Diesel fire pump and automatic non-damage inspection control method thereof

Abstract

This application relates to the field of intelligent inspection technology for fire pumps, and particularly to a diesel engine fire pump and its automatic non-destructive inspection control method. The method includes: acquiring reference pulse information; wherein the reference pulse information reflects current pulses that cannot cause macroscopic angular displacement of the crankshaft of the diesel engine; in response to a detection operation corresponding to the reference pulse information, acquiring detection information corresponding to each detection operation; determining a first characteristic parameter and a second characteristic parameter based on the detection information; and determining a control strategy for controlling the diesel engine fire pump based on the first characteristic parameter and the second characteristic parameter. The automatic non-destructive inspection control method for diesel engine fire pumps provided by this application can reduce the possibility that the diesel engine fire pump will fail to start due to wear accumulation during a real fire alarm, caused by cold start wear during automatic inspection.

Description

Technical Field

[0001] This application belongs to the field of intelligent inspection technology for fire pumps, and particularly relates to a diesel engine fire pump and its automatic non-destructive inspection control method. Background Technology

[0002] Diesel engine fire pumps are core equipment for ensuring the reliability of fire water supply systems in high-rise buildings, petrochemical plants, power plants, and large warehouses. According to relevant fire safety regulations, fire pump sets must be inspected regularly to ensure they can reliably start and operate in emergencies.

[0003] In related technologies, the currently prevalent automatic inspection solution in the industry is timed start-up inspection. This involves automatically starting the diesel engine according to a preset cycle via a controller, allowing it to run unloaded or under load for a period of time before shutting down. While this method solves the problem of missed manual inspections, approximately 80% of the wear on the moving parts of a diesel engine occurs during the cold start phase. During each cold start inspection, the engine oil has not yet fully reached the surfaces of the friction pairs, leaving critical components such as the crankshaft, connecting rod, and piston in a state of boundary lubrication or even dry friction, resulting in irreversible cumulative wear. If calculated based on weekly inspections, a diesel engine fire pump with a designed lifespan of twenty years will be forced to undergo more than a thousand cold start wear cycles throughout its entire lifespan, severely shortening the equipment's lifespan and potentially causing it to fail to start due to wear accumulation during a real fire, thus preventing it from providing firefighting assistance at critical moments and endangering the lives and property of users. Summary of the Invention

[0004] This application provides a diesel engine fire pump and its automatic non-destructive inspection control method, which can improve the problem that the diesel engine fire pump is more likely to fail to start due to wear accumulation during the actual fire alarm process due to cold start wear during the automatic inspection process.

[0005] In a first aspect, embodiments of this application provide a diesel engine fire pump and its automatic non-destructive inspection control method, including: Acquire reference pulse information; wherein, the reference pulse information is used to reflect current pulses that cannot cause macroscopic angular displacement of the crankshaft of the diesel engine; In response to the detection operation corresponding to the reference pulse information, detection information corresponding to each detection operation is acquired; wherein, the detection operation is an operation of applying the reference pulse information to the starter motor of the diesel engine in a stationary and fuel injection prohibited state, and the detection information is used to reflect the transient current response waveform of the starter motor under the detection operation; Based on the detection information, a first feature parameter and a second feature parameter are determined; wherein, the first feature parameter is used to reflect the proportion of valid operating status data that was not completely extracted in multiple detection operations, and the second feature parameter includes a feature to reflect the degree of influence of the inherent electrical characteristics of the motor on the operating status data and a feature to reflect the degree of influence of non-steady-state transient distortion on the operating status data; Based on the first characteristic parameter and the second characteristic parameter, a control strategy for controlling the diesel engine fire pump is determined.

[0006] The technical solutions described in this application embodiment have at least the following technical effects: The diesel engine fire pump and its automatic non-destructive inspection control method provided in this application first acquire reference pulse information to reflect current pulses that cannot cause macroscopic angular displacement of the crankshaft of the diesel engine. Then, in response to the operation of applying the reference pulse information to the starter motor of the diesel engine in a stationary and prohibited fuel injection state, a detection operation is performed to reflect the transient current response waveform of the starter motor under the detection operation. Detection information corresponding to each detection operation is acquired to reflect the transient current response waveform of the starter motor under the detection operation. Based on the detection information, a first feature parameter is determined to reflect the proportion of effective operating state data that was not completely extracted in multiple detection operations, and a second feature parameter is determined to reflect the degree of influence of the inherent electrical characteristics of the motor on the operating state data and the degree of influence of non-steady-state transient distortion on the operating state data. Finally, a control strategy for controlling the diesel engine fire pump is determined using the first feature parameter and the second feature parameter.

[0007] This method effectively avoids the contradiction between assessing equipment start-up capability and consuming equipment start-up life by detecting pulses that fail to induce macroscopic angular displacement of the crankshaft. This ensures that high-frequency inspections no longer come at the expense of diesel engine life, completely eliminating the cumulative cold-start wear problem that has long existed in traditional timed start-up inspection schemes. Furthermore, this method utilizes the synergistic analysis of the first and second characteristic parameters. This two-dimensional decomposition logic effectively reduces the problem of misjudging short-term random fluctuations as long-term deterioration trends, resulting in a more refined and accurate characterization of equipment health status. It also eliminates the need to wait for the concentration or status value to remain within a stable range for a confirmation period after each inspection, significantly improving the decision-making efficiency of a single inspection.

[0008] In one possible implementation of the first aspect, determining the first feature parameter and the second feature parameter based on the detection information includes: Based on the detection information, operating status data is determined; wherein, the operating status data is used to reflect the data in the detection information used to characterize the electrical performance of the starter motor; Based on each detection information and the corresponding running status data, the multiple detection information are divided into complete execution data and incomplete execution data; wherein, the complete execution data is used to reflect the detection information when the running status data is completely extracted from the multiple detection information, and the incomplete execution data is used to reflect the detection information when the running status data is not completely extracted from the multiple detection information; Based on the complete execution data and the total number of executions, the first feature parameter is determined; Based on the complete execution data, the incomplete execution data, and the detection information, the second feature parameter is determined.

[0009] In one possible implementation of the first aspect, determining the operating status data based on the detection information includes: Based on the detection information, a symbol data chain is determined; wherein the symbol data chain is used to reflect the stability change of the transient current in the detection information; Based on the symbol data chain, the operating status data is determined from the detection information.

[0010] In one possible implementation of the first aspect, determining the symbol data chain based on the detection information includes: Based on the detection information, an average current value and multiple adjacent current changes are determined; wherein, the average current value refers to the average value of all transient currents in the detection information, and the adjacent current changes refer to the differences between adjacent transient currents in the detection information. Based on the detection information and the average current value, multiple reference current changes are determined; wherein, the reference current change refers to the difference between each transient current in the detection information and the average current value; A symbolic data chain is constructed in chronological order from multiple comparison values ​​determined by multiple adjacent current changes and multiple reference current changes.

