Work machine monitoring system

Abstract

To provide a work machine monitoring system capable of effectively suppressing an emission amount of carbon dioxide of a work machine.SOLUTION: The data base server 107 records the revolution speed of the engine 102 detected by the engine revolution speed detection means 115a, 115b and the oil pressure detected by the oil pressure detection means 116a, 116b in the working machine 101. The server 108 calculates the information on the fuel consumption and the information on the emission of carbon dioxide on the basis of them, estimates the working state of the machine 101, and displays the information on the fuel consumption, the information on the emission of carbon dioxide and the estimated information on the working state on the display of the terminal 109.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a work machine monitoring system, a work machine monitoring method, and a program. [Background technology]

[0002] Approximately 70% or so of the carbon dioxide emitted during construction work comes from construction machinery and trucks (including dump trucks), with construction machinery accounting for more than half of that. In particular, hydraulic excavators account for 68% of the large construction machinery in operation at construction sites, and are known to account for a significant proportion of carbon dioxide emissions. The following points are presented as fuel-efficient driving methods for reducing carbon dioxide emissions (for example, Non-Patent Document 1): (1) Preventing unnecessary idling Idling is necessary for five minutes immediately after starting the engine and five minutes before shutting it down, but idling for long periods of time wastes fuel. Hydraulic excavators circulate oil using the hydraulic pump even when idling, and a 20-ton class excavator consumes approximately 0.76 liters of oil per hour. If idling time is reduced by one hour per day and the excavator is operated 25 days per month for one year, this will result in a fuel savings of 228 liters. (2) Preventing hydraulic pressure relief Hydraulic relief refers to the process whereby the pressure adjustment valve opens and oil returns to the hydraulic oil tank when the hydraulic pressure rises above the upper limit pressure of the hydraulic circuit. If the reaction force of the excavated soil is large, the work equipment (hydraulic actuator) will not move even if the operating lever is continued to be pulled, and the hydraulic pressure is relieved. Fuel consumption during hydraulic relief is 28 liters / hour, which is more fuel than the 25 liters / hour fuel consumption during 90-degree swing loading work, and the more hydraulic pressure is relieved, the more fuel is wasted. If the working time during hydraulic relief is reduced by one hour per day, and the machine is operated 25 days per month for one year, this will result in a fuel savings of 8,400 liters. (3) Partial engine operation (reducing engine speed) For the same excavation and loading work, lowering the engine speed will result in less fuel consumption and improved fuel efficiency than when the engine speed is set to maximum. (4) High-level excavation (higher excavation position) When excavating at the bottom of the slope, where soil is scooped from the toe (low position) of the face towards the shoulder (high position), the cycle time is longer and the arm and boom (hydraulic actuator) move more, resulting in more fuel consumption.When excavating at the top of the face first and then the bottom, this is called top-bottom excavation, which shortens the cycle time and improves fuel consumption and fuel efficiency.

[0003] Conventionally, a technology for reducing carbon dioxide emissions from construction machinery and the like includes a data collection means for collecting drive history data of the drive source of the managed equipment, for example, data representing the history of engine revolutions, and a processing means for performing processing to determine management data for the managed exhaust gas of the managed equipment based on the drive history data, and the processing means uses the management data to perform management processing for multiple managed equipment to reduce the emissions (for example, Patent Document 1). [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Iizuka, Shibata, Kawakita, and Takahashi, "Fuel-efficient operation for reducing carbon dioxide emissions in construction work (2)," Proceedings of the Global Environment Symposium, October 2002, pp. 7-12 [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2001-227397 Summary of the Invention [Problem to be solved by the invention]

[0006] As suggested by the aforementioned Non-Patent Document 1, in construction machinery and other work machines, not only the operating conditions of the engine but also the operating conditions of hydraulically operated work equipment (hydraulic actuators) such as excavators and cranes have a significant impact on carbon dioxide emissions. However, the above-mentioned conventional technology only manages the driving history data of the engine's drive source, which has the problem of not being able to effectively suppress carbon dioxide emissions.

