. [ Fig. 4 ] is a block diagram showing an example of the diagnostic system of the second embodiment. [ Fig. 5 ] is a first flowchart showing an example of the operation of the diagnostic system of the second embodiment. [ Fig. 6 ] is a second flow chart showing an example of the operation of the diagnostic system of the second embodiment. [ Fig. 7 ] is a diagram showing an example of a diagnostic chart of the second embodiment. [ Fig. 8 ] is a diagram showing an example of the hardware configuration of the diagnostic system of the embodiment.

100:Diagnostic system

1A: Power source

2A: Motor

3A: Communication device

4A: Loading device

5A: current measuring device

6A: Shaft

7A: Shaft

8A: wire

10A, 10B: equipment

20:Diagnostic device

21: Measurement result acquisition department

22: Analysis department

23:Diagnosis and Treatment Department

24: Input part

25: Display part

26: Memory Department

Claims (10)

A diagnostic system comprising: a measurement result acquisition unit that acquires the measured value of the current supplied to each of the plurality of devices; an analysis unit that performs frequency analysis on the aforementioned measured values; an extraction unit that extracts a frequency component value of a predetermined frequency from an analysis result of the frequency analysis as an evaluation value representing a state of the device; and An output unit that outputs the aforementioned evaluation value of each of the aforementioned devices for comparison. The diagnostic system according to claim 1, wherein the extracting unit extracts, as the evaluation value, a high harmonic component value related to the predetermined frequency in addition to a frequency component value of the predetermined frequency. The diagnostic system according to claim 1 or claim 2, wherein the output unit outputs information for comparing the evaluation values extracted for each of the devices. The diagnostic system according to any one of claim 1 to claim 3, wherein the plurality of devices are devices having the same specifications, or devices having the same specifications and activated under the same operating conditions. The diagnostic system according to any one of claim 1 to claim 4, which additionally has: The learning material acquisition unit, which acquires learning materials that form a set of the aforementioned evaluation value and the evaluation result of the status of the aforementioned equipment indicated by the evaluation value; and The learning unit sets the threshold value for judging the state of the aforementioned equipment through mechanical learning using the aforementioned learning materials, The aforementioned output section is capable of outputting the aforementioned evaluation value of each of the aforementioned devices in comparison, and outputting the aforementioned threshold value in comparison with the aforementioned evaluation value. The diagnostic system according to any one of claim 1 to claim 5, wherein the aforementioned equipment includes one or more machines, The extracting unit extracts a frequency component value of the predetermined frequency for each of the equipment or a type of failure occurring in the equipment. A diagnostic system comprising a terminal device and a diagnostic device capable of communicating with the terminal device, The aforementioned terminal device is equipped with: Requiring means that require diagnosis of the status of each of the plurality of devices; and an output unit that outputs an evaluation value of each of the aforementioned devices extracted by the extraction unit of the aforementioned diagnostic device for comparison, The aforementioned diagnostic device is equipped with: a measurement result acquisition unit that acquires the measured value of the current supplied to each of the plurality of devices in response to a request from the terminal device; an analysis unit that performs frequency analysis on the aforementioned measured values; and The extraction unit extracts a frequency component value of a predetermined frequency from an analysis result of the frequency analysis as an evaluation value indicating a state of the device. A diagnostic method comprising: a step of acquiring a measured value of current supplied to each of the plurality of devices; A step of performing frequency analysis on the aforementioned measured values; a step of extracting a frequency component value of a predetermined frequency from an analysis result of the aforementioned frequency analysis as an evaluation value representing the state of the aforementioned facility; and A step of outputting the aforementioned evaluation values extracted for each of the aforementioned devices for comparison. A diagnostic method, which is a diagnostic method performed by a terminal device and a diagnostic device capable of communicating with the terminal device, The aforementioned terminal device executes: a request step that requires a diagnosis of the status of each of the plurality of devices; and an outputting step of outputting the evaluation value of each of the aforementioned devices extracted by the extracting step of the aforementioned diagnostic means for comparison, The aforementioned diagnostic means perform: a measurement result obtaining step of obtaining measured values of currents supplied to each of the plurality of devices upon request from the terminal device; an analysis step of performing frequency analysis on the aforementioned measured values; and The extracting step is to extract a frequency component value of a predetermined frequency from the analysis result of the frequency analysis as an evaluation value indicating the state of the device. A program that causes a computer to execute: a step of acquiring a measured value of current supplied to each of the plurality of devices; A step of performing frequency analysis on the aforementioned measured values; a step of extracting a frequency component value of a predetermined frequency from an analysis result of the aforementioned frequency analysis as an evaluation value representing the state of the aforementioned facility; and A step of outputting the aforementioned evaluation values extracted for each of the aforementioned devices for comparison.

Images