JP2005309724A - Abnormality diagnosis system and abnormality diagnosis method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an abnormal state diagnostic system and an abnormal state diagnostic method for various kinds of machines in which a database of the data of operation states that are not abnormal can be utilized for uses other than failure predictions. <P>SOLUTION: A control means 4 for monitoring and controlling a machine 2 to be diagnosed has a database 7 and a display means 8, and the database 7 stores standard values of operation state data of the machine 2 to be diagnosed. The system is so composed that in the abnormal state, the operation state data of the machine 2 to be diagnosed in an abnormal state and the corresponding standard values of the operation state data are displayed in the display means 8. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a technique for detecting and diagnosing an abnormality in an air conditioner (for example, a gas heat pump) or a generator (including a cogeneration system).

  As a technology for detecting and diagnosing abnormalities in air conditioners, for example, in various air conditioners installed in large numbers, standard operating state data (non-abnormal conditions) for each air conditioner is stored in a database. Compare the operation data during operation of the air conditioner with the standard condition data recorded in the database under the same conditions, and predict the occurrence of a failure when the difference between the operation data and the standard condition data exceeds the threshold However, it already exists (for example, Patent Document 1).

However, although the related art has a database of operation state data in a standard state, the database is utilized only for a very limited purpose of “prediction of failure”.
Therefore, there is a demand for utilizing the database (operation state database in the standard state) for purposes other than prediction of failure. However, there is no conventional technique that can meet such a demand.
JP 2001-91121 A

  The present invention has been proposed in view of the above-described problems of the prior art, and an abnormality diagnosis system for various machines that can utilize a database of operation state data in a non-abnormal state (standard state) for purposes other than failure prediction. The purpose is to provide an abnormality diagnosis method.

  In the abnormality diagnosis system of the present invention, a control means (for example, a remote monitoring center 4) for monitoring and controlling a machine to be diagnosed (for example, an air conditioner 2, a generator) has a database (7) and a display means (for example, a display 8). The database (7) stores the standard value of the operation state data of the diagnosis target machine (2) (operation state data of the diagnosis target device in a state that is not abnormal). The operation state data of the diagnosis target machine (2) and the standard value of the corresponding operation state data are configured to be displayed on the display means (8) (Claim 1).

  In this specification, the term “at the time of abnormality” means not only when an abnormality is detected on the diagnosis target device (2) side (for example, by an automatic control mechanism) and an alarm signal is output, but also a complaint from the user. It is used in a concept that includes the case where a report (so-called “claim”) is sent.

  Here, the control means (for example, the remote monitoring center 4) includes classification means (load state classification unit 6A), and the classification means stores the operation state of the diagnosis target machine (2) in the database (7). When storing the standard value of the data, the operation state data is classified and averaged for each load condition, and the control means (for example, the remote monitoring center 4) is a diagnosis target at the time of abnormality It is preferable that a standard value of the same load condition as the operation state data of the machine (2) is extracted from the database (7) and displayed on the display means (8) (Claim 2).

  The machine to be diagnosed (2) has a monitoring means (remote monitoring adapter 3) for monitoring its operating state, and the monitoring means (remote monitoring adapter 3) is an operation state data of the machine to be diagnosed (2). From the measured value, a representative value in a predetermined period (N) (for example, operation state data at the time when the load of the air conditioner (2) becomes highest in the period N) is selected, and the control means (for example, a remote monitoring center) 4), the classification means (load state classification unit 6A) classifies only the representative values selected by the monitoring means (3) for each load condition and averages them. (Claim 3).

  The abnormality diagnosis method of the present invention includes a step (S4) of obtaining a standard value (operation state data of a diagnosis target device in a state that is not abnormal) of operation state data of a diagnosis target machine (for example, an air conditioner 2, a generator); A step of classifying the acquired standard values for each load condition by the classifying means (load state classification unit 6A) and averaging them to construct a database of the standard values (S8), and at the time of abnormality, diagnosis at the time of the abnormality A step (S24) of extracting a standard value of the same load condition as the operation state data of the target machine from the database and a standard value of the same load condition as the operation state data of the diagnosis target machine at the time of abnormality are displayed on the display means. (S25). (Claim 4).