[0007] Therefore, an object of the present invention is to make it possible to effectively suppress the amount of carbon dioxide emitted from a work machine. [Means for solving the problem]

[0008] The work machine monitoring system of the present application comprises: a work machine including an engine, a hydraulic pump driven by the engine, a hydraulic actuator driven by hydraulic oil discharged by the hydraulic pump, engine speed detection means for detecting the speed of the engine, and oil pressure detection means for detecting oil pressure in the hydraulic pump; a recording means for executing a process of recording the engine speed and the oil pressure in chronological order; an information processing means that executes a process of calculating information related to fuel consumption and information related to carbon dioxide emissions based on the engine speed and oil pressure that are respectively recorded in chronological order in the recording means, and a process of estimating the working status of the work machine; a display means for executing a process of displaying, in correspondence with the work machine, graphs showing time-series changes in the engine speed and oil pressure, which are respectively recorded in time series in the recording means, the information on fuel consumption and the information on carbon dioxide emissions calculated by the information processing means, and the estimated information on the work situation; Equipped with. [Effects of the Invention]

[0009] According to the present invention, it is possible to effectively suppress the amount of carbon dioxide emitted from a work machine. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram illustrating an embodiment of a work machine monitoring system. [Figure 2] FIG. 2 is a block diagram illustrating an example of the configuration of a data warehouse server. [Figure 3] 10 is a flowchart illustrating an example of a work machine monitoring process. [Figure 4] FIG. 10 is a diagram illustrating a display example by the display process. [Figure 5] FIG. 10 is an explanatory diagram of a process for estimating a work cycle and soil volume (number of work tasks). [Figure 6] FIG. 1 is a diagram (part 1) explaining the relationship between engine speed and oil pressure. [Figure 7] FIG. 2 is a diagram (part 2) explaining the relationship between engine speed and oil pressure. [Figure 8] FIG. 10 is an explanatory diagram of a process for estimating the state of hydraulic relief. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Fig. 1 is a block diagram illustrating an embodiment of a work machine monitoring system. The embodiment, a work machine monitoring system 100, is made up of one or more work machines 101(#1) to 101(#N) (N is a natural number), a control device 118, the Internet 119, a database server 107 and a data warehouse server 108 provided by a cloud service 120, and a management terminal device 109.

[0012] For example, one or more work machines 101(#1) to 101(#N) (N is a natural number), such as construction machinery such as hydraulic excavators (including backhoes), tractor shovels, cranes, and bulldozers, and trucks (including dump trucks) that operate at construction sites, each have the basic configuration shown in work machine 101(#1) in Fig. 1. In the following explanation, unless otherwise distinguished, N work machines 101(#1) to 101(#N) will be collectively referred to as work machine 101.

[0013] First, the work machine 101 is equipped with an engine 102. The engine 102 is, for example, a diesel engine, and drives the travel mechanism (drive shaft, transmission, tires, etc.) of the work machine 101 (not shown) via an engine shaft 110, and also drives the hydraulic pump 103 to rotate.

[0014] The hydraulic pump 103 drives an internal pump mechanism via an engine shaft 110 to send hydraulic oil from a hydraulic oil tank (not shown) to one or more hydraulic actuators 104(#1) to 104(#M) via an oil supply pipe 114 and valves 115(#1) to 115(#M) (M is a natural number greater than or equal to 1), applying hydraulic pressure. Each of the hydraulic actuators 104(#1) to 104(#M) operates a work mechanism, such as a shovel, boom, crane, platform lifting device, or swing mechanism, using the hydraulic oil pressure. When an operator operates one of the control devices 116(#1) to 116(#M) that corresponds to the desired work mechanism (referred to as "control device 116(#i)"), the valve 115(#i) opens by an amount corresponding to the amount of operation, and the corresponding hydraulic actuator 104(#i) operates the corresponding work mechanism. Although FIG. 1 shows one hydraulic pump 103, there may be two or more hydraulic pumps 103.

[0015] The rotation speed of the engine 102 is detected by an engine rotation speed detection means in which an optical fiber laser sensor 105b installed in the vicinity of reflective tape 105a, which is attached to an engine shaft 110 connected to, for example, an alternator (generator) 109 in the engine room and rotates together with the engine shaft 110, receives the reflected laser light. The optical fiber laser sensor 105b is connected to a PLC (Programmable Logic Controller) device 111 installed in, for example, an operator's cabin. The PLC device 111 calculates the rotations per minute (rpm) of the engine 102 based on the laser light from the reflective tape 105a detected by the optical fiber laser sensor 105b.

