Diagnostic processing device, diagnostic system, and diagnostic method for fluid machine

Abstract

To extract inefficiently operating or deteriorated equipment from acquired operation data.SOLUTION: A method for diagnosing the setting of a fluid machine based on information detected by a sensor mounted on the fluid machine, includes: inputting at least one of a load factor, a set pressure and a discharge pressure, an ambient temperature, a discharge temperature, the number of alarms issued, and an operating time of the fluid machine as analysis information; determining whether the setting of the fluid machine have potential for improvement based on the analysis information; counting the number of days which has been determined that there is potential for improvement over a predetermined period; when the count exceeds a threshold, creating a proposed improvement setting for the fluid machine based on the analysis information; and providing the proposed improvement setting to a user of the fluid machine.SELECTED DRAWING: Figure 9

Description

[Technical Field]

[0001] The present invention relates to, for example, a diagnostic processing device, a diagnostic system, and a diagnostic method for fluid machinery. [Background technology]

[0002] In recent years, with the progress of global warming, efforts have been made to realize a decarbonized society that will achieve virtually zero CO2 emissions. Remote monitoring systems using the Internet of Things (IoT) cloud, which constantly monitors industrial equipment, are becoming increasingly popular, allowing services to remotely visualize the operating status of equipment and the occurrence of abnormalities. Today, in addition to these visualization services, there is a need to identify devices in order to propose configuration changes and other measures.

[0003] Conventionally, a known technology for identifying devices that require changes to the settings of monitoring devices is that disclosed in Patent Document 1. Patent Document 1 discloses an invention related to the diagnosis (monitoring) of a refrigeration system, which secures a heat source necessary for hot water supply operation of a supercooling water heater unit or the like even when the load on the refrigeration unit is low, such as in winter, thereby ensuring a sufficient amount of hot water in the hot water storage tank and reducing the frequency of starting and stopping the refrigeration unit and the supercooling water heater unit, thereby improving the reliability of the equipment. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-033432 Summary of the Invention [Problem to be solved by the invention]

[0005] Patent Document 1 discloses a technology that improves reliability by counting the number of times a water heater is turned on and off, detecting when the number exceeds a certain number within a certain period of time, and switching to "hot water priority mode." However, it does not describe a method for identifying the temperature of the monitored object. To achieve CO2 reductions from industrial equipment, a method is needed that not only monitors the on / off of the equipment, but also considers the temperature aspect when identifying the equipment.

[0006] An object of the present invention is to provide a diagnostic processing device, a diagnostic system, and a diagnostic method for fluid machinery that are capable of extracting candidate equipment that should be operated under different conditions (conditions, environments) from the current status from the operation data of the equipment. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems and achieve the above-mentioned objects, one embodiment of the present invention is a diagnostic processing device that is connected to one or more fluid machines via a network and diagnoses the operating status of each of the fluid machines, characterized in that it comprises: an input unit that inputs data indicating the operating status from each of the fluid machines; and a diagnostic unit that performs an operation improvement diagnosis for each of the fluid machines based on the data input by the input unit and creates an operation improvement plan based on the results of the improvement diagnosis.

[0008] Another embodiment of the present invention is a diagnostic system having one or more fluid machines and a diagnostic processing device that diagnoses the operating status of each of the fluid machines via a network, wherein each of the fluid machines acquires information including at least one of the load factor, set pressure and discharge pressure, ambient temperature, discharge temperature, number of alarms issued, and operating time as its operating status, and the diagnostic processing device has an input unit that inputs the operating status from each of the fluid machines, and a diagnostic unit that performs an operation improvement diagnosis for each of the fluid machines based on the operating status input by the input unit, and creates an operation improvement plan based on the results of the improvement diagnosis.

[0009] Furthermore, another embodiment of the present invention is a method for diagnosing fluid machinery using an apparatus for diagnosing the operating status of one or more fluid machinery connected via a network, characterized in that it includes an input step for inputting data indicating the operating status from each of the fluid machinery, and a diagnosis step for performing an operation improvement diagnosis for each of the fluid machinery based on the data input in the input step, and creating an operation improvement plan based on the results of the improvement diagnosis. [Effects of the Invention]