  In the step of constructing the database (S8), the monitoring means (remote monitoring adapter 3) provided in the diagnosis target machine (2) is used for a predetermined period (from the measured value of the operation state data of the diagnosis target machine (2) ( N) representative values (for example, operation state data at the time when the load of the air conditioner (2) becomes the highest during the period N) are selected, and the diagnosis target machines (for example, the air conditioner 2 and the generator) are monitored. Only the representative value transmitted to the control means (for example, the remote monitoring center 4) to be controlled and selected by the monitoring means (3) is classified for each load condition by the classification means (load state classification unit 6A). It is preferable to average (Claim 5).

  In the abnormality diagnosis system of the present invention, it is preferable that the control means (for example, the remote monitoring center 4) and / or the monitoring means (remote monitoring adapter 3) includes a computer. Here, the term “computer” is used in the present specification to widely encompass devices having information processing capabilities.

  The present invention can be applied not only to a control mechanism attached to an air conditioner but also to remote monitoring means that are informationally connected by an information network or the like.

According to the present invention having the above-described configuration, when an abnormality occurs, the standard value is displayed on the display means (for example, the display 8) together with the data at the time of the abnormality.
For this reason, even if you are not familiar with the operating data (standard value) of an air conditioner without any abnormalities, even if you cannot make a diagnosis by looking at only the operating data at the time of abnormality, you can display the standard values on the screen. It is possible to easily diagnose (determine) what is abnormal in the operation data when an abnormality occurs.

  Even a person who can diagnose the cause of a failure by looking only at the operation data at the time of occurrence of an abnormality may make a diagnosis error if the cause of the failure is confusing. As a countermeasure, the accuracy of diagnosis can be improved by displaying standard values on the screen and grasping the characteristics of the machine at the beginning of installation.

  That is, the remote monitoring center (4) or the person in charge of the maintenance company contracted with the remote monitoring center (4) has these two operating state data (operating state data when an abnormality occurs, operating state data when no abnormality occurs). By comparing these, it is possible to diagnose (determine) what kind of modulation the air conditioner has caused by this abnormality.

  Even if the air conditioner (2) does not detect any abnormality, if the user feels dissatisfied with the air conditioning condition and makes a complaint to the maintenance company, the standard value corresponding to the load condition at the time of the complaint is stored in the database. What kind of modulation the air conditioner is causing this claim by extracting from the above and displaying it on a personal computer screen, etc., which is a terminal of the remote monitoring center (4), and comparing it with the operating state at the time of occurrence of an abnormality Can also be diagnosed.

  In the prior art (Japanese Patent Laid-Open No. 2001-91121), the standard value database is used only for predicting an abnormality. In the present invention, even after an abnormality occurs, the cause of the abnormality is diagnosed. To do this, a standard value database is used. In other words, according to the present invention, the database in the standard state can be used for the purpose of abnormality diagnosis.

  The standard value database is constructed with the operation state data from the new product before the elapse of the predetermined period L. By doing so, the influence of deterioration over time is prevented from being included in the standard value database.

  Furthermore, according to the present invention, it is possible to find standard operation state data for each air conditioner for various air conditioners installed in large numbers. At the same time, the operation data in the standard state for each air conditioner can be used for diagnosis of the cause of abnormality when an abnormality occurs in each air conditioner. Here, since the operation state data in the standard state is not uniform and corresponds to the installation environment of each air conditioner, the accuracy of abnormality cause diagnosis can be improved.

Embodiments of the present invention will be described below with reference to the accompanying drawings.
In FIG. 1, an abnormality diagnosis apparatus generally indicated by reference numeral 1 includes an air conditioner 2, operation state data of a standard state of the air conditioner 2, and operation state data at the time of abnormality of the air conditioner 2 for a predetermined period (period N ) The remote monitoring adapter 3 and the computer 4 are stored.
The standard operation state data stored in the remote monitoring adapter 3 and the operation state data when the air conditioner 2 is abnormal are transmitted through communication lines L1 and L2 (standard operation state data is transmitted). Communication line), communication lines L11 and L12 (communication lines through which abnormal operation state data is transmitted) and the network 10 are sent to the computer 4 (control means or remote monitoring center).

Here, as the network 10, the Internet, a local area network (LAN), a dedicated line system, a system using a telephone line, and other information networks can be widely used.
Further, as described above, the computer 4 can be configured by a device having information processing capability such as a server machine, a PC, or a workstation.

The computer 4 is configured to determine whether or not the air conditioner 2 is out of order based on the operation state data in the standard state and the operation state data when the air conditioner 2 is abnormal.
The computer 4 is connected to a display means (display) 8, and the display means 8 can simultaneously display the operation state data in the standard state and the operation state data at the time of abnormality.