[0016] On the other hand, the hydraulic pressure of the hydraulic oil discharged by the hydraulic pump 103 is detected by hydraulic pressure detection means, which is composed of, for example, a diaphragm-type hydraulic pressure sensor 106a installed inside the hydraulic pump 103 and a hydraulic pressure detection signal line 106b that outputs a hydraulic pressure detection signal (analog signal) detected by the hydraulic pressure sensor 106a. The PLC device 111 calculates, for example, an instantaneous hydraulic pressure value [MPa] (Mega Pascal = 1 million Pascals) based on the hydraulic pressure detection signal, which is an analog signal input from the hydraulic pressure detection signal line 106b and converted into a digital signal by an A / D (analog / digital) converter.

[0017] Furthermore, the PLC device 111 determines the current position (latitude and longitude) of the work machine 101 based on radio waves received by a receiving antenna 112 of a Global Navigation Satellite System (GNSS) from a positioning satellite.

[0018] Then, the PLC device 111 transmits the calculated engine 102 rotation speed [rpm] and oil pressure [Mpa], as well as the measured current position (latitude and longitude), via an antenna 113 using a built-in wireless interface such as WiFi (a registered trademark of the Wi-Fi Alliance, USA) or Bluetooth (a registered trademark of Bluetooth SIG, INC., USA), for example, every minute to a control device 118 installed, for example, in an office at the construction site.

[0019] The control device 118 collects information on the engine 102 rotation speed [rpm], oil pressure [MPa], and current position (latitude and longitude) received from each of one or more work machines 101(#1) to 101(#N). The control device 118 then transmits the information on the engine 102 rotation speed [rpm] and oil pressure [MPa] together with the identification information of the work machines 101(#1) to 101(#N) via the Internet 119 using a wireless or wired communication interface to the database server 107, which is recording means, for recording in chronological order, and also transmits information on the current position (latitude, longitude, and altitude) to the data warehouse server 108.

[0020] The database server 107 may be provided by a cloud service 120 such as AWS (Amazon Web Service) (registered trademark of Amazon.com, Inc., USA), Microsoft Azure (registered trademark of Microsoft Corporation, USA), or Google Cloud (registered trademark of Google LLC, USA). Alternatively, the database server 107 may be installed independently by the organization that operates the work machine monitoring system 100.

[0021] The data warehouse server 108 operates as an information processing means and a display means, and has the configuration shown in Fig. 2, for example. This configuration may be that of a typical server computer, and has a configuration in which a CPU 201, a ROM (read-only memory) 202, a RAM (random access memory) 203, an SSD (solid state disk) storage device 204, and a network interface 205 are interconnected by a system bus 206. Note that the data warehouse server 108 can be one provided by the cloud service 120 described above. Alternatively, the data warehouse server 108 may be installed independently by the organization operating the work machine monitoring system 100.

[0022] The CPU 201 of the data warehouse server 108 reads out the work machine monitoring program stored in the ROM 202 into the RAM 203 and executes it, thereby executing the processing steps described below for each of the work machines 101(#1) to 101(#N) in Figure 1.

[0023] The SSD storage device 204 of the data warehouse server 108 stores, for example, various data that are calculated or estimated in the information processing described below.

[0024] The network interface 205 of the data warehouse server 108 controls communication with the database server 107 in FIG. 1, and communication with the control device 118 and management terminal device 109 via the Internet 119 .

[0025] Figure 3 is a flowchart showing an example of work machine monitoring processing that is realized by CPU 201 executing a work machine monitoring program. The work machine monitoring processing has a processing structure in which information processing A consisting of processing step groups S301 to S304, processing step groups S305 and S306 that are work situation estimation processing A', processing step S307, and display processing B consisting of processing step S307 and processing step S308 are repeatedly executed. Note that although the processing steps are shown to be executed in the order shown by the upward arrows in the flowchart of Figure 3, those that can be executed in parallel may be executed in parallel.