[0010] According to the present invention, it is possible to extract, from the operation data of the equipment, candidate equipment that should be operated (under different conditions, in different environments) from the current situation, and to propose improvements to these candidates. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a configuration diagram showing a diagnostic system according to a first embodiment of the present invention. [Figure 2] 1 is a configuration diagram showing the configuration of a compressor according to a first embodiment of the present invention. [Figure 3] 1 is a configuration diagram showing a configuration of an information communication device according to a first embodiment of the present invention. [Figure 4] FIG. 2 is an explanatory diagram illustrating an example of the configuration of a device information database according to the first embodiment of the present invention. [Figure 5] FIG. 2 is an explanatory diagram illustrating an example of the configuration of a customer information database according to the first embodiment of the present invention. [Figure 6] 3 is an explanatory diagram illustrating an example of the configuration of a historical data management table according to the first embodiment of the present invention; FIG. [Figure 7] 3 is an explanatory diagram illustrating an example of the configuration of an alarm / failure information management table according to the first embodiment of the present invention. FIG. [Figure 8] FIG. 1 is an explanatory diagram illustrating the relationship between functions according to the first embodiment of the present invention. [Figure 9] 4 is a flowchart illustrating the operation of a compressor diagnostic process according to the first embodiment of the present invention. [Figure 10]FIG. 2 is an explanatory diagram illustrating customer information according to the first embodiment of the present invention. [Figure 11] FIG. 2 is an explanatory diagram illustrating an example of an output of data visualization according to the first embodiment of the present invention. [Figure 12] 10 is a flowchart illustrating the operation of a compressor diagnostic process according to a second embodiment of the present invention. [Figure 13] 10 is a flowchart illustrating the operation of a compressor diagnostic process according to a third embodiment of the present invention. [Figure 14] FIG. 10 is an explanatory diagram illustrating first customer information according to the third embodiment of the present invention. [Figure 15] FIG. 10 is an explanatory diagram illustrating second customer information according to the third embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. The following description and drawings are examples for explaining the present invention, and some omissions and simplifications have been made as appropriate for clarity of explanation. The present invention can be implemented in various other forms. Unless otherwise specified, each component may be singular or plural.

[0013] In order to facilitate understanding of the invention, the position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings.

[0014] In the following explanation, various types of information may be described using expressions such as "database" (hereinafter referred to as "DB"), "table" (hereinafter referred to as "TBL"), and "list", but various types of information may also be expressed in data structures other than these. To indicate independence from data structure, "XXTBL", "XX list", etc. may be referred to as "XX information". When describing identification information, expressions such as "identification information", "identifier", "name", "ID", and "number" are used, and these are interchangeable.

[0015] When there are multiple components with the same or similar functions, they may be described using the same reference numeral with different subscripts. However, when there is no need to distinguish between these multiple components, the subscripts may be omitted.

[0016] Furthermore, in the following description, processing performed by executing a program may be described, but the program is executed by a processor (e.g., a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit)) to perform the specified processing while appropriately using storage resources (e.g., memory) and / or interface devices (e.g., communication ports), and therefore the processor may be the subject of the processing. Similarly, the subject of the processing performed by executing a program may be a controller, device, system, computer, or node having a processor. The subject of the processing performed by executing a program may be any computing unit, and may include a dedicated circuit (e.g., an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit)) that performs specific processing.

[0017] A program may be installed on a device such as a computer from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. If the program source is a program distribution server, the program distribution server may include a processor and storage resources for storing the program to be distributed, and the processor of the program distribution server may distribute the program to be distributed to other computers. Also, in the following description, two or more programs may be realized as one program, and one program may be realized as two or more programs. <Embodiment 1> First, the configuration of a diagnostic system according to embodiment 1 will be described with reference to Figures 1 to 3. Figure 1 is a configuration diagram showing an example of a diagnostic system according to embodiment 1. The diagnostic system 1 of embodiment 1 is a system that monitors the states of multiple devices to be monitored, such as air compressors. The devices to be monitored are, for example, fluid machinery.

[0018] As shown in Fig. 1, diagnostic system 1 is configured by connecting compressors 3A, which are an example of one or more fluid machines, installed at service bases 2 such as one or more factories, and diagnostic processing device 5, which is installed in monitoring center 4 that monitors service base 2, via network 6 such as the Internet. In the following, a compressor is shown as an example of a fluid machine to be monitored, but the system can also be applied to devices whose operation is controlled in the same way as a compressor (for example, air blowers such as fans and blowers).

[0019] Each compressor (in FIG. 1, each of the 14 compressors from compressor 3A to compressor 3N) has the same configuration and function, and transmits information such as the pressure inside each device and the accumulated operating time up to that point as operation data to the diagnostic processing device 5 periodically or irregularly via the network 6. Note that in the first embodiment, as an example, 14 compressors, i.e., compressors 3A to 3N, are given, but the number of compressors is not limited depending on the environment of the service base 2.

[0020] In addition, if any measurement value exceeds a predetermined threshold, if a malfunction occurs, or if repairs or inspections are performed, the compressor 3A sends an alarm or notification according to the content of the malfunction to the diagnostic processing device 5 via the network 6.

[0021] Fig. 2 is a diagram showing an example of the configuration of compressor 3A, which is a representative of compressors 3A to 3N. Compressor 3A is a device that discharges compressed air. As shown in Fig. 2, compressor 3A is composed of a power mechanism 32, a pressure sensor 33, a load control unit 34, a start / stop control unit 35, an output device 36, a temperature sensor 37, etc.

[0022] The power mechanism 32 is a compressor main body 31, which is the main mechanism of the compressor 3A, and a power source for driving the compressor main body 31, and the pressure sensor 33 detects and measures the discharge pressure, which is the pressure of the air discharged from the compressor 3A. The load control unit 34 switches between loaded operation and unloaded operation of the compressor 3A, thereby performing load control to control the discharge pressure output by the compressor 3A to be above a lower limit pressure and below an upper limit pressure.