  The computer 4 includes a timer 5 for measuring the period L, a load condition classification unit 6A, a load condition classification unit 6B, and a storage unit (database, hereinafter referred to as a database). ing.

The remote monitoring adapter 3 is provided with a period N measuring timer 31. Here, the remote monitoring adapter 3 selects, for example, the operation state data at the time when the load of the air conditioner 2 becomes the highest in the period N as the representative value.
Then, the selected representative value is transmitted to the computer 4 side.
In other words, the remote monitoring adapter 3 temporarily stores various operation state data measured by various sensors (not shown) provided in the air conditioner 2, and performs predetermined data every time period N elapses. Only data selected according to the selection rule is sent to the computer 4 side.

More specifically, when the standard value database is constructed, the operation state data in the standard state is transmitted from the remote monitoring adapter 3 via the line L1, the network 10, and the line L2, and the classification of the load conditions is performed. Received by the unit 6A.
The load condition classification unit 6A classifies representative values (standard operation state data) selected on the remote monitoring adapter 3 side of the air conditioner 2 according to load conditions.
Then, each load condition is averaged (classified representative values) to create a matrix as shown in FIG.
That is, the driving state data in the standard state is classified for each load condition, and the averaged numerical values are registered in the database 7, and the standard value database is constructed by the numerical values.

On the other hand, the operation state data at the time of abnormality is transmitted from the remote monitoring adapter 3 via the line L11, the network 10, and the line L12, and is received by the load condition classification unit 6B.
The operating condition data at the time of abnormality received by the load condition classification unit 6B is classified by the load condition, and the result is collated with the database 7 and transmitted to the comparison display 5, and the standard screen is displayed on the monitor screen. Are displayed together with operation state data under similar load conditions.
Although the load condition classifying unit 6A and the load condition classifying unit 6B are shown as separate units in FIG. 1, the same unit (single load condition classifying unit) is also used. Is possible.

Here, the operation state data is classified and stored for each air conditioner such as a gas heat pump in the computer 4, but for a predetermined period from the beginning of remote monitoring (for example, immediately after the delivery and installation of the air conditioner). Operation state data in a standard state (for example, for 12 months) is averaged for each load condition as shown in a matrix shown in FIG. 2, and this is used as standard value data.
For example, in the matrix of FIG. 2, the outside air temperature is assigned to a temperature range of less than 0 ° C. to 45 ° C. or more every 5 degrees in a temperature range of 10 blocks, and the operation rate of the indoor unit is further increased from 0 to 50 in the temperature range assigned to that 10. %, 50 to 100%, and divided into 20 patterns in total, and the measured case is classified into any of the above 20 patterns.

In FIG. 2, the “indoor unit operation rate” is represented by a numerical value obtained by dividing “total amount of indoor units during thermo-ON in the air conditioner” by “total capacity of indoor units of the air conditioner”.
(It is assumed that there are multiple indoor units. However, even if there is only one indoor unit, it can be divided into an indoor unit operation rate of 0% and an indoor unit operation rate of 100%.)
Here, for example, in the case of cooling, when the room temperature becomes higher than the set temperature by a predetermined temperature or more, the cooling device operates, but the operation start is “thermo ON”. On the other hand, as a result of the cooling operation, when the room temperature falls within the predetermined range of the set temperature, the operation of the air conditioner is temporarily stopped. Such operation stop is “thermo OFF”.

  In the illustrated embodiment, for example, the operation state data when the load on the air conditioner becomes the highest is used as the representative value, but the way of taking the representative value is not limited to this.

  As a transmission method to the computer 4, the Internet is shown as the information network N in the illustrated example. However, this is merely an example, and as described above, a dedicated line, a telephone line, a LAN, and other various information transmission systems can be used.

  The period L measuring timer of the computer 4 takes the period L (for example, 12 months) as the period for creating the standard value database, and after the first operation is started after the air conditioner 2 is delivered and installed, the period L ( A standard value database is created based on the operation state data within 12 months).

  Next, with reference to FIG. 3, control for creating a standard value (standard operating state data) database will be described.

  First, in step S1, the computer 4 determines whether or not to start using the newly delivered air conditioner. If the specification is to be started (YES in step S1), the process proceeds to step S2 and must be started. (NO in step S1), the loop of step S1 is repeated.

  In step S2, a period L measurement timer (a timer for obtaining standard value data, a timer for measuring 12 months from the installation) 5 is started, and in a next step S3, a period N measurement timer (for each predetermined period) is started. The timer for timekeeping (31) for acquiring operating state data is started.

