A method and system for detecting the productivity of old machine tools

Abstract

This invention relates to a method and system for detecting the production capacity of aging machine tools, belonging to the field of online machine tool detection technology. The solution first obtains the operational status of machine tool components involved in each stage of the corresponding part's machining process. By analyzing the operational status of the corresponding machine tool components that meet the process requirements, it determines whether the machine tool has completed a complete machining process, including clamping or adsorbing the part, spindle rotation, feeding, and releasing the part. By counting the number of complete machining processes completed by the machine tool within a certain time period, the current processing capacity of the corresponding part is obtained. This invention targets the production capacity detection of aging machine tool equipment, eliminating the need for manual statistical data collection. By collecting data reflecting the operational status of machine tool components from aging equipment, the number of complete machining operations for each part can be cross-validated, resulting in high detection efficiency and accuracy, improved automation, and reduced labor intensity.

Description

Technical Field

[0001] This invention relates to a method and system for detecting the productivity of old machine tools, belonging to the field of online machine tool detection technology. Background Technology

[0002] Machine tools refer to the machinery and equipment used to manufacture machines and equipment. For example, a lathe is a machine tool that primarily uses a cutting tool to turn rotating workpieces. Drills, reamers, taps, dies, and knurling tools can also be used on machine tools for corresponding machining operations. Lathes are mainly used for machining shafts, discs, sleeves, and other workpieces with rotating surfaces, and are the most widely used type of machine tool in mechanical processing and manufacturing.

[0003] During the operation of a lathe, the workpiece is first fixed by a chuck with jaws. The spindle motor drives the workpiece to rotate at high speed through the chuck. Then, a linear motion mechanism such as a lead screw is driven by a stepper motor to move the cutting tool toward the surface to be machined on the workpiece. After contacting the surface to be machined, the cutting of the surface is achieved.

[0004] To calculate the overall efficiency of machine tools (time utilization, performance utilization, and yield rate), relevant information needs to be collected from the machine tools themselves. Modern machine tools are broadly classified into three categories based on their control systems: machine tools without automatic control systems, machine tools with PLC control systems, and machine tools with CNC control systems. Information collection for machine tools with automatic control systems is relatively simple; information such as the equipment's operating status can be transmitted in real-time through the system's communication interface. However, collecting relevant information from older machine tools without automatic control systems is difficult. As crucial machinery in the parts processing, machine tools are closely related to the progress and production capacity of parts processing.

[0005] For older machine tools without automated control systems, production capacity must be calculated manually. Manual counting is labor-intensive, inefficient, time-consuming, and prone to errors, leading to significant inaccuracies. Especially when processing a large number of workpieces, discrepancies often arise between material input and output. Ultimately, to meet targets, it becomes necessary to increase redundancy, resulting in substantial waste of materials and personnel costs and a decrease in output. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for detecting the production capacity of old machine tools, in order to solve the problem that the existing method for calculating the production capacity of old machine tools is labor-intensive and prone to errors.

[0007] To achieve the above objectives, the present invention includes: The present invention provides a technical solution for a method for detecting the production capacity of old machine tools. The method obtains the action status of machine tool components involved in each stage of the corresponding part processing. By determining whether the machine tool has completed a complete processing process including clamping or adsorbing the part, spindle rotation, feeding, and releasing the part based on the action status of the corresponding machine tool components that meet the process requirements, the method obtains the current processing capacity of the corresponding part by counting the number of complete processing processes completed by the machine tool within a certain time period.

[0008] This invention first collects the operational states of machine tool components involved in each stage of the parts processing. These stages include fixing the parts to be processed, the spindle rotating to drive the parts to rotate, or driving the tools and drills to rotate, tool feeding or feeding of the parts to be processed, retraction of the fed tool or parts after processing, spindle stopping, and releasing the processed parts. The machine tool components corresponding to fixing the parts to be processed include the clamping relay of the chuck, the electromagnet and its relay, the hydraulic chuck hydraulic lines and solenoid valves, etc.; the machine tool components corresponding to spindle rotation include the spindle relay, the spindle drive motor and its frequency converter or controller; the machine tool components corresponding to feeding include the feed motor relay, the feed motor and its frequency converter or controller; retraction, stopping, and releasing are the reverse actions of the above three stages, therefore the corresponding machine tool components are the same.

[0009] The operational status of the aforementioned machine tool components can be reflected by the corresponding electrical parameters, physical parameters, and the status of dry contacts (auxiliary contacts). This invention collects various parameters and node states of the machine tool components and finds complete machining processes that meet the process requirements for machining a part from these data, including fixing, spindle rotation, feeding, and releasing. By counting the number of such complete machining processes, the number of parts that have been machined is obtained, and finally, the current machining capacity of the machine tool is calculated.

[0010] The operational states of machine tool components reflecting these stages should meet the technological requirements for machining a part. Generally speaking, the parameters and node states reflecting these operational states should be continuous, accurate, and timely. For example, the changes between two operational states with a causal relationship should be logical. For instance, after the part is clamped, the spindle should start rotating within a certain time (this time is determined by the machine tool and the machining process). If, based on the parameters and node states, there are node actions or parameters reflecting the spindle rotation before the part is clamped, or if there are node actions or parameters reflecting the spindle rotation a long time after the part is clamped, such situations that do not conform to the machining process should not be counted as a complete machining process.

[0011] Furthermore, determining the operating status of machine tool components that clamp or attract firmly parts includes: the dry contact action of the chuck relay or attracting electromagnet relay, the hydraulic pressure value of the hydraulic chuck reaching the set value, the action of the hydraulic chuck clamping solenoid valve, the current signal of the hydraulic chuck clamping solenoid valve coil reaching the set value, and the current signal of the attracting electromagnet coil reaching the set value.

[0012] Furthermore, the process requirements for the operating state of machine tool components that clamp or firmly adhere to parts include that the relevant signals corresponding to the operating state of the machine tool components continue until the processing of a part is completed.

[0013] The process requirements should also be logical for a certain action state. For example, the action state of clamping parts should exist continuously and uninterruptedly during the processing. If it does not meet the requirements, it should not be counted as a complete processing process.

[0014] Furthermore, determining the operating status of the machine tool components that rotate the spindle includes: spindle motor relay dry contact activation, spindle motor bus current reaching the set value, spindle motor inverter start / stop signal, and spindle motor inverter frequency signal reaching the set value.

[0015] Furthermore, the process requirements for the operating state of the machine tool components that rotate the spindle include that the working time of the electrical components responsible for the spindle rotation conforms to the processing range of the corresponding parts.

[0016] Furthermore, determining the operating status of the feed machine tool components includes: the feed motor relay dry contact activation, the feed motor bus current value reaching the set value, the feed motor inverter start / stop signal, and the feed motor inverter frequency signal reaching the set value.

[0017] Furthermore, the process requirements for the operating state of the feed machine tool components include that the working time of the electrical components responsible for the feed conforms to the processing range of the corresponding parts.

[0018] For spindle rotation and feed, the spindle rotation time should meet the corresponding machining duration, and the feed distance or time should meet the corresponding machining process requirements; otherwise, the relevant data should not be counted as a complete machining process.

[0019] Furthermore, the operating states of the machine tool components that release the parts include: the chuck relay dry contact activation, the hydraulic chuck hydraulic system pressure reaching the set value, the hydraulic chuck clamping solenoid valve activation, and the current signal of the chuck clamping solenoid valve coil reaching the