[0023] The start / stop control unit 35 performs start / stop control by stopping the compressor 3A if no-load operation continues for a predetermined time or more, and restarting the compressor 3A if the discharge pressure falls below a predetermined value. The output device 36 has a communication function and outputs the air compressed by the compressor main body 31 via the network 6. The temperature sensor 37 detects and measures the temperature around the compressor 3A and the temperature of the compressed air.

[0024] Fig. 3 is a diagram showing the configuration of the diagnostic processing device 5. The diagnostic processing device 5 is a server having a function of monitoring and diagnosing the equipment status of each compressor 3A. As shown in Fig. 3, the diagnostic processing device 5 is configured with a CPU 10, a memory 11, an auxiliary storage device 12, a network interface (hereinafter referred to as network I / F) 13, an input device 14, and an output device 15.

[0025] The CPU 10 is a processor that controls the overall operation of the diagnostic processing device 5. The memory 11 is composed of a read-only memory (ROM) (not shown) made up of nonvolatile storage elements, and a random access memory (RAM) (not shown) made up of volatile storage elements. The ROM stores unchanging programs such as a basic input output system (BIOS). The RAM is composed of a dynamic RAM (DRAM) and the like, and is used as a working memory for the CPU 10. The information stored in the memory 11 will be described later.

[0026] The auxiliary storage device 12 is composed of a large-capacity, non-volatile storage device such as a hard disk drive or an SSD (Solid State Drive). Various programs and various data that should be stored for a long period of time are stored in the auxiliary storage device 12. The programs and data stored in the auxiliary storage device 12 are loaded from the auxiliary storage device 12 into the memory 11 when the analysis server is started or when needed. The CPU 10 executes the programs loaded into the memory 11, thereby performing various processes of the diagnostic processing device 5 as a whole, as described below.

[0027] The network I / F 13 is configured by, for example, a network interface card (NIC), and functions as an interface for communication with each of the compressors 3A to 3N to be monitored via the network 6 (FIG. 1).

[0028] The input device 14 is composed of, for example, a mouse, a keyboard, etc., and is used by the user to input various operations to the diagnostic processing device 5. The output device 15 is composed of, for example, a liquid crystal panel, an organic EL (Electro-Luminescence) display, and / or a printer, etc., and is used to display or print out necessary information. The input device 14 and the output device 15 may be integrated into one device such as a touch panel.

[0029] The various data stored in the diagnostic processing device 5 or used for processing can be realized by the CPU 10 reading and using the data from the memory 11 or the auxiliary storage device 12. Furthermore, each functional unit (for example, the data input unit 21, the diagnostic unit 22, the data output unit 23, and the data visualization unit 24) can be realized by the CPU 10 loading the program 20 stored in the memory 11 into the memory 11 and executing it.

[0030] The above-described program 20 may be stored (downloaded) into a storage device from a storage medium or from a network, and then loaded onto the memory 11 and executed by the CPU 10. Alternatively, the program 20 may be directly loaded onto the memory 11 from a storage medium or from the network 6 via a communication device, and then executed by the CPU 10.

[0031] In the following, the functions of the diagnostic processing device 5 are performed by a single server, but all or part of these functions may be distributed across one or more computers, such as a cloud, and may be realized by communicating with each other via a network. Specific processes performed by each component of this system will be described later using flowcharts.

[0032] Next, a description will be given of the information stored in the memory 11. As shown in Fig. 3, the memory 11 has a data input unit 21, a diagnosis unit 22, a data output unit 23, a data visualization unit 24, and a device information DB 25. Each of these units is configured by software that can be executed by the CPU 10, such as a program or module.

[0033] Next, the TBL configuration will be explained using Fig. 4 to Fig. 7. Fig. 4 is a diagram showing an example of the configuration of the device information DB 25, Fig. 5 is a diagram showing an example of the configuration of the customer information management TBL 26, Fig. 6 is a diagram showing an example of the configuration of the operation data management TBL 27, and Fig. 7 is a diagram showing an example of the configuration of the alarm / fault information management TBL 28.

[0034] As shown in FIG. 4, the device information DB 25 constitutes a storage unit having a customer information management TBL 26, an operation data management TBL 27, and an alarm / failure information management TBL 28.

[0035] 5, the customer information management TBL 26 is a TBL for managing users such as companies and organizations that use the compressors 3A to 3N at the service base 2. As shown in Fig. 5, the customer information management TBL 26 records, in association with each other, a customer name 26A indicating the name of the user who uses the compressor 3A, an installation location 26B indicating the installation location of the compressor 3A, a serial number 26C for identifying the compressor 3A, and a model 26D indicating the type of compressor 3A.

[0036] Figure 5 shows that a company called "Corporation A" has installed a compressor identified by serial number "XXX1234" and model "A model" at service center 2 in "XX city, XX prefecture." Here, 14 compressors are shown as an example, but the number of compressors registered will depend on the size and environment of service center 2.