  In the next step S4, various operating parameters are measured by a measuring means (not shown), and the measured values are temporarily stored in the remote monitoring adapter 3 on the air conditioner (gas engine heat pump) 2 side.

  In step S6, the computer 4 determines whether or not the period N has elapsed. If the period N has elapsed (YES in step S6), the computer 4 proceeds to the next step S7. On the other hand, if the period N has not elapsed (NO in step S6), the process returns to step S4 to repeat step S4 and subsequent steps.

  In step S7, the measured value (representative value) selected according to a predetermined rule is transmitted to the computer 4 via the line L1, the network 10, and the line L2, and the process proceeds to step S8 where the load condition classification unit 6A selects it. The classified representative values are classified, and the classified representative values are averaged and registered in the database 7.

In the next step S9, it is determined from the measurement result of the period L measuring timer 5 whether or not the period L has elapsed. If the period L has elapsed (YES in step S9), the process proceeds to step S10.
On the other hand, if the period L has not elapsed (NO in step S9), the period N measurement timer 31 is reset in step S12, the process returns to step S4, and step S4 and subsequent steps are repeated again.

  In step S10, the standard value database is determined, and the period L measurement timer 5 is stopped (OFF). Thereafter, the representative value of the driving state data is not selected, the driving state database is not updated (step S11), and the control is terminated.

After the standard value database is constructed, the operation state data does not flow through the line L1, the network 10, and the line L2.
The system through which the operation state data thereafter flows is the line L11, the network 10, and the line L12.
Therefore, the operation state data when an abnormality occurs flows through the system of the line L11, the network 10, and the line L12 in FIG.

As described above, the abnormal data is determined by the load condition classification unit 6B as to which of the load conditions shown in FIG.
The operating state data at the time of abnormality is displayed on the display 8 as it is, but the standard value under the same load condition is also displayed.

  Next, a control method (abnormality diagnosis method) when an abnormality occurs in the air conditioner will be described with reference to FIG.

  First, in step S21, the computer 4 checks whether or not an abnormality has occurred. If an abnormality has occurred (YES in step S21), the process proceeds to step S2. On the other hand, if no abnormality has occurred (NO in step S21), the loop in step S21 is repeated until it occurs.

  In step S22, the monitoring adapter 3 transmits the operation data at the time of abnormality to the computer 4 side. In the next step S23, the computer 4 that has received the operation data at the time of abnormality classifies the data for each load condition in the load condition classification unit 6B.

  In the next step S24, the standard value of the corresponding load condition is called from the standard value database 7 on the screen of the display 5, and in step S25, the abnormal operation data and the standard value are displayed side by side on the display 5 screen. To do.

  FIG. 5 shows an example of abnormal operation data and standard values displayed side by side on the screen of the display 5 in step S25.

In the example shown in FIG. 5, it can be seen that the pressure on the high pressure side of the refrigerant (2.55 MPa) is particularly increased compared to the pressure on the high pressure side of the standard refrigerant (1.95 MPa) when an abnormality occurs.
As a cause of the abnormality on the refrigerant high-pressure side, a failure factor that is likely to be suspected is insufficient heat exchange of the outdoor air heat exchanger. That is, the data at the time of occurrence of abnormality illustrated in FIG. 5 is lower in engine speed and throttle opening than the standard time data, and has a high refrigerant pressure, a low refrigerant pressure, a compressor discharge temperature, a compressor suction temperature, Since the heat exchanger outlet temperature is high, at first glance, the cause of the refrigerant high pressure abnormality seems to be insufficient heat exchange of the outdoor air heat exchanger.

Here, because the outdoor heat exchanger of the gas heat pump is integrated with the cooling water radiator, when the outdoor air heat exchanger is short of heat exchange, the heat dissipation amount of the cooling water is also insufficient. The cooling water temperature should also increase.
Although the cooling water temperature of 78 ° C. at the time of occurrence of an abnormality in FIG. 5 is never a low temperature, in the case of the example shown in FIG. 5, the standard cooling water temperature is 82 ° C., which is even higher.
From this, it can be diagnosed that the true cause of failure is other than insufficient heat exchange of the outdoor air heat exchanger.

Further, in the case of FIG. 5, the opening degree of the bypass valve that is normally opened to reduce the refrigerant high pressure is lower than the standard value when an abnormality occurs.
From this, it is considered that the true cause of the failure is a poor opening degree of the bypass valve.