[0011] In one possible implementation of the first aspect, determining the runtime status data from the detection information based on the symbol data chain includes: Based on the symbolic data chain, a data change trend is determined; wherein, the data change trend is used to reflect the degree of change of the data of the chain nodes in the symbolic data chain over time; Based on the data change trend, a first timing point and a second timing point are determined; wherein, the first timing point refers to the time point corresponding to the first decline of the data change trend, and the second timing point refers to the time point corresponding to the second decline of the data change trend; Based on the time interval determined by the first timing and the second timing, the corresponding operating status data is determined from the detection information.

[0012] In one possible implementation of the first aspect, determining the second feature parameter based on the complete execution data, the incomplete execution data, and the detection information includes: Based on the complete execution data, the incomplete execution data, and the detection information, the steady-state influence degree and the transient influence degree are determined; wherein, the steady-state influence degree is used to reflect the degree of influence of the inherent electrical characteristics of the motor on the operating status data, and the transient influence degree is used to reflect the degree of influence of non-steady-state transient distortion on the operating status data; The steady-state influence degree and the transient influence degree are jointly determined as the second characteristic parameter.

[0013] In one possible implementation of the first aspect, determining the steady-state impact degree and the transient impact degree based on the complete execution data, the incomplete execution data, and the detection information includes: Based on the complete execution data, the running status data corresponding to the complete execution data is extracted from the detection information; Based on the operating status data, a first variance and a mean current are determined; wherein, the first variance is used to reflect the variance between the operating status data corresponding to the complete execution data, and the mean current is used to reflect the average current between the operating status data corresponding to the complete execution data. Based on the incomplete execution data, a second variance is determined; wherein the second variance is used to reflect the variance of the incomplete execution data; The ratio of the first variance to the mean current is determined as the steady-state influence, and the ratio of the second variance to the mean current is determined as the transient influence.

[0014] In one possible implementation of the first aspect, determining the control strategy for controlling the diesel engine fire pump based on the first characteristic parameter and the second characteristic parameter includes: The difference between the steady-state influence degree of the second feature parameter and the first data determined by the first feature parameter, and the transient influence degree of the second feature parameter and the second data determined by the first feature parameter, is identified as the influence degree value; wherein, the influence degree value is used to reflect the degree of influence of the change in the number of complete executions on the change in the running state data; Based on the aforementioned impact level value, a control strategy is determined.

[0015] In one possible implementation of the first aspect, determining the control strategy based on the degree of influence value includes: The comparison result, determined by comparing the influence level value with the preset availability threshold, outputs a health level characterizing the health status of the starter motor. When the health level indicates that the starter motor is in a slightly deteriorated state, the first strategy of the control strategy is executed; the first strategy includes adjusting the application frequency of the reference pulse information and displaying the corresponding level prompt information on the local human-machine interface; When the health level indicates that the starter motor is in a moderately deteriorated state, in addition to executing the first strategy, the routine load start inspection is prohibited. When the health level indicates that the starter motor is in a critical fault state, the second strategy of the control strategy is executed; the second strategy includes immediately locking all automatic start functions of the diesel engine fire pump and remotely alarming.

[0016] Secondly, embodiments of this application provide an automatic non-destructive inspection control system for diesel engine fire pumps, comprising: An acquisition unit is used to acquire reference pulse information; wherein the reference pulse information is used to reflect current pulses that cannot cause macroscopic angular displacement of the crankshaft of the diesel engine; The detection unit is used to respond to the detection operation corresponding to the reference pulse information and acquire detection information corresponding to each detection operation; wherein, the detection operation is an operation of applying the reference pulse information to the starter motor of the diesel engine in a stationary and fuel injection prohibited state, and the detection information is used to reflect the transient current response waveform of the starter motor under the detection operation; An analysis unit is used to determine a first feature parameter and a second feature parameter based on the detection information; wherein, the first feature parameter is used to reflect the proportion of valid operating status data that was not completely extracted in multiple detection operations, and the second feature parameter includes a feature to reflect the degree of influence of the inherent electrical characteristics of the motor on the operating status data and a feature to reflect the degree of influence of non-steady-state transient distortion on the operating status data; The decision unit is used to determine a control strategy for controlling the diesel engine fire pump based on the first feature parameter and the second feature parameter.

[0017] Thirdly, embodiments of this application provide a diesel engine fire pump, including a diesel engine fire pump body and a control device. The non-destructive inspection device is electrically connected to the control device. The control device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the method described in any of the first aspects above.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any of the first aspects above.

[0019] Fifthly, embodiments of this application provide a computer program that, when running on the control equipment of a diesel engine fire pump, causes the control equipment of the diesel engine fire pump to execute the automatic non-destructive inspection control method for the diesel engine fire pump described in any of the first aspects above.

[0020] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating an embodiment of the automatic non-destructive inspection control method for diesel engine fire pumps provided in this application. Figure 2 This is a schematic diagram illustrating the implementation process of an automatic non-destructive inspection control method for diesel engine fire pumps provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an automatic non-destructive inspection control system for diesel engine fire pumps provided in one embodiment of this application; Figure 4 This is a schematic diagram of the structure of a diesel engine fire pump provided in one embodiment of this application; Figure 5 This is a schematic diagram of the structure of a control device for a diesel engine fire pump provided in one embodiment of this application; The following are the labeling elements in the figure: 100. Diesel engine fire pump; 110. Diesel engine fire pump body; 120. Control equipment. Detailed Implementation

[0023] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0024] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0025] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0026] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0027] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0028] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0029] In related technologies, the currently widely adopted automatic inspection solution in the industry is timed start-up inspection. This involves automatically starting the diesel engine according to a preset cycle via a controller, allowing it to run unloaded or under load for a period of time before shutting down. While this method solves the problem of manual forgetting of inspections, approximately 80% of the wear on the moving parts of a diesel engine occurs during the cold start phase. During each cold start inspection, the engine oil has not yet fully reached the surfaces of all friction pairs, leaving critical components such as the crankshaft, connecting rod, and piston in a state of boundary lubrication or even dry friction, resulting in irreversible cumulative wear. If calculated based on weekly inspections, a diesel engine fire pump with a design life of twenty years will be forced to undergo more than a thousand or even more cold start wear cycles throughout its entire lifespan. This severely shortens the equipment's lifespan and may even cause it to fail to start due to wear accumulation during a real fire, thus preventing it from providing firefighting assistance at critical moments and endangering the lives and property of users.

[0030] To address the aforementioned problems, this application provides a diesel engine fire pump and its automatic non-destructive inspection control method. This method first acquires reference pulse information reflecting current pulses that cannot cause macroscopic angular displacement of the diesel engine's crankshaft. Then, in response to the reference pulse information, a detection operation is performed to apply the reference pulse information to the starter motor of the diesel engine, which is stationary and in a state where fuel injection is prohibited. This operation reflects the transient current response waveform of the starter motor under the detection operation. Detection information is acquired corresponding to each detection operation, reflecting the transient current response waveform of the starter motor under the detection operation. Based on the detection information, a first characteristic parameter reflecting the proportion of incomplete extraction of effective operating state data in multiple detection operations and a second characteristic parameter including the degree of influence of the motor's inherent electrical characteristics on the operating state data and the degree of influence of non-steady-state transient distortion on the operating state data are determined. Finally, a control strategy for controlling the diesel engine fire pump is determined using the first and second characteristic parameters.