[0037] The operation data management TBL 27 is a TBL for managing operation data showing the operation results of each compressor. As shown in Fig. 6, the operation data management TBL 27 records the above-mentioned serial number (and model) 27A, the acquisition date and time of the operation data 27B, items (1 to 6) included in the operation data 27C, and the numerical values ​​(1 to 6) of the items 27D.

[0038] For example, Figure 6 shows that compressor 3A, identified by serial number "XXX1234 (Model A)", acquired operational data at "2019 / 5 / 13 9:00" including items and values ​​such as set pressure "0.65" MPa, discharge pressure "0.65" MPa, ambient temperature "40" degrees, discharge temperature "102" degrees, load factor "83"%, and operating time "2500" hours.

[0039] The values ​​of these items are obtained from the respective parts of the compressor 3A shown in Fig. 2. For example, the set pressure is a set value of the discharge pressure that is output by the compressor 3A by switching between loaded operation and no-load operation, which is recorded by the load control unit 34. The discharge pressure is a set value of the discharge pressure that is output by the compressor 3A by switching between loaded operation and no-load operation, which is recorded by the load control unit 34.

[0040] The ambient temperature is the temperature around the compressor 3A, recorded by the temperature sensor 37. The discharge temperature is the temperature of the discharge air output by the compressor 3A when the compressor 3A switches between loaded operation and unloaded operation, recorded by the temperature sensor 37. The load factor is the ratio of the time the compressor 3A is driven to the time it is not driven, recorded by the load control unit 34. The operating time is the time the compressor 3A is operating, recorded by the start / stop control unit 35.

[0041] Compressor 3A performs load control by switching between load operation and no-load operation, controlling the output discharge pressure to be above a lower limit pressure and below an upper limit pressure, and performs start / stop control by stopping operation if no-load operation continues for a predetermined time or longer, and restarting operation if the discharge pressure falls below a predetermined value.

[0042] These load controls and start / stop controls are controls that are repeatedly performed during compressor operation. In the first embodiment, operation data related to the periodic operating state of the compressor 3A is recorded in the operation data management TBL 27. Therefore, in FIG. 6, for example, in the case of a compressor with serial number "XXX1234 (Model A)," the set pressure, discharge pressure, ambient temperature, discharge temperature, load factor, and operating time for a certain period starting from "2019 / 5 / 13 9:00" are recorded.

[0043] For these values, for example, the input unit 30 performs statistical processing (for example, calculating the average value, tallying up the operating time over the above-mentioned certain period, etc.) on the operating data received from the compressor 3A, and stores the values ​​in the operating data management TBL 27. The alarm / failure information management TBL 28 is a TBL for managing operation data indicating the alarm / failure record of each compressor. As shown in Fig. 7, the alarm / failure information management TBL 28 records the occurrence date 28A of an alarm or failure, the above-mentioned serial number 28B, model 28C, and details 28D of the alarm or failure that occurred. Fig. 7 shows, for example, that on the occurrence date "2018 / 8 / 15," compressor 3A identified by serial number "XXX1234" and model "A model" acquired operation data including each item and value such as "xx failure."

[0044] In this way, in the first embodiment, the operating state is analyzed by targeting controls that are repeatedly performed in the operation of a compressor, such as start / stop control and load control. Then, depending on the results of the analysis, improvement measures are proposed to promote energy conservation for a compressor that is operating inefficiently, such as changing the setting values ​​that perform such control. An example of inefficient operation is an operation in which the values ​​of various operation data obtained in start / stop control and load control (in FIG. 6, numerical values ​​1 to 7 for items 1 to 7) are outside predetermined ranges.

[0045] The proposal then includes reviewing the settings and reducing unnecessary driving of the compressor, which is periodically performed on the compressor, such as pressure setting and driving (re-driving). Specific processing will be described below.

[0046] Next, the operation will be explained using Fig. 8 to Fig. 11. Fig. 8 is an explanatory diagram explaining the relationship between functions in the diagnostic processing device 5, Fig. 9 is a flowchart explaining the operation of the compressor diagnostic processing, Fig. 10 is an explanatory diagram explaining customer information, and Fig. 11 is an explanatory diagram explaining an example of data visualization output.

[0047] 8, the data input unit 21 receives customer information and operation data from each of the compressors 3A to 3N arranged at the service base 2 shown in Fig. 1. The data input unit 21 stores the input customer information and operation data in the equipment information DB 25, and outputs it to the diagnosis unit 22. Specifically, the data input unit 21 stores the customer information in the customer information management TBL 26, and stores the operation data in the operation data management TBL 27 and the alarm / fault information management TBL 28.

[0048] The diagnosis unit 22 acquires information linked to the customer information stored in the equipment information DB 25. Specifically, the diagnosis unit 22 determines a diagnosis result indicating the operating status according to the operation flow of the compressor diagnosis process shown in Fig. 9, and outputs the customer information, operation data, alarm / fault information, and diagnosis result to the data output unit 23. According to the customer information, operation data, alarm / fault information, and diagnosis result acquired from the diagnosis unit 22, the data output unit 23 outputs to the data visualization unit 24 the content to be visualized based on this information.