[0026] As an example of information processing A, the CPU 201 executes a program S301 that calculates the average rotation speed [rpm] of the engine 102 for each day that the work machine 101 is operated, based on time series data of the rotation speed [rpm] of the engine 102 recorded in the database server 107.

[0027] As an example of information processing A, the CPU 201 executes processing step S302 to calculate the idling time [min] (minutes) for each day that the work machine 101 has operated, based on time-series data of the rotation speed [rpm] of the engine 102 recorded in the database server 107. For example, for each day that the work machine 101 has operated, if the value of the time-series data for each minute of the rotation speed [rpm] of the engine 102 is within a predetermined idling rotation speed range (for example, 300 to 800 rpm), the CPU 201 determines that the engine 102 in Fig. 1 was idling during that time period, and integrates that time into the idling time. The CPU 201 outputs the integrated value of the idling time as the idling time [min] for that day.

[0028] As an example of information processing A, the CPU 201 executes processing step S303 to calculate information related to fuel consumption for each day that the work machine 101 has operated, based on time-series data of the engine 102 rotation speed [rpm] and oil pressure [Mpa] recorded in the database server 107. For example, the CPU 201 calculates an estimated value of the fuel consumption amount [L] (liters) accumulated per day, based on each set of time-series values ​​of the engine 102 rotation speed [rpm] and oil pressure [Mpa], for each day that the work machine 101 has operated.

[0029] This fuel consumption amount can be calculated, for example, by the following formula (1).

number

[0030] Instead of the above calculation, in step S303, the CPU 201 calculates the rotation speed E [rpm] of the engine 102 and the oil pressure P n The fuel consumption amount F [L] may be calculated by calculating the time series values ​​of the fuel consumption based on fuel consumption conversion data that converts the time series value set of [Mpa] into the consumption amount [L] (liters) of light oil, which is diesel engine fuel, and accumulating the time series values ​​for one day. The fuel consumption conversion data can be obtained in advance by testing for each work machine 101, for example.

[0031] As an example of information processing A, the CPU 201 executes processing step S304 to calculate information regarding carbon dioxide emissions based on, for example, the information regarding fuel consumption calculated in processing step S303 for each day the work machine 101 operates. For example, the CPU 201 calculates the carbon dioxide emissions [kg-CO2] for each day the work machine 101 operates by multiplying the fuel consumption [L], which is the accumulated value for one day calculated in processing step S303, by a diesel / carbon dioxide emission conversion coefficient [kg-CO2 / L] = 2.619 kg-CO2 / L, for example, obtained by testing.

[0032] Meanwhile, as part of information processing A, the CPU 201 executes processing A' to estimate the work status of the work machine 101 based on time-series data of the rotation speed [rpm] of the engine 102 recorded in the database server 107. Specifically, the CPU 201 executes the following processing steps S305 and S306 as an example of processing A' to estimate the work status.

[0033] As an example of process A' for estimating the work status, the CPU 201 executes processing step 305 to estimate the work cycle and earthwork volume (number of work tasks) for each working day of the work machine 101, based on changes in the engine 102 rotation speed [rpm] and oil pressure [Mpa] recorded in the database server 107. This process will be described in detail using Figure 5.

[0034] As an example of process A' for estimating the work situation, the CPU 201 executes processing step 306 for estimating the state of the hydraulic relief of the hydraulic pump 103 (FIG. 1) in the work machine 101 based on changes in the rotation speed [rpm] and oil pressure [Mpa] of the engine 102 recorded in the database server 107. This processing will be described in detail using FIGS. 6, 7, and 8.

[0035] As described above in the explanation of Figure 1, the PLC device 111 installed on the work machine 101 determines the current position (latitude and longitude) of the work machine 101 based on radio waves received by the GNSS receiving antenna 112 from positioning satellites, and records this in the database server 107. Therefore, as an example of information processing A, the CPU 201 executes processing step S307, which acquires the current position (latitude and longitude) of the work machine 101 from the control device 118 in Figure 1 via the Internet 119.

[0036] Next, the CPU 201 of the data warehouse server 108 executes processing step S308 as display processing B, which is a display means, to determine whether or not the administrator has issued a display instruction to display the monitoring status of the work machine on a display (not shown) on the management terminal device 109 connected via the Internet 119.