[0031] This method effectively avoids the contradiction between assessing equipment start-up capability and consuming equipment start-up life by detecting pulses that fail to induce macroscopic angular displacement of the crankshaft. This ensures that high-frequency inspections no longer come at the expense of diesel engine life, completely eliminating the cumulative cold-start wear problem that has long existed in traditional timed start-up inspection schemes. Furthermore, this method utilizes the synergistic analysis of the first and second characteristic parameters. This two-dimensional decomposition logic effectively reduces the problem of misjudging short-term random fluctuations as long-term deterioration trends, resulting in a more refined and accurate characterization of equipment health status. It also eliminates the need to wait for the concentration or status value to remain within a stable range for a confirmation period after each inspection, significantly improving the decision-making efficiency of a single inspection.

[0032] The automatic non-destructive inspection control method for diesel engine fire pumps provided in this application embodiment can be applied to the control equipment of diesel engine fire pumps. In this case, the control equipment of the diesel engine fire pump is the executing subject of the automatic non-destructive inspection control method for diesel engine fire pumps provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of control equipment for diesel engine fire pumps.

[0033] The diesel engine fire pump includes the main body of the diesel engine fire pump and control equipment. The main body of the diesel engine fire pump is electrically connected to the control equipment. The control equipment includes a monitoring device group and a control unit, with the monitoring device group integrated into the control unit. The monitoring device group includes a pulse generation module, a control switch module, and a current waveform acquisition module. The pulse generation module is used to generate reference pulse information; for example, the pulse generation module can be a pulse generator capable of generating precise pulse width and amplitude. The control switch module is electrically connected to both the pulse generation module and the starter motor of the diesel engine. The control switch module is used to apply a current pulse corresponding to the reference pulse information to the starter motor of the diesel engine, which is in a stationary state and prohibited from fuel injection, to perform a detection operation; for example, the control switch module can be a solid-state relay or a high-power MOSFET switching circuit. The current waveform acquisition module is electrically connected to the starter motor. The current waveform acquisition module is used to acquire the transient current response waveform of the starter motor during each detection operation and generate detection information corresponding to each detection operation; for example, the current waveform acquisition module can be a current probe based on a Hall effect sensor combined with a high-speed data acquisition card. The control device can be a programmable logic controller (PLC), a distributed control system (DCS), or an industrial computer (IPC) equipped with a dedicated control program, etc.

[0034] To better understand the automatic non-destructive inspection and control method for diesel engine fire pumps provided in this application embodiment, the specific implementation process of the automatic non-destructive inspection and control method for diesel engine fire pumps provided in this application embodiment will be described by way of example below.

[0035] Figure 1 and Figure 2 A schematic flowchart of the automatic non-destructive inspection control method for diesel engine fire pumps provided in this application embodiment is shown. Please refer to [link / reference]. Figure 1 and Figure 2 The automatic non-destructive inspection and control method for diesel engine fire pumps includes: S100, acquire reference pulse information; wherein, the reference pulse information is used to reflect current pulses that cannot cause macroscopic angular displacement of the crankshaft of the diesel engine.

[0036] It can be understood that the reference pulse information refers to a precisely defined electrical excitation signal, the core characteristic of which is that the energy of the current pulse is controlled at an extremely low level. When the diesel engine is stationary, if the energy of the current pulse applied to the starter motor is too high, it will cause observable rotational displacement of the crankshaft, thus triggering mechanical operation of the diesel engine. However, the current pulse corresponding to the reference pulse information is set with an amplitude and duration insufficient to overcome the static inertia of the diesel engine, therefore it cannot cause any macroscopic angular displacement of the crankshaft. The reference pulse information can be manually input or calibrated experimentally by gradually increasing the pulse current width applied to the starter motor while using a high-precision angular displacement sensor to monitor the crankshaft position. When the crankshaft begins to exhibit measurable minute rotation, the corresponding pulse energy threshold is recorded. Based on this pulse energy threshold, a preset proportion of this threshold is used as the upper limit of the reference pulse information's energy, ensuring that all subsequent detection operations are performed without causing any mechanical action in the diesel engine. The preset proportion can be manually input.

[0037] S200, in response to the detection operation corresponding to the reference pulse information, acquires the detection information corresponding to each detection operation; wherein, the detection operation refers to the operation of applying reference pulse information to the starter motor of the diesel engine which is in a stationary state and prohibited from fuel injection, and the detection information is used to reflect the transient current response waveform of the starter motor under the detection operation.

[0038] It can be understood that the detection operation is a standardized pulse excitation process performed when the diesel engine is in a specific state. The static state refers to the diesel engine's crankshaft completely stopping rotation, and the fuel injection prohibition state refers to the diesel engine's fuel injection system being electrically locked, preventing fuel injection into the cylinders even in unexpected situations. Under these dual safety conditions, the control system repeatedly applies reference pulse information to the starter motor's excitation winding or armature circuit according to preset time intervals or trigger conditions. After each application of the reference pulse information, the starter motor's electrical system generates a transient current response due to the pulse excitation. The shape, amplitude attenuation characteristics, and oscillation frequency of this response waveform are closely related to the starter motor's internal winding state, insulation performance, connection reliability, and other electrical characteristics. The detection information is the waveform data of this transient current changing over time, acquired by a high-precision current sensor at a sampling frequency no less than a preset frequency.

[0039] S300, based on the detection information, determine the first feature parameter and the second feature parameter; wherein, the first feature parameter is used to reflect the proportion of valid operating status data that was not completely extracted in multiple detection operations, and the second feature parameter includes the degree of influence of the inherent electrical characteristics of the motor on the operating status data and the degree of influence of non-steady-state transient distortion on the operating status data.

[0040] It is understandable that in repeated testing operations, not every piece of information can be successfully parsed to extract physically meaningful operational status data. Due to factors such as intermittent poor contact in the starter motor's internal electrical connections, external electromagnetic interference, or voltage fluctuations in the power supply bus during pulse application, the transient current response waveforms extracted from some testing information may be severely distorted, making it impossible to extract valid data representing the motor's true electrical characteristics. The first characteristic parameter quantifies the proportion of such invalid detections; a higher value indicates a more unstable electrical connection or external environment for the starter motor. On the other hand, even for detections that successfully extract operational status data, this data still contains two different sources of influence: one is a long-term, repeatable influence, stemming from the inherent, relatively stable electrical characteristics of the motor; the other is a random, non-repeatable influence caused by unsteady transient distortions (such as random contact noise between the carbon brushes and commutator, or external transient electromagnetic interference). The second characteristic parameter quantifies these two influences separately, providing a basis for distinguishing between stable degradation and random anomalies.