[0049] The data visualization unit 24 outputs the customer information, operation data, alarm / fault information, and diagnosis results acquired from the data output unit 23 as output results including a customer name 51, a target device name 52, an installation location 53, a serial number 54, a diagnosis result 55, and an improvement plan 56, as shown in FIG. 10 . The output results may be output as a printed matter such as a report from a printing device such as a printer (not shown), or may be displayed on a browser output to the screen of the output device 15. When outputting to the output device 15, the data output unit 23 generates and outputs display data based on the output results, and when outputting to a printing device, generates and outputs display data based on the output results. In the first embodiment, the data output unit 23, the data visualization unit 24, and the output device 15 form a display unit.

[0050] Furthermore, the data may be displayed on the output device 72 of the user terminal 7 via the network 6. In this case, the data output unit 23 generates display data based on the output result and transmits it to the user terminal 7 via the network I / F 13. In the first embodiment, the data output unit 23 and the network I / F 13 form a transmission unit.

[0051] The input device 71 of the user terminal 7 receives and inputs the output results including the customer name 51, the target device name 52, the installation location 53, the serial number 54, the diagnosis result 55, and the improvement plan 56.

[0052] 9 and 10, the operation flow of the compressor diagnosis process will be described below. As described above, the diagnosis unit 22 acquires the above-mentioned serial number (and model) 27A, the acquisition date and time 27B of the operational data, the items (1 to 6) 27C included in the operational data, and the numerical values ​​(1 to 6) 27D of the items, all of which are stored in the operational data management TBL 27 of the equipment information DB 26. Note that, although the example in FIG. 6 lists six sets of items and numerical values, this is merely an example, and there may be six or fewer or more than six.

[0053] Specifically, if the data stored in the customer information management TBL 26 matches the acquired customer information, for example, data such as customer name "A Co., Ltd.", installation location "XX City, XX Prefecture," serial number "XXX1234," and model "A Model," the diagnosis unit 22 reads this information and acquires it from the operation data management TBL 27 as data linked to the serial number "XXX1234" and model "A Model."

[0054] For example, the diagnosis unit 22 acquires data in which the acquisition date and time is "2019 / 5 / 13 9:00", the set pressure is "0.65" MPa, the discharge pressure is "0.65" MPa, the ambient temperature is "40" degrees, the discharge temperature is "102" degrees, the load factor is "83"%, and the operating time is "2500" hours.

[0055] Furthermore, the diagnosis unit 22 acquires data linked to the serial number "XXX1234" and the model "A model" from the alarm / failure information management TBL 28. For example, the diagnosis unit 22 acquires the alarm / failure content "xx failure" when the occurrence date is "2018 / 8 / 15", the alarm / failure content "△△ alarm" when the occurrence date is "2018 / 9 / 2", and the alarm / failure content "○○ inspection" when the occurrence date is "2018 / 12 / 2".

[0056] The diagnostic unit 22 determines whether the load factor is equal to or greater than a predetermined threshold value for the acquired operation data (step S10). If the diagnostic unit 22 determines that the load factor is greater than the threshold value (step S10; YES), it further determines whether the maximum value of the discharge temperature is higher than a predetermined threshold value for the ambient temperature (maximum value of the discharge temperature>threshold value for the ambient temperature) (step S11). When the diagnosis unit 22 determines that the maximum value of the discharge temperature is higher than the predetermined threshold value for the ambient temperature (step S11; YES), it further determines whether the number of working days is equal to or greater than the predetermined threshold value (step S12). If the diagnosis unit 22 determines that the number of operating days is equal to or greater than a predetermined threshold (step S12; YES), it adds the device with the serial number "XXX1234" as a candidate to list 1 as shown in FIG. 10, updates the list, and outputs the result to the data output unit 23 (step S13). If the determination in step S10, step S11, or step S12 is NO, the process ends with the determination result that the device is not a target, that is, is operating normally (step S14).

[0057] An example of the screen display will now be described. Fig. 11 is a diagram showing an example of a screen that visualizes the data output in embodiment 1. A screen configuration 50 of the screen includes a customer name 51, a target device name 52, an installation location 53, a serial number 54, a diagnosis result 55, and an improvement proposal 56.

[0058] The customer name 51 is an area for displaying the customer name included in the customer information output from the data output unit 23. In this area, for example, the customer name "A Co., Ltd." is displayed.

[0059] The target device name 52 is an area for displaying the serial number of the compressor 3A included in the customer information. For example, the serial number "XXX1234" is displayed in this area. In this case, instead of the serial number, a model number linked to the serial number or a product name (not shown) may be displayed.

[0060] The installation location 53 is an area that displays the location where the compressor 3A included in the customer information is installed. For example, the installation location "XX City, XX Prefecture" is displayed in this area.

[0061] The serial number 54 is an area for displaying the serial number of the compressor 3A included in the customer information. For example, the serial number "XXX1234" is displayed in this area.