[0037] If the determination in processing step S308 is NO, CPU 201 returns to the execution of information processing A.

[0038] If the determination in processing step S308 is YES, the CPU 201 executes display processing step S309. Specifically, for example, the CPU 201 generates display data, such as the one shown in the example below, by associating one of the work machines 101(#1) to 101(#N) (hereinafter referred to as "work machine 101(#i)") designated as a display work machine 401 by an administrator operating management terminal device 109, which is a computer terminal connected to the Internet 119 in Figure 1, on a display screen 400 of the display of the management terminal device 109 as shown in Figure 4, with a similarly designated display date 402, transmits the data to the management terminal device 109 via the Internet 119, and displays it on the display screen 400 of the display of the management terminal device 109.

[0039] Specifically, the CPU 201 displays on the display screen 400, for example, a line graph 403 (vertical axis: engine speed [rpm], horizontal axis: measurement time [hours: minutes: seconds]) showing the time series change in the rotation speed of the engine 102 of the work machine 101 (#i) on the display specified date 402 recorded in the database server 107, and a line graph 404 (vertical axis: oil pressure [MPa], horizontal axis: measurement time [hours: minutes: seconds]) showing the time series change in the oil pressure.

[0040] Furthermore, the CPU 201 displays, for example, in a display area 405 within the display screen 400, the accumulated fuel consumption [L] for one day on the designated display date for the work machine 101 (#i) designated as the displayed work machine 401, calculated by the information processing A in FIG. 2 described above (the "Estimated fuel consumption" item in 405 in FIG. 4), a simulation value [L] when the average rotation speed [rpm] of the engine 102 is reduced by 10% (the "Reduction simulation" item in 405 in FIG. 4), and a value [L] indicating how much fuel will be reduced by the above simulation value (the "Fuel reduction amount" in 405 in FIG. 4). The contents of this display screen 400 may be flexibly changed since the required information may differ for each site, for example, whether to view data by hour, by day, or by month. For example, the CPU 201 may display the average rotation speed [rpm] of the engine 102, the idling time [min], the average fuel consumption per hour [L / h], or the amount of carbon dioxide emitted per day [kg-CO2]. Furthermore, the CPU 201 may display, in the display area 406 of the display screen 400, the comparison between the idling time and the working time for one day together with the cumulative operating time, for example, as a doughnut graph.

[0041] Furthermore, the CPU 201 displays, in the display area 407 of the display screen 400, for example, a bar graph (vertical axis: [kg-CO2], horizontal axis: [days]) that allows comparison of the time series values ​​of carbon dioxide emissions for, for example, the past 20 days of the work machine 101 (#i) designated as the displayed work machine 401, calculated by the information processing A in FIG. 2 described above.

[0042] Furthermore, the CPU 201 displays on the display screen 400 a map 408 showing the position 409 at the current time of the work machine 101 (#i) designated as the displayed work machine 401, which corresponds to the current position (latitude and longitude) acquired by the information processing A of Figure 2 described above.

[0043] In response to an operator's operation of an operating device 116(#i) among the operating devices 116(#1) to 116(#M) corresponding to a desired working mechanism, the corresponding valve 115(#i) opens, and hydraulic pressure [MPa] is applied to the corresponding hydraulic actuator 104(#i). As a result, when the hydraulic pressure [MPa] measured in the hydraulic pump 103 increases, the torque applied to the engine shaft 110 ( FIG. 1 ) to which the hydraulic pump 103 is connected increases. Even if the engine 102 rotation speed [rpm] remains the same, fuel consumption and carbon dioxide emissions increase in order to maintain that rotation speed. Therefore, in this embodiment, as described in processing steps S303 and S304 of FIG. 3 , accurate fuel consumption and carbon dioxide emissions can be calculated by calculating fuel consumption and carbon dioxide emissions using, for example, fuel consumption conversion data based on time-series data of the engine 102 rotation speed [rpm] and hydraulic pressure [MPa]. This allows accurate calculation of fuel consumption and carbon dioxide emissions, which can be used as indicators for determining optimal fuel-saving driving.