[0041] For example, detection information can be used to determine data reflecting the electrical performance of the starter motor. Then, for each piece of detection information and its corresponding data reflecting the electrical performance of the starter motor, the multiple detection information can be divided into detection information reflecting when operational status data is completely extracted from multiple detection information and detection information reflecting when operational status data is not completely extracted from multiple detection information. Finally, based on the completely extracted data and the total number of executions reflecting all detection operations, a first feature parameter is determined, and a second feature parameter is determined based on the completely extracted data, the incompletely extracted data, and the detection information. Alternatively, the detection information can be input into a learning model, which outputs the corresponding first and second feature parameters. The training process of the learning model can use the data after processing the detection information and the corresponding first and second feature parameters as the training dataset, and then input the training dataset into the learning model for training, ultimately obtaining the learning model. And so on, but not limited to these examples.

[0042] In one possible implementation, in step S300, determining the first feature parameter and the second feature parameter based on the detection information includes: S310, Based on the detection information, determine the operating status data; wherein, the operating status data is used to reflect the data in the detection information used to characterize the electrical performance of the starter motor.

[0043] It is understandable that operational status data is a key indicator that directly characterizes the current electrical performance of the starter motor, obtained from raw detection information through signal processing and feature extraction. The raw waveform data contains a large amount of redundant information and noise, requiring algorithmic processing to extract physically meaningful parameters. It is important to note that for a healthy starter motor, under a fixed reference pulse excitation, the peak current of its transient current response waveform should be stable within a relatively narrow range, and the decay time constant should also meet the factory design value.

[0044] For example, the stability change reflecting the transient current in the detection information can be determined using the detection information, and then the operating status data can be determined from the detection information based on this stability change. Alternatively, the detection information can be input into a learning model, and the learning model can output the corresponding operating status data, and so on, but it is not limited to these methods.

[0045] In one possible implementation, in step S310, based on the detection information, the operating status data is determined, including: S311, Based on the detection information, determine the symbol data link; wherein, the symbol data link is used to reflect the stability change of the transient current in the detection information.

[0046] Symbolic data links (SCRs) can be understood as the process of converting the original transient current response waveform into a sequence of discrete symbols (e.g., +1, 0, -1). A stable, expected transient response waveform generates a relatively regular symbol sequence, while a distorted waveform generates a chaotic one. The SCR compares the current value at each sampling point in the original waveform with a reference value (such as a local mean or the value from the previous moment) and assigns a symbol based on the comparison result. A +1 is assigned when the current value increases, a -1 when it decreases, and a 0 when it remains unchanged. This generated symbol sequence eliminates the influence of the absolute current amplitude, retaining only the pattern information of the waveform changes, thus reflecting the stability of the transient current more purely. For example, the average value of all transient currents in the detection information can be determined from the detection information, along with the difference between adjacent transient currents in the detection information. Then, based on the detection information and this average value, the difference between each transient current in the detection information and this average value can be determined. Finally, the ratios between the differences between adjacent transient currents in multiple detection information sets and this average value can be constructed into a symbolic data chain in chronological order. Alternatively, the detection information can be input into a learning model, and the learning model can output the corresponding symbolic data chain, and so on, but it is not limited to these methods.

[0047] In one possible implementation, step S311, determining the symbol data chain based on the detection information, includes: S3111, based on the detection information, determine the average current value and multiple adjacent current changes; where the average current value refers to the average value of all transient currents in the detection information, and the adjacent current changes refer to the difference between adjacent transient currents in the detection information.

[0048] It is understandable that for a detection data point containing N sampling points, the arithmetic mean of the current values ​​at these N sampling points is first calculated as the average current value for that detection. Simultaneously, for every two adjacent sampling points on the waveform, the difference between the current value of the latter sampling point and the current value of the former sampling point is calculated to obtain the adjacent current change value.

[0049] S3112, based on the detection information and the average current value, determines multiple reference current changes; wherein, the reference current change refers to the difference between each transient current and the average current value in the detection information.

[0050] It can be understood that for each sampling point in the detection information, the current value is compared with the average current value to obtain a set of reference current change sequences. Reference current change = current value corresponding to each sampling point in the detection information - average current value.

[0051] S3113, based on multiple comparison values ​​determined by multiple adjacent current changes and multiple reference current changes, is constructed into a symbol data chain in chronological order.

[0052] It can be understood that the construction process of the symbol data chain involves comprehensively comparing adjacent current changes with the reference current change. For each sampling point, the difference between its corresponding adjacent current change and the reference current change at that point is calculated. Based on the comparison results, the symbols corresponding to all sampling points are arranged in chronological order, thus forming the symbol data chain.

[0053] This setup, by calculating the average value and adjacent differences, provides two reference benchmarks at different scales for the subsequent symbolization process. The average value reflects the global center, while the adjacent differences reflect local dynamics. The variation in the reference current describes the deviation of each point on the waveform from the overall mean, providing a global comparison benchmark for subsequent symbolization. The symbol data chain constructed through dual comparisons reflects both the instantaneous dynamics of the current waveform and its position relative to the overall level, thus enabling a more comprehensive and accurate characterization of the waveform's stability and variation patterns.

[0054] S312, based on the symbolic data link, determines the operating status data from the detection information.

[0055] It's understandable that the symbolic data link records the changing patterns of the current waveform, while the operating status data is the raw current data within a specific physically meaningful time interval identified from the symbolic data link. Not all parts of the entire symbolic data link are used to extract operating status data. Because the electrical system of the starting motor may experience a brief initial oscillation caused by parasitic capacitance and inductance at the initial moment of pulse application, this data cannot accurately reflect the electrical characteristics of the motor itself. Therefore, it is necessary to analyze the changing patterns of the symbolic data link to identify the start and end points of the waveform entering the stable response phase. When the symbolic data link changes from initial high-frequency alternation to regular, monotonic changes, it signifies that the transient process has entered the main response phase, and the corresponding raw current data at this point can be used as the operating status data.

[0056] This setup, through symbolic processing, simplifies complex, high-dimensional analog waveform data into low-dimensional, highly interference-resistant symbol sequences, making subsequent quantitative analysis of current stability simpler and more robust. By guiding the extraction of operating status data through symbolic data chains, non-characteristic segments in the waveform can be automatically and intelligently removed, ensuring that the extracted data truly and accurately represents the core electrical characteristics of the starter motor.

[0057] In one possible implementation, in step S312, based on the symbolic data chain, the running status data is determined from the detection information, including: S3121, Based on the symbolic data chain, determine the data change trend; wherein, the data change trend is used to reflect the degree of change of the data of the chain nodes in the symbolic data chain over time.

[0058] It can be understood that the symbolic data chain itself is a sequence of discrete symbols, which is transformed from the corresponding comparative value data, and the data change trend is the degree of change of the data of each chain node of the comparative value data sequence corresponding to the symbolic data chain over time.

[0059] S3122, Based on the data change trend, determine the first timing point and the second timing point; wherein, the first timing point refers to the time point corresponding to the first decline in the data change trend, and the second timing point refers to the time point corresponding to the second decline in the data change trend.