[0062] The diagnosis result 55 is an area that displays the results of the compressor diagnosis process shown in Fig. 9. In this area, for example, a statement such as "Extracted as a device with a high discharge temperature relative to the ambient temperature" is displayed.

[0063] The improvement proposal 56 is an area that displays the degree of wear on the equipment and advice on how to save energy for the compressor 3A that has received the diagnosis result 55. For example, a message such as "Suggestion for regular maintenance" is displayed in this area.

[0064] As described above, the diagnostic system of the first embodiment can diagnose a monitored device (e.g., a compressor or a fan) using a computer (diagnostic processing device 5) having a processor and a memory. Specifically, the processor receives operation data including periodic control performed on the monitored device (e.g., control of the device, such as load control or start / stop control, described below) and the operating time of the device operated in accordance with the control. The processor diagnoses whether the device is a candidate for operation (conditions, environment) different from the current state based on a determination of whether the control included in the operation data and the operating time of the device satisfy a predetermined relationship (e.g., in the case of a compressor, the processing of steps S10, S11, and S12 in FIG. 9 ). As a result, the device can be operated efficiently while taking into account the state of wear and tear of the device and energy conservation. <Embodiment 2> Next, a description will be given of embodiment 2. In the above-described embodiment 1, the load factor, the discharge temperature, and the number of operating days are used as the criteria, as shown in Fig. 9, but in embodiment 2, the load factor, the set pressure, and the number of operating days are used as the criteria, as shown in Fig. 12, which will be described later.

[0065] Fig. 12 is a diagram showing the operation flow of the diagnostic processing of the second embodiment, which is performed by the diagnostic unit 22 shown in Fig. 8. As in the first embodiment, the diagnostic unit 22 acquires the above-mentioned serial number (and model) 27A, acquisition date and time 27B of the operational data, items (1 to 6) 27C included in the operational data, and numerical values ​​(1 to 6) 27D of the items, all of which are stored in the operational data management TBL 27 of the device information DB 26.

[0066] Specifically, if the data stored in the customer information management TBL 26 that matches the acquired customer information is data such as customer name "A Co., Ltd.", installation location "XX City, XX Prefecture," serial number "XXX1234," and model "A Model," the diagnosis unit 22 reads this information and acquires it from the operation data management TBL 27 as data linked to the serial number "XXX1234" and model "A Model."

[0067] For example, the diagnosis unit 22 acquires data in which the acquisition date and time is "2019 / 5 / 13 9:00", the set pressure is "0.65" MPa, the discharge pressure is "0.65" MPa, the ambient temperature is "40" degrees, the discharge temperature is "102" degrees, the load factor is "83"%, and the operating time is "2500" hours. The diagnosis unit 22 also acquires this data from the alarm / fault information management TBL 28 as data linked to the serial number "XXX1234" and the model "A model".

[0068] For example, the diagnosis unit 22 acquires the alarm / fault content as "xx fault" when the occurrence date is "2018 / 8 / 15", the alarm / fault content as "△△ alarm" when the occurrence date is "2018 / 9 / 2", and the alarm / fault content as "○○ inspection" when the occurrence date is "2018 / 12 / 2".

[0069] The diagnostic unit 22 determines whether the load factor is less than a threshold value based on the acquired operation data (step S20). If the diagnostic unit 22 determines that the load factor is lower than a predetermined threshold value (step S20; YES), the diagnostic unit 22 further determines whether the device is operating outside the set pressure range (step S21).

[0070] When the diagnosis unit 22 determines that the device is operating outside the set pressure range (step S21; YES), it further determines whether the number of working days is equal to or greater than a threshold value (S12: similar to the first embodiment). If the diagnosis unit 22 determines that the number of operating days is equal to or greater than the threshold (S12; YES), it updates the list 1 by adding the device with the serial number "XXX1234" as a candidate, and outputs the result to the data output unit 23 (step S13: same as in the first embodiment). Note that if the determination is NO in step S20, step S21, or S12, the device is not a target, that is, the process ends with the determination result that the device is operating normally (step S14: same as in the first embodiment).

[0071] In the screen configuration shown in Fig. 10, the diagnostic result 55 is an area that displays the results of the compressor diagnostic process shown in Fig. 12. In this area, for example, a message such as "Extracted as equipment operating outside the set range" is displayed.

[0072] The improvement proposal 56 is an area that displays the degree of wear on the equipment and advice on how to save energy for the compressor 3A that has received the diagnosis result 55. For example, a message such as "Suggestion to review settings" is displayed in this area.

[0073] As described above, the diagnostic system of the second embodiment can diagnose a monitored device (e.g., a compressor or a fan) using a computer (diagnostic processing device 5) having a processor and a memory. That is, the processor receives operation data including periodic control performed on the monitored device (e.g., control of the device, such as load control or start / stop control, described below) and the operating time of the device operated in accordance with the control. The processor diagnoses whether the device is a candidate for operation (conditions, environment) different from the current state based on whether the control included in the operation data and the operating time of the device satisfy a predetermined relationship (e.g., in the case of a compressor, the processing of steps S20, S21, and S12 of FIG. 12). As a result, the device can be operated efficiently while taking into account the state of wear and tear of the device and energy conservation. <Embodiment 3> Next, a third embodiment will be described with reference to Figures 13, 14, and 15. In the first and second embodiments described above, the load factor, discharge temperature, set pressure, and number of operating days are used as the criteria, as shown in Figures 9 and 12, but in the third embodiment, the operating time, ambient temperature, and number of alarm failures are used as the criteria, as shown in Figure 13, which will be described later.