[0044] 5(a) is a line graph (vertical axis: engine rotation speed [rpm], horizontal axis: measurement time) showing an example of time-series data 501 of the rotation speed of the engine 102 recorded in the database server 107 when the work machine 101 is a traveling vehicle (for example, a heavy dump truck). When the work machine 101 is a traveling vehicle, it is possible to determine whether the work machine 101 is traveling or stopped from this time-series data 501 of the rotation speed of the engine 102. For example, in the time-series data 501, the area surrounded by dashed line 502 indicates a traveling state, and the area surrounded by dashed line 503 indicates a stop (loading, dumping up). The CPU 201 of the data warehouse server 108 extracts specific waveform patterns such as those shown as 502 or 503 in Figure 5(a) from the time series data of the engine 102 rotation speed [rpm] recorded in the database server 107, thereby estimating the work cycle of the work machine 101 for each working day, and can estimate the amount of earthwork (number of jobs) by counting the number of these waveform patterns on that working day.

[0045] FIG. 5(b) is a line graph (vertical axis: engine rotation speed [rpm], horizontal axis: measurement time) showing an example of time-series data 510 of the rotation speed of the engine 102 recorded in the database server 107 when the work machine 101 is a hydraulic excavator (e.g., a backhoe). When the work machine 101 is a hydraulic excavator, this time-series data 510 of the rotation speed of the engine 102 shows changes in the rotation speed [rpm] of the engine 102 when work is being performed by operating the boom, which is a work mechanism, and when swinging is being performed by the swing mechanism, which is also a work mechanism. For example, in the time-series data 510 of FIG. 5(b), the area surrounded by dashed line 511 indicates a working state, each point 512 indicates a swinging state, and each point 513 indicates a standby state. From this, for example, in the case of loading work onto a transport vehicle, it is possible to determine that one work cycle is "boom operation (digging) → swing → boom operation (loading)." The CPU 201 of the data warehouse server 108 extracts specific waveform patterns such as those shown as 511, 512, or 513 in Figure 5(b) from the time series data of the engine 102 rotation speed [rpm] recorded in the database server 107, thereby estimating the work cycle for each operating day of the work machine 101, and can estimate the amount of earthwork (number of operations) by counting the number of these waveform patterns on that operating day.

[0046] The example in Figure 5 is an example in which the work cycle and soil volume (number of operations) are estimated from the waveform pattern of the time series data of the rotation speed [rpm] of the engine 102, but it is also possible to add the time series data of the oil pressure [Mpa] to the time series data of the rotation speed [rpm] of the engine 102 and estimate the work cycle and soil volume (number of operations) from the characteristics of each waveform pattern.

[0047] Fig. 6 is a diagram showing a range of one day, and Fig. 7 is a diagram showing a range of a shorter time period, in which line graph 403 showing the time series change in the rotation speed of engine 102 in Fig. 4 and line graph 404 showing the time series change in oil pressure are compared so that the measurement times of both are aligned when work machine 101 (#i) is, for example, a hydraulic excavator. Figs. 6 and 7 show that, particularly in hydraulic excavators, the rotation speed and oil pressure of engine 102 are linked. In other words, as engine rotation speed increases, oil pressure also increases, and as engine rotation speed decreases, oil pressure also tends to decrease. FIG. 8 is an explanatory diagram of a process for estimating the state of hydraulic relief when the work machine 101 is a hydraulic excavator (e.g., a backhoe). A line graph showing hydraulic time-series data 601 recorded in the database server 107 (vertical axis: hydraulic pressure [MPa] (corresponding to 403 in FIG. 4), horizontal axis: measurement time) and a line graph showing engine 102 rotation speed time-series data 602 recorded in the database server 107 (vertical axis: engine rotation speed [rpm], horizontal axis: measurement time) (corresponding to 404 in FIG. 4) are drawn so that the measurement times of both graphs match. As explained in FIG. 5, T1 is the estimated work cycle, T2 is the timing of swing, and T3 is the timing of stopping. As explained in the "Background Art" section, when hydraulic relief occurs, unnecessary fuel consumption occurs. As shown in Fig. 8, it can be estimated that hydraulic relief has occurred during a period T0 when the time-series data 602 of the engine 102 rotation speed [rpm] is at a predetermined rotation speed (for example, around 1800 rpm in Fig. 8) and the time-series data of the hydraulic pressure [MPa] is stuck at the upper limit value of 100%. Therefore, when the changes in the engine 102 rotation speed [rpm] and the changes in the hydraulic pressure [MPa] recorded in the database server 107 are in the state shown at T0 in Fig. 8, the CPU 201 estimates that hydraulic relief has occurred in the hydraulic pump 103 of the work machine 101, and in the display processing of step S308 in Fig. 3 described above, displays, for example, the percentage or time during which hydraulic relief occurred within a day, and in the case of real-time display, a warning. As a result, according to this embodiment, fuel-saving operation that suppresses hydraulic relief is possible.