  Based on the above-described diagnosis result, in step S26, the true cause of the abnormality is estimated, and the cause of the failure can be specified by checking the estimation and the relevant part of the device (around the bypass valve). Control ends when the cause of the failure is identified.

Here, the following two points can be cited as the merits of displaying the standard value data attached to the abnormal operation state data.
(1) Because the operation data of the air conditioner without any abnormality is not well known, even if the operation data at the time of abnormality cannot be diagnosed, the standard value is displayed on the screen and the data at the time of abnormality is displayed. With this, it is possible to easily determine where the operation is abnormal when an abnormality occurs.
(2) Even those who can diagnose the cause of a failure by looking only at the operation data at the time of occurrence of an abnormality may make a mistake in the diagnosis if the cause of the failure is confusing. As a countermeasure, the accuracy of diagnosis can be improved by displaying standard values on the screen and grasping the characteristics of the machine at the beginning of installation.

  The maintenance person in charge of the owner of the remote monitoring center (computer) 4 or the person in charge of the maintenance company who has contracted with the owner of the remote monitoring center (computer) 4 will receive these two operating state data (the operating state at the time of occurrence of an abnormality). By comparing the data and the operation state data when there is no abnormality, it is possible to diagnose (determine) what kind of modulation the air conditioner has caused by this abnormality.

  Even when the air conditioner 2 does not detect any abnormality, if the user feels dissatisfied with the air conditioning condition and makes a complaint to the maintenance company, the standard value corresponding to the load condition at the time of the complaint is stored in the database 7. By extracting and displaying on the display 8 of the remote monitoring center (computer) 4 and comparing with the operation state at the time of occurrence of abnormality, it is also possible to diagnose what kind of modulation the air conditioner is causing. I can do it.

The illustrated embodiment is merely an example, and is not intended to limit the technical scope of the present invention.
For example, in the illustrated embodiment, a case where the present invention is applied to an air conditioner is shown, but the present invention is applicable not only to an air conditioner but also to a generator (including a cogeneration system).
In the illustrated embodiment, the load conditions are classified into 20 patterns (see FIG. 2), but the classification of the load conditions is not limited to such 20 types of matrices.

The block diagram which shows the structure of embodiment. The matrix which shows the example of classification of load conditions. The flowchart which showed the control method which creates a standard value database. The flowchart which showed the control method when abnormality arises in an air conditioner. A comparison table showing comparison between standard value data displayed on the display and data at the time of abnormality.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Abnormality diagnosis apparatus 2 ... Air conditioner 3 ... Remote monitoring adapter 4 ... Remote monitoring computer 5 ... Timer 6A, 6B for period L measurement ... Load condition classification | category part 7 ... -Database registration unit 8 ... display 10 ... network

Claims (5)

  The control means for monitoring and controlling the machine to be diagnosed has a database and a display means, and the database stores the standard values of the operation state data of the machine to be diagnosed. An abnormality diagnosis system, characterized in that the operation state data and the standard value of the corresponding operation state data are displayed on the display means.   The control unit includes a classification unit, and the classification unit stores the standard value of the operation state data of the diagnosis target machine in the database so that the operation state data is classified and averaged for each load condition. The control means is configured such that a standard value of the same load condition as the operation state data of the diagnosis target machine at the time of abnormality is extracted from the database and displayed on the display means. Abnormality diagnosis system.   The diagnosis target machine has monitoring means for monitoring its operating state. The monitoring means selects a representative value in a predetermined period from the measured value of the operation state data of the diagnosis target machine and transmits it to the control means. The abnormality diagnosis system according to claim 2, wherein the classification unit is configured to classify and average only representative values selected by the monitoring unit for each load condition.   A step of acquiring a standard value of the operation state data of the machine to be diagnosed, a step of classifying the acquired standard value for each load condition by the classifying means and averaging the data, and constructing a database of the standard value; The display means includes a step of extracting a standard value of the same load condition as the operation state data of the machine to be diagnosed at the time of abnormality from the database and a standard value of the load condition identical to the operation state data of the machine to be diagnosed at the time of abnormality. A method for diagnosing an abnormality characterized by comprising:   In the step of constructing the database, control means for monitoring and controlling the diagnosis target machine by selecting a representative value in a predetermined period from the measured value of the operation state data of the diagnosis target machine by the monitoring means provided in the diagnosis target machine 2. The abnormality diagnosis method according to claim 1, wherein only the representative value transmitted to and selected by the monitoring unit is classified and averaged for each load condition by the classification unit.

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