[0060] It is understandable that at the initial moment of applying the reference pulse, the electrical system of the starting motor has not yet fully established a response. At this time, the transient current waveform may contain high-frequency oscillations caused by distributed capacitance and inductor resonance, and the corresponding data change trend will be at a relatively high value. As the oscillation decays rapidly, the response waveform will enter an exponential rise or fall phase mainly determined by the motor winding resistance and inductance. At this time, the waveform change pattern tends to stabilize, and the data change trend will experience the first significant drop. This time point is the first opportunity. As the detection operation proceeds, when the response process approaches a steady state, the current change amplitude further decreases, the change pattern tends to be constant, and the data change trend will experience the second significant drop. This time point is the second opportunity.

[0061] S3123, based on the time interval determined by the first timing and the second timing, determine the corresponding operating status data from the detection information.

[0062] It can be understood that the time interval determined by the first and second timing points (i.e., the time period between the first and second timing points) corresponds to the stable main response stage in the transient current response waveform that best represents the inherent electrical characteristics of the starting motor. Within this interval, the non-characteristic high-frequency oscillations caused by the initial excitation have basically disappeared, while the response waveform has not yet fully entered the steady-state stage where changes can be ignored. Therefore, the original current sampling data within this interval can be extracted and used as operating status data.

[0063] This configuration transforms the discrete symbol sequence into a continuous trend indicator, enabling quantitative assessment of the overall stability of the transient current waveform in the detection information and providing a basis for identifying key time points. Through automatic analysis of data trends, the start and end points of the main response phase in the transient current response waveform can be accurately located without manual intervention, providing precise time window boundaries for subsequent data extraction. By accurately extracting the intermediate stable segment of the waveform, early oscillation artifacts and later saturation segments are eliminated, resulting in operational status data with optimal signal quality and the highest physical correlation for subsequent analysis.

[0064] S320, based on each detection information and the corresponding running status data, divides multiple detection information into complete execution data and incomplete execution data; among them, complete execution data is used to reflect the detection information when running status data is completely extracted from multiple detection information, and incomplete execution data is used to reflect the detection information when running status data is not completely extracted from multiple detection information.

[0065] It is understandable that after processing each piece of detection information, the system attempts to extract runtime status data from it. The completeness of the extraction process depends on whether the corresponding runtime status data can be extracted. If, after processing, the runtime status data corresponding to a particular detection information can be completely extracted, then that detection information is marked as complete execution data. Conversely, if the runtime status data corresponding to that detection information cannot be completely extracted, then that detection information is marked as incomplete execution data.

[0066] S330, based on complete execution data and total number of executions, determine the first characteristic parameter.

[0067] It is understandable that the first feature parameter is used to quantify the proportion of valid runtime data successfully extracted in multiple detection operations. First, the total number of executions within a preset detection period is counted, and then the number of times within that period is marked as complete execution data is counted. The first feature parameter can be characterized by the ratio of the number of complete executions to the total number of executions.

[0068] S340, based on complete execution data, incomplete execution data, and detection information, determine the second feature parameter.

[0069] For example, the degree of influence of the inherent electrical characteristics of the motor on the operating status data and the degree of influence of non-steady-state transient distortion on the operating status data can be determined by using complete execution data, incomplete execution data, and detection information. These two degrees of influence can then be jointly identified as the second feature parameter. Alternatively, complete execution data, incomplete execution data, and detection information can be input into the learning model, and the learning model can output the corresponding second feature parameter, and so on, but not limited to these methods.

[0070] This setup transforms the high-dimensional, high-noise raw waveform data into low-dimensional, high-signal-to-noise ratio physical characteristic parameters, significantly improving the efficiency and accuracy of subsequent analysis. By filtering the raw detection information for validity, reliable data suitable for subsequent health analysis is distinguished from invalid data caused by various interferences, providing a direct data source for the calculation of the first characteristic parameter. The first characteristic parameter directly reflects the stability of the detection system itself and the reliability of the starter motor's electrical connection, providing a quantitative basis for determining whether to adjust the inspection frequency or perform hardware checks. By processing valid and abnormal data separately, the second characteristic parameter is decomposed into two components with clear physical meanings, providing technical support for subsequently distinguishing between natural aging of the motor and sudden electrical faults.

[0071] In one possible implementation, in step S340, the second feature parameter is determined based on the complete execution data, the incomplete execution data, and the detection information, including: S341, based on complete execution data, incomplete execution data, and detection information, determine the steady-state influence degree and the transient influence degree; wherein, the steady-state influence degree is used to reflect the degree of influence of the inherent electrical characteristics of the motor on the operating status data, and the transient influence degree is used to reflect the degree of influence of non-steady-state transient distortion on the operating status data; It is understandable that for multiple tests marked as fully executed, the differences between their corresponding operational status data have two aspects. First, there is the slow change in the inherent electrical characteristics of the starting motor itself, which has steady-state and long-term characteristics, known as the steady-state effect. Second, there is the short-term, non-repetitive distortion introduced each time a pulse is applied due to random changes in the external electromagnetic environment, power supply bus voltage ripple, or the instantaneous contact state between the motor's internal carbon brushes and commutator. This effect has transient and random characteristics, known as the transient effect. For data marked as not fully executed, it represents an extreme case where the transient distortion is severe enough to compromise data integrity; therefore, its data characteristics can be used to help quantify the degree of transient effect.

[0072] For example, operational status data corresponding to the complete execution data can be extracted from the detection information using complete execution data. Then, based on this corresponding operational status data, the variance reflecting the differences between the operational status data corresponding to the complete execution data and the average current value reflecting these differences can be determined. Next, using incomplete execution data, the variance reflecting the incomplete execution data can be determined. Finally, the ratio of the variance between the operational status data corresponding to the complete execution data to the average current value is confirmed as the steady-state influence level, and the ratio of the variance of the incomplete execution data to the average current value is confirmed as the transient influence level. Alternatively, complete execution data, incomplete execution data, and detection information can be input into a learning model, and the learning model can output the corresponding steady-state influence level and transient influence level, etc., but not limited to these methods.

[0073] In one possible implementation, in step S341, based on complete execution data, incomplete execution data, and detection information, the steady-state impact degree and the transient impact degree are determined, including: S3411, based on complete execution data, extracts the running status data corresponding to the complete execution data from the detection information.

[0074] It is understandable that, based on the identification of all complete execution data, the corresponding runtime status data is retrieved from the stored original detection information database according to the unique identifier of each complete execution data. This data constitutes an array set, where each element represents a current waveform segment of the stable main response stage obtained from a successful detection.

[0075] S3412, Based on the operating status data, determine the first variance and the mean current; wherein, the first variance is used to reflect the variance between the operating status data corresponding to the complete execution data, and the mean current is used to reflect the average current between the operating status data corresponding to the complete execution data.

[0076] It can be understood that, for each sampling point, the average current value of all complete execution data at that location is calculated to obtain an average current curve, and the variance at each location is calculated to obtain a variance curve. The variance values ​​across the entire variance curve are then averaged to obtain the first variance. The mean current is obtained by averaging all time points on the average current curve to obtain a global average current value.