[0048] In the embodiment described above, as an example of process A' in FIG. 3 for estimating a work situation, the CPU 201 may execute a processing step of inputting a data set of changes in the rotation speed [rpm] and hydraulic pressure [Mpa] of the engine 102 that has been newly recorded in the database server 107 into a work situation estimation model obtained by machine learning of a data set of changes in the rotation speed [rpm] and hydraulic pressure [Mpa] of the engine 102, and outputting an estimation result of the work situation of the work machine 101 and an estimation result of the state of the hydraulic relief.

[0049] 1 may further include operation state detection means 117 for detecting the operation states of the operation devices 116(#1) to 116(#M) for operating the hydraulic actuators 104(#1) to 104(#M), and the PLC device 111 of the work machine 101 may transmit the operation states of the operation devices 116(#1) to 116(#M) detected by the operation state detection means 117 to the database server 107 via the Internet 119 for recording. Then, in display processing step S309 of FIG. 3 , the CPU 201 of the data warehouse server 108 may further display a graph showing changes in the operation states of the operation devices 116(#1) to 116(#M), which are recorded in the database server 107, in correspondence with the graphs showing changes in the rotation speed [rpm] and hydraulic pressure [Mpa] of the engine 102 over time, which are recorded in the database server 107. This makes it possible to further estimate the behavior of each of the hydraulic actuators 104(#1) to 104(#M) in FIG.

[0050] According to the embodiment described above, it is possible to simultaneously and in real time monitor the operating status of the engine 102 and hydraulic pump 103 of one or more engine-driven work machines 101 at a construction site. Furthermore, according to the above embodiment, in addition to obtaining information on the engine 102 rotation speed and idling time, it is possible to calculate more accurate information on fuel consumption and carbon dioxide emissions based on time-series data on the engine 102 rotation speed and hydraulic pressure, and it is also possible to estimate a more appropriate work cycle and soil volume (number of work tasks). Furthermore, according to the above embodiment, it is possible to estimate the hydraulic relief state based on time-series data on the engine 102 rotation speed and hydraulic pressure. Furthermore, according to the above embodiment, when multiple identical work machines 101 are used, it is possible to analyze the characteristics of each operator and provide guidance on efficient driving methods. Additionally, the travel speed of the work machine 101 can be determined from the travel time calculated from the position information and data acquisition time. This enables safety management by preventing excessive speeds and identifying sections where the travel speed is significantly slow. [Explanation of symbols]

[0051] 100 Work Machine Monitoring System 101, 101(#1)~101(#N) Work Machine 102 Engine 103 Hydraulic pump 104, 104(#1)~104(#M), 104(#i) Hydraulic actuator 105a Reflective tape 105b Optical fiber laser sensor 106a Oil pressure sensor 106b Oil pressure detection signal line 107 Database Server 108 Data Warehouse Server 109 Management terminal 110 Engine shaft 111 PLC equipment 112 receiving antenna 113 Antenna 114 Oil pipe 115, 115(#1)~115(#M), 115(#i) valve 116, 116(#1)~116(#M), 116(#i) Operating device 117 Operation status detection means 118 Control Device 119 Internet 120 Cloud Services 201 CPU 202 ROM 203 RAM 204 SSD storage 205 Network Interface