[0074] Figure 13 is a diagram showing the operational flow of the diagnostic processing of embodiment 3 performed by the diagnostic unit 22 shown in Figure 8, Figure 14 is an explanatory diagram explaining the first customer information according to embodiment 3, and Figure 15 is an explanatory diagram explaining the second customer information according to embodiment 3.

[0075] As in the first and second embodiments described above, the diagnosis unit 22 acquires the above-mentioned serial number (and model) 27A, the acquisition date and time 27B of the operational data, the items (1 to 6) 27C included in the operational data, and the numerical values ​​(1 to 6) 27D of the items, which are stored in the operational data management TBL 27 of the device information DB 26. Specifically, if the data stored in the customer information management TBL 26 that matches the acquired customer information is data of customer name "A Corporation," installation location "XX City, XX Prefecture," serial number "XXX1234," and model "A Model," the diagnosis unit 22 reads this information and acquires it from the operational data management TBL 27 as data linked to the serial number "XXX1234" and model "A Model."

[0076] For example, the diagnosis unit 22 acquires data in which the acquisition date and time is "2019 / 5 / 13 9:00", the set pressure is "0.65" MPa, the discharge pressure is "0.65" MPa, the ambient temperature is "40" degrees, the discharge temperature is "102" degrees, the load factor is "83"%, and the operating time is "2500" hours. The diagnosis unit 22 also acquires this data from the alarm / fault information management TBL 28 as data linked to the serial number "XXX1234" and the model "A model".

[0077] For example, the diagnosis unit 22 acquires the alarm / fault content as "xx fault" when the occurrence date is "2018 / 8 / 15", the alarm / fault content as "△△ alarm" when the occurrence date is "2018 / 9 / 2", and the alarm / fault content as "○○ inspection" when the occurrence date is "2018 / 12 / 2".

[0078] The diagnostic unit 22 determines whether the operating time is less than 1000 hours based on the acquired operation data (step S30). If the diagnostic unit 22 determines that the operating time is greater than 1000 hours (step S30; NO), the diagnostic unit 22 further determines whether the operating time is greater than or equal to 3000 hours (step S33).

[0079] If the diagnostic unit 22 determines that the operating time is 3000 hours or more (step S33; YES), it adds +1 to the day counter CTR, which has an initial value of zero (step S37), and then determines whether the unit was operating at an ambient temperature of 56 degrees or higher (S34).

[0080] If the diagnosing unit 22 determines that the machine was operating at an ambient temperature of 56°C or higher (S34; YES), it determines that there is a possibility of improvement, increments the day counter CTR by +1 (step S38), and determines whether the number of alarm failures is greater than that of the same model (S35). Here, if the day counter CTR was the value to which +1 was added in step S34, it becomes 2 at this stage.

[0081] When the diagnosis unit 22 determines that the number of alarm failures is greater than that of the same model (S35; YES), it determines that there is a possibility of improvement, increments the day counter CTR by 1 (step S39), and further determines whether the day counter CTR is equal to or greater than a predetermined threshold value of 2 (S36). Here, if 1 was added when it was determined that there is a possibility of improvement in steps S34 and S38, the day counter CTR becomes the value resulting from the additions made at those steps. If the diagnosis unit 22 determines that the day counter CTR is less than 2, which is a predetermined threshold value (step S36; NO), it updates the list 2 shown in Fig. 14 by adding the device with the serial number "XXX1234" as a candidate, and outputs the result to the data output unit 23 (step S41). Alternatively, if the diagnosis unit 22 determines that the day counter CTR is equal to or greater than 2, which is the predetermined threshold value (step S36; YES), it updates the list 3 shown in Fig. 15 by adding the device with the serial number "XXX1234" as a candidate, and outputs the result to the data output unit 23 (step S42).

[0082] The diagnosis result 55 shown in Fig. 10 is an area that displays the results of the compressor diagnosis process shown in Fig. 13. In this area, for example, a message such as "Extracted as equipment that has been operating for a long time in a high temperature state" is displayed.

[0083] The improvement proposal 56 is an area that displays the degree of wear on the equipment and advice on how to save energy for the compressor 3A that has received the diagnosis result 55. For example, a message such as "Suggestion for regular maintenance" is displayed in this area.