[0077] S3413, Determine the second variance based on the incomplete execution data; wherein the second variance is used to reflect the variance of the incomplete execution data.

[0078] It is understandable that for detection information marked as incomplete execution, since the running state data of the rule cannot be extracted, it is impossible to calculate its variance in the time domain using the same method as in step S3412. However, it should be noted that the original transient current response waveform of the incomplete execution data can still provide quantification information. That is, energy calculation or statistical feature extraction can be performed on the original waveform of the incomplete execution data to calculate the variance of the waveform sequence of each incomplete execution data. Then, the variance values ​​of all incomplete execution data are averaged to obtain the second variance.

[0079] S3414, the ratio of the first variance to the mean current is identified as the steady-state influence, and the ratio of the second variance to the mean current is identified as the transient influence.

[0080] It is understandable that dividing the first variance by the mean current yields a dimensionless ratio. This ratio eliminates the influence of the absolute current level and purely characterizes the relative stability of the inherent electrical characteristics, i.e., the degree of steady-state influence. The smaller the degree of steady-state influence, the more stable the inherent electrical characteristics of the motor. Dividing the second variance by the mean current yields a dimensionless ratio, i.e., the degree of transient influence. This setup associates the labels of complete execution data with their corresponding specific numerical data, providing a standard input dataset for subsequent statistical calculations. The first variance measures the consistency between multiple successful tests; a smaller value indicates more stable inherent electrical characteristics of the motor. The mean current provides a reference scale for normalizing subsequent ratios. The steady-state impact quantifies the consistency of the motor's inherent characteristics across multiple tests in a relative proportion, providing a standardized indicator for state comparisons across motors and lifecycles. The second variance quantifies the intensity of non-steady-state transient distortions from the perspective of the internal disorder of incomplete data, providing a basis for calculating the transient impact. The transient impact quantifies the severity of random disturbances and intermittent contact problems in a standardized form, facilitating direct comparison and comprehensive evaluation with the steady-state impact.

[0081] S342, the steady-state influence degree and the transient influence degree are jointly determined as the second characteristic parameter.

[0082] It is understandable that the steady-state influence and the transient influence are two different dimensions of indicators. The former reflects the stability of the long-term evolution of the motor's health state, while the latter reflects the anti-interference capability of the detection process and the reliability of the electrical connection. Combining these two indicators constitutes the complete second characteristic parameter.

[0083] This configuration further breaks down the second characteristic parameter into two sub-components with different physical mechanisms, which helps to accurately diagnose the root cause of the fault, whether it is motor aging, poor connection, or severe interference. The second characteristic parameter simultaneously characterizes the inherent state of the equipment and the interference of the operating environment in a quantitative form, providing comprehensive data support for the hierarchical decision-making of subsequent control strategies.

[0084] S400 determines a control strategy for controlling a diesel engine fire pump based on a first characteristic parameter and a second characteristic parameter.

[0085] It can be understood that the control strategy refers to a set of control plans that dynamically adjust the subsequent operating mode, inspection behavior and alarm output of the equipment based on the actual health status of the starter motor in the diesel engine fire pump.

[0086] For example, the strength of the steady convergence trend reflecting the complete execution data and the strength of the fluctuating divergence trend reflecting the incomplete execution data can be determined using the second feature parameter. Then, based on the difference between the strength of the steady convergence trend reflecting the complete execution data and the first data determined by the first feature parameter, and the strength of the fluctuating divergence trend reflecting the incomplete execution data and the second data determined by the first feature parameter, the degree of influence of the change in the number of complete executions on the change in the running state data can be confirmed. Finally, the corresponding control strategy is determined based on this degree of influence. Alternatively, the first and second feature parameters can be input into the learning model, and the learning model can output the corresponding control strategy, etc., but are not limited to these methods.

[0087] This setup enables the electrical condition of the starter motor to be monitored while the diesel engine is completely stationary and without any mechanical wear, achieving truly non-destructive inspection and reducing mechanical wear and fuel consumption caused by frequent diesel engine starts in traditional inspections. Through standardized, repeatable pulse excitation and synchronous acquisition, raw data that quantitatively characterizes the electrical health of the starter motor is obtained, providing a reliable information foundation for subsequent condition assessment. By constructing a two-dimensional feature parameter system, the reliability of the detection process itself is identified, and the inherent response and non-steady-state disturbances of the system are separated, laying the foundation for subsequent accurate condition assessment and control strategy selection. Executing a hierarchical control strategy based on the quantified feature parameters enables a shift from periodic inspections to condition-driven adaptive inspections, optimizing equipment operation and maintenance efficiency while ensuring safety and preventing fire pump start-up failures due to starter motor malfunctions.

[0088] In one possible implementation, in step S400, a control strategy for controlling the diesel engine fire pump is determined based on the first characteristic parameter and the second characteristic parameter, including: S410, the influence degree value is determined based on the steady-state influence degree of the second characteristic parameter and the first data determined by the first characteristic parameter, and the difference between the transient influence degree of the second characteristic parameter and the second data determined by the first characteristic parameter; wherein, the influence degree value is used to reflect the degree of influence of the change in the number of complete executions on the change in the running status data.

[0089] It can be understood that the first data is the product of the steady-state influence degree and the first characteristic parameter, and the second data is the product of the transient influence degree and the difference between 1 and the first characteristic parameter. The influence degree value is the difference between the first data and the second data.

[0090] S420, determine the control strategy based on the degree of impact value.

[0091] It is understandable that the numerical range of the impact level value can be divided into multiple intervals, each interval corresponding to a health level or operating state of the starter motor. Different health levels map to different control strategies. For example, it can be assumed that an impact level value greater than 0.7 is considered healthy, an impact level value between 0.4 and 0.7 is considered mild concern, an impact level value between 0.1 and 0.4 is considered a moderate warning, and an impact level value less than 0.1 is considered a serious fault. Based on this hierarchy, the system automatically executes the corresponding control strategies, such as maintaining inspection, increasing inspection frequency, limiting load-bearing starts, or locking all automatic start functions.

[0092] This setup, through a comprehensive quantitative index, unifies detection success rate, inherent stability, and random disturbances within a single framework, providing a concise and powerful decision-making basis for the final control strategy selection. By quantifying and grading the degree of influence, automated and intelligent decision-making for the control strategy is achieved. This enables timely warnings when early signs of performance degradation appear in the starter motor, and proactively cuts off dangerous operations in the event of a serious fault, thereby maximizing the reliability and safety of the diesel engine fire pump.

[0093] In one possible implementation, in step S430, a control strategy is determined based on the degree of influence value, including: S431, based on the comparison result determined by comparing the impact degree value with the preset availability threshold, outputs the health level used to characterize the health status of the starter motor.