Claims

1. a work machine including an engine, a hydraulic pump driven by the engine, a hydraulic actuator driven by hydraulic oil discharged by the hydraulic pump, engine speed detection means for detecting the speed of the engine, and oil pressure detection means for detecting oil pressure in the hydraulic pump; a recording means for executing a process of recording the engine speed and the oil pressure in chronological order; an information processing means that executes a process of calculating information related to fuel consumption and information related to carbon dioxide emissions based on the engine speed and the oil pressure that are respectively recorded in chronological order in the recording means, and a process of estimating the working status of the work machine; a display means for executing a process of displaying, in correspondence with the work machine, graphs showing time-series changes in the engine speed and oil pressure, which are respectively recorded in time series in the recording means, the information on fuel consumption and the information on carbon dioxide emissions calculated by the information processing means, and the estimated information on the work situation; A work machine monitoring system comprising:

2. 2. The work machine monitoring system according to claim 1, wherein the process of estimating the work status is a process of estimating a work cycle and an earthmoving volume of the work machine based on changes in the engine speed and changes in the hydraulic pressure.

3. 2. The work machine monitoring system according to claim 1, wherein the process of estimating the work status is a process of estimating a hydraulic relief state of the hydraulic pump in the work machine based on changes in the engine speed and the hydraulic pressure.

4. 2. The work machine monitoring system according to claim 1, wherein the process of estimating the work status is a process of inputting a data set of changes in the engine rotation speed and changes in the oil pressure that is newly recorded in the recording means into a work status estimation model obtained by machine learning of a data set of changes in the engine rotation speed and changes in the oil pressure, and outputting an estimation result of the work status of the work machine.

5. the work machine is further provided with a global navigation satellite system receiver that receives radio waves from positioning satellites to determine the current position of the work machine, the information processing means further executes processing to acquire, from the work machine, the current position measured by the work machine; The display means further displays a map of the current position of the work machine acquired by the information processing means. The work machine monitoring system of claim 1 .

6. further comprising an operation state detection means for detecting an operation state of an operation device for operating the hydraulic actuator; the recording means records the operation state of the operation device in chronological order; the display means further displays a graph showing the change in the operating state of the operating device recorded in chronological order in the recording means, in correspondence with the graph showing the change in the engine speed and the oil pressure over time. The work machine monitoring system of claim 1 .

7. the hydraulic pump drives the plurality of hydraulic actuators; the plurality of hydraulic actuators are operated by the plurality of individual operating devices, the operation state detection means detects the operation state detection means of each of the plurality of operation devices; the recording means records the operation states of the plurality of operation devices in chronological order, the display means displays a graph showing each change in the operation state of the plurality of operation devices. The work machine monitoring system according to claim 6.

8. a process of recording in a recording means in chronological order the number of revolutions of the engine and the hydraulic pressure in the hydraulic pump detected in a work machine equipped with an engine, a hydraulic pump driven by the engine, and a hydraulic actuator driven by hydraulic oil discharged by the hydraulic pump; a process for calculating information relating to fuel consumption and information relating to carbon dioxide emissions based on the engine speed and the oil pressure, which are respectively recorded in chronological order in the recording means, and a process for estimating the working status of the work machine; a process of displaying, in association with the work machine, graphs showing time-series changes in the engine speed and oil pressure, which are respectively recorded in time series in the recording means, information about the fuel consumption and information about the carbon dioxide emissions, and estimated information about the work situation; A work machine monitoring method in which the above is executed by one computer or in a distributed manner across multiple computers.

9. a process of recording in a recording means in chronological order the number of revolutions of the engine and the hydraulic pressure in the hydraulic pump detected in a work machine equipped with an engine, a hydraulic pump driven by the engine, and a hydraulic actuator driven by hydraulic oil discharged by the hydraulic pump; a process for calculating information relating to fuel consumption and information relating to carbon dioxide emissions based on the engine speed and the oil pressure, which are respectively recorded in chronological order in the recording means, and a process for estimating the working status of the work machine; a process of displaying, in association with the work machine, graphs showing time-series changes in the engine speed and oil pressure, which are respectively recorded in time series in the recording means, information about the fuel consumption and information about the carbon dioxide emissions, and estimated information about the work situation; A program for executing the above on one computer or distributed across multiple computers.

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