[0084] As described above, the diagnostic system of the third embodiment can diagnose a monitored device (e.g., a compressor or a fan) using a computer (diagnostic processing device 5) having a processor and a memory. Specifically, the processor receives operation data including periodic control performed on the monitored device (e.g., control of the device, such as load control or start / stop control, described below) and the operating time of the device operated in accordance with the control. The processor diagnoses whether the device is a candidate for operation (conditions, environment) different from the current state based on a determination of whether the control included in the operation data and the operating time of the device satisfy a predetermined relationship (e.g., in the case of a compressor, the processes of S30 to S36 in FIG. 9). As a result, the device can be operated efficiently while taking into account the state of wear and tear of the device and energy conservation. [Explanation of symbols]

[0085] 1: Diagnostic system 2: Service base 3A~3N: Compressor 4: Monitoring Center 5: Diagnostic processing device 6: User terminal 10:CPU 11: Memory 12:Auxiliary storage device 13: Network I / F 14: Input device 15: Output device 20: Program 21: Data entry section 22: Diagnostic Department 23: Data output section 24: Data visualization department 25:Device information DB 26:Customer information management TBL 27: Operational data management TBL 28: Alarm failure information management TBL

Claims

1. A diagnostic processing device connected to one or more fluid machines via a network and configured to diagnose an operating condition of each of the fluid machines, an input unit for inputting data indicating an operating status from each of the fluid machines; a diagnosis unit that performs an improvement diagnosis of operation for each of the fluid machines based on the data input by the input unit and creates an improvement plan for operation in accordance with a result of the improvement diagnosis; A diagnostic processing device comprising:

2. 2. The diagnostic processing device according to claim 1, further comprising a display unit for displaying and outputting the improvement plan created by said diagnostic unit.

3. 2. The diagnostic processing device according to claim 1, further comprising a transmitting unit that is connected to a user terminal having a display function via the network, generates display data for displaying and outputting the improvement proposal created by the diagnosing unit, and outputs the display data to the user terminal.

4. 2. The diagnostic processing device according to claim 1, wherein the operating status is information including at least one of load factor, set pressure and discharge pressure, ambient temperature, discharge temperature, number of alarms issued, and operating time, and wherein the diagnostic unit determines whether there is potential for improvement in the settings and equipment of the fluid machinery based on the operating status, counts the number of days for which it is determined that there is potential for improvement over a predetermined period, and if the count exceeds a predetermined threshold, creates an improvement setting proposal or an improvement equipment proposal for the fluid machinery based on the operating status, and creates the improvement setting proposal or the improvement equipment proposal as the improvement proposal.

5. 5. The diagnostic processing device according to claim 4, wherein the operating condition is a load factor, and when the load factor falls below a predetermined threshold, it is determined that there is a possibility of improvement.

6. 5. The diagnostic processing device according to claim 4, wherein the operating conditions are an ambient temperature and a discharge temperature, and when the discharge temperature exceeds a predetermined threshold value associated with the ambient temperature, it is determined that there is a possibility of improvement.

7. 5. The diagnostic processing device according to claim 4, wherein the operating conditions are a set pressure and a discharge pressure, and when the discharge pressure deviates from a predetermined range from the set pressure, it is determined that there is a possibility of improvement.

8. 5. The diagnostic processing device according to claim 4, wherein the operating condition is an ambient temperature, and when the ambient temperature exceeds a predetermined threshold, it is determined that there is a possibility of improvement.

9. 5. The diagnostic processing device according to claim 4, wherein the operating conditions are an ambient temperature and an operating time, and the diagnostic processing device determines that there is a possibility of improvement when the operating time when the ambient temperature is equal to or higher than a predetermined temperature exceeds a predetermined threshold.

10. 5. The diagnostic processing device according to claim 4, wherein the operating status is the number of alarms issued, and the diagnostic processing device determines that an abnormality has occurred if the number of alarms issued is greater than or equal to a predetermined number of times compared to the number of alarms issued by the fluid machinery of the same model.

11. 2. The diagnostic processing device according to claim 1, further comprising a storage unit for storing data indicating the operating conditions inputted by said input unit in association with each of said fluid machines.

12. A diagnostic system having one or more fluid machines and a diagnostic processing device that diagnoses an operating condition of each of the fluid machines via a network, each of the fluid machines acquires information including at least one of a load factor, a set pressure and a discharge pressure, an ambient temperature, a discharge temperature, a number of alarms issued, and an operating time as an operating status; The diagnostic processing device includes: an input unit for inputting the operating status from each of the fluid machines; a diagnosing unit that performs an improvement diagnosis of operation for each of the fluid machines based on the operating conditions input by the input unit, and creates an improvement plan for operation in accordance with a result of the improvement diagnosis; A diagnostic system comprising:

13. 13. The diagnostic system according to claim 12, wherein the diagnostic processing device is connected to a user terminal via the network and has an output unit that outputs the improvement proposal created by the diagnostic unit for display on the user terminal.

14. A diagnostic method for fluid machinery by a device that diagnoses the operating conditions of one or more fluid machinery connected via a network, comprising: an input step of inputting data indicating an operating status from each of the fluid machines; a diagnosis step of performing an improvement diagnosis of operation for each of the fluid machines based on the data input in the input step, and creating an improvement plan for operation in accordance with a result of the improvement diagnosis; A diagnostic method for fluid machinery, comprising:

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