[0094] Understandably, one or more availability thresholds need to be preset first. These thresholds can be set based on equipment manufacturer recommendations, historical data statistics, or the safety requirements of specific application scenarios. The calculated impact values ​​are then compared sequentially with these thresholds, and the health status of the starter motor is classified into different levels based on the comparison results. Each level corresponds to a clear qualitative description, such as "healthy," "caution," "warning," or "dangerous." The system outputs the health level, which can be displayed on a local monitor as text or icons, or uploaded to a remote monitoring center via a communication interface.

[0095] S432, when the health level indicates that the starter motor is in a slightly deteriorated state, execute the first strategy of the control strategy; the first strategy includes adjusting the application frequency of the reference pulse information and displaying the corresponding level prompt information on the local human-machine interface.

[0096] It is understandable that a slightly deteriorated state corresponds to a moderately low level of impact. At this point, although the starter motor's performance shows signs of decline, it can still operate normally under most conditions. The first strategy is a preventative and informational low-intensity intervention. Adjusting the application frequency of the reference pulse information is equivalent to increasing the inspection frequency (e.g., changing it to once every eight hours) to reduce unnecessary frequent electrical stress impacts on the already fragile electrical system. A yellow or corresponding level of warning message is displayed on the local human-machine interface (such as the display screen of an integrated industrial computer) to inform maintenance personnel that "the starter motor's performance has slightly declined; an inspection is recommended soon."

[0097] S433: When the health level indicates that the starter motor is in a moderately deteriorated state, in addition to implementing the first strategy, the routine load start inspection is prohibited.

[0098] It is understandable that a moderate degradation state corresponds to a lower impact level. At this point, the starter motor's performance has significantly decreased. Although pulse detection in a stationary state can still be partially performed, attempting a true load start (i.e., requiring the starter motor to rotate and ignite the diesel engine) carries a high risk of failure, potentially causing the fire pump to fail to start at a critical moment. Therefore, while continuing the first strategy (continuously performing non-destructive pulse detection to monitor the degradation trend and display warning messages), a critical safety restriction is added: the control system is prohibited from automatically executing or manually triggering routine load start inspections (i.e., a complete start test involving actual crankshaft rotation and attempted fuel injection ignition).

[0099] S434, when the health level indicates that the starter motor is in a critical fault state, execute the second strategy of the control policy; the second strategy includes immediately locking all automatic start functions of the diesel engine fire pump and remote alarm.

[0100] It is understandable that a severe fault state corresponds to an impact level below an extremely low threshold. This state indicates that the electrical characteristics of the starter motor are extremely unstable, the probability of successfully executing any form of automatic start (including non-destructive pulse detection during inspections) is extremely low, and continued application of any electrical pulses may exacerbate the fault or even trigger safety risks (such as short-circuit fire). The second strategy is a protective and intervention-based high-intensity action. When executing the second strategy, the control system first immediately locks all automatic start functions of the diesel engine fire pump, including but not limited to, linkage start from the fire alarm system, periodic automatic inspection start, and remote control start from the remote control center. At the same time, the system will send the highest priority alarm information (such as audible and visual alarms, SMS push notifications, and software pop-ups) to the designated remote monitoring center, duty personnel's mobile phones, or property management system.

[0101] This setup transforms abstract quantitative indicators into intuitive health levels through threshold comparisons, facilitating quick understanding of equipment status by on-site maintenance personnel and providing clear guidance for subsequent manual intervention. The first strategy, without interrupting the equipment's main functions, achieves adaptive response and early warning for mild degradation by adjusting detection density and issuing early warnings, helping to schedule maintenance in the early stages of a fault. Actively prohibiting high-risk load testing during moderate degradation reduces further equipment damage due to test failures and prevents loss of backup capacity due to erroneous testing while fire protection facilities are on standby, representing a reasonable balance between safety and monitoring needs. The second strategy, upon confirming that the starter motor can no longer operate safely and reliably, proactively cuts off all automatic control paths that could lead to dangerous actions and notifies relevant personnel of the fault information with maximum intensity, buying valuable time for emergency manual handling and repair, fundamentally preventing fire protection function failure due to equipment operating with defects.

[0102] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0103] Corresponding to the diesel engine fire pump automatic non-destructive inspection control method in the above embodiments, this application also provides an automatic non-destructive inspection control system for diesel engine fire pumps. Each module of the automatic non-destructive inspection control system for diesel engine fire pumps can realize each step of the automatic non-destructive inspection control method for diesel engine fire pumps. Figure 3 The diagram shows the structural block diagram of the automatic non-destructive inspection and control system for diesel engine fire pumps provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0104] Reference Figure 3 The automatic non-destructive inspection and control system for diesel engine fire pumps includes: The acquisition unit is used to acquire reference pulse information; wherein, the reference pulse information is used to reflect current pulses that cannot cause macroscopic angular displacement of the crankshaft of the diesel engine.

[0105] The detection unit is used to respond to the detection operation corresponding to the reference pulse information and acquire the detection information corresponding to each detection operation; wherein, the detection operation refers to the operation of applying the reference pulse information to the starter motor of the diesel engine in a stationary and prohibited fuel injection state, and the detection information is used to reflect the transient current response waveform of the starter motor under the detection operation.

[0106] The analysis unit is used to determine a first feature parameter and a second feature parameter based on the detection information. The first feature parameter reflects the proportion of valid operating status data that was not completely extracted in multiple detection operations. The second feature parameter includes parameters that reflect the degree of influence of the inherent electrical characteristics of the motor on the operating status data and the degree of influence of non-steady-state transient distortion on the operating status data.

[0107] The decision unit is used to determine the control strategy for controlling the diesel engine fire pump based on the first characteristic parameter and the second characteristic parameter.

[0108] It should be noted that the information interaction and execution process between the above systems / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0109] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0110] This application also provides a control device for a diesel engine fire pump. Figure 5 This is a schematic diagram of the structure of a control device 5 provided in an embodiment of this application. Figure 5 As shown, the control device 5 in this embodiment includes: at least one processor 50 ( Figure 5 Only one is shown in the image), at least one memory 51 ( Figure 5 (Only one is shown in the image) and a computer program 52 stored in the at least one memory 51 and executable on the at least one processor 50. When the processor 50 executes the computer program 52, it causes the control device 5 to implement the steps in any of the above embodiments of the automatic non-destructive inspection control method for diesel engine fire pumps, or causes the control device 5 to implement the functions of each module / unit in the above embodiments of the system.

[0111] For example, the computer program 52 may be divided into one or more modules / units, which are stored in the memory 51 and executed by the processor 50 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 52 in the control device 5.

[0112] The control device 5 can be a desktop computer, laptop, handheld computer, or cloud server, etc. The control device 5 may include, but is not limited to, a processor 50 and a memory 51. Those skilled in the art will understand that... Figure 5 This is merely an example of control device 5 and does not constitute a limitation on control device 5. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0113] The processor 50 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0114] In some embodiments, the memory 51 may be an internal storage unit of the control device 5, such as a hard disk or memory of the control device 5. In other embodiments, the memory 51 may be an external storage device of the control device 5, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the control device 5. Furthermore, the memory 51 may include both internal storage units and external storage devices of the control device 5. The memory 51 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0115] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0116] This application provides a computer program product that, when run on the control device of a diesel engine fire pump, enables the control device of the diesel engine fire pump to perform the steps in any of the above-described method embodiments.

[0117] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to the control equipment of the diesel engine fire pump, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, such as a USB flash drive, a portable hard drive, a magnetic disk, or an optical disk.

[0118] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0119] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0120] In the embodiments provided in this application, it should be understood that the disclosed automatic non-destructive inspection control system for diesel engine fire pumps can be implemented in other ways. For example, the embodiments of the automatic non-destructive inspection control system for diesel engine fire pumps described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0121] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0122] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for automatic, non-destructive inspection and control of a diesel engine fire pump, characterized in that, include: Acquire reference pulse information; wherein, the reference pulse information is used to reflect current pulses that cannot cause macroscopic angular displacement of the crankshaft of the diesel engine; In response to the detection operation corresponding to the reference pulse information, detection information corresponding to each detection operation is acquired; wherein, the detection operation is an operation of applying the reference pulse information to the starter motor of the diesel engine in a stationary and fuel injection prohibited state, and the detection information is used to reflect the transient current response waveform of the starter motor under the detection operation; Based on the detection information, a first feature parameter and a second feature parameter are determined; wherein, the first feature parameter is used to reflect the proportion of valid operating status data that was not completely extracted in multiple detection operations, and the second feature parameter includes a feature to reflect the degree of influence of the inherent electrical characteristics of the motor on the operating status data and a feature to reflect the degree of influence of non-steady-state transient distortion on the operating status data; Based on the first characteristic parameter and the second characteristic parameter, a control strategy for controlling the diesel engine fire pump is determined.

2. The automatic non-destructive inspection and control method for diesel engine fire pumps as described in claim 1, characterized in that, The step of determining the first feature parameter and the second feature parameter based on the detection information includes: Based on the detection information, operating status data is determined; wherein, the operating status data is used to reflect the data in the detection information used to characterize the electrical performance of the starter motor; Based on each detection information and the corresponding running status data, the multiple detection information are divided into complete execution data and incomplete execution data; wherein, the complete execution data is used to reflect the detection information when the running status data is completely extracted from the multiple detection information, and the incomplete execution data is used to reflect the detection information when the running status data is not completely extracted from the multiple detection information; Based on the complete execution data and the total number of executions, the first feature parameter is determined; Based on the complete execution data, the incomplete execution data, and the detection information, the second feature parameter is determined.

3. The automatic non-destructive inspection and control method for diesel engine fire pumps as described in claim 2, characterized in that, The step of determining the operating status data based on the detection information includes: Based on the detection information, a symbol data chain is determined; wherein, the symbol data chain is used to reflect the stability change of the transient current in the detection information; Based on the symbol data chain, the operating status data is determined from the detection information.

4. The automatic non-destructive inspection and control method for diesel engine fire pumps as described in claim 3, characterized in that, The step of determining the symbol data chain based on the detection information includes: Based on the detection information, an average current value and multiple adjacent current changes are determined; wherein, the average current value refers to the average value of all transient currents in the detection information, and the adjacent current changes refer to the differences between adjacent transient currents in the detection information. Based on the detection information and the average current value, multiple reference current changes are determined; wherein, the reference current change refers to the difference between each transient current in the detection information and the average current value; A symbolic data chain is constructed in chronological order from multiple comparison values ​​determined by multiple adjacent current changes and multiple reference current changes.

5. The automatic non-destructive inspection and control method for diesel engine fire pumps as described in claim 3, characterized in that, The step of determining the operating status data from the detection information based on the symbol data chain includes: Based on the symbolic data chain, a data change trend is determined; wherein, the data change trend is used to reflect the degree of change of the data of the chain nodes in the symbolic data chain over time; Based on the data change trend, a first timing point and a second timing point are determined; wherein, the first timing point refers to the time point corresponding to the first decline of the data change trend, and the second timing point refers to the time point corresponding to the second decline of the data change trend; Based on the time interval determined by the first timing and the second timing, the corresponding operating status data is determined from the detection information.

6. The automatic non-destructive inspection and control method for diesel engine fire pumps as described in claim 2, characterized in that, The step of determining the second feature parameter based on the complete execution data, the incomplete execution data, and the detection information includes: Based on the complete execution data, the incomplete execution data, and the detection information, the steady-state influence degree and the transient influence degree are determined; wherein, the steady-state influence degree is used to reflect the degree of influence of the inherent electrical characteristics of the motor on the operating status data, and the transient influence degree is used to reflect the degree of influence of non-steady-state transient distortion on the operating status data; The steady-state influence degree and the transient influence degree are jointly determined as the second characteristic parameter.

7. The automatic non-destructive inspection and control method for diesel engine fire pumps as described in claim 6, characterized in that, The determination of the steady-state impact degree and the transient impact degree based on the complete execution data, the incomplete execution data, and the detection information includes: Based on the complete execution data, the running status data corresponding to the complete execution data is extracted from the detection information; Based on the operating status data, a first variance and a mean current are determined; wherein, the first variance is used to reflect the variance between the operating status data corresponding to the complete execution data, and the mean current is used to reflect the average current between the operating status data corresponding to the complete execution data. Based on the incomplete execution data, a second variance is determined; wherein the second variance is used to reflect the variance of the incomplete execution data; The ratio of the first variance to the mean current is determined as the steady-state influence, and the ratio of the second variance to the mean current is determined as the transient influence.

8. The automatic non-destructive inspection and control method for diesel engine fire pumps as described in claim 6, characterized in that, The step of determining a control strategy for controlling a diesel engine fire pump based on the first characteristic parameter and the second characteristic parameter includes: The difference between the steady-state influence degree of the second feature parameter and the first data determined by the first feature parameter, and the transient influence degree of the second feature parameter and the second data determined by the first feature parameter, is identified as the influence degree value; wherein, the influence degree value is used to reflect the degree of influence of the change in the number of complete executions on the change in the running state data; Based on the aforementioned impact level value, a control strategy is determined.

9. The automatic non-destructive inspection control method for diesel engine fire pumps as described in claim 8, characterized in that, The determination of the control strategy based on the degree of influence includes: The comparison result, determined by comparing the influence level value with the preset availability threshold, outputs a health level characterizing the health status of the starter motor. When the health level indicates that the starter motor is in a slightly deteriorated state, the first strategy of the control strategy is executed; the first strategy includes adjusting the application frequency of the reference pulse information and displaying the corresponding level prompt information on the local human-machine interface; When the health level indicates that the starter motor is in a moderately deteriorated state, in addition to executing the first strategy, the routine load start inspection is prohibited. When the health level indicates that the starter motor is in a critical fault state, the second strategy of the control strategy is executed; the second strategy includes immediately locking all automatic start functions of the diesel engine fire pump and remotely alarming.

10. A diesel engine fire pump, characterized in that, The device includes a diesel engine fire pump body and a control device, wherein the diesel engine fire pump body is electrically connected to the control device, and the control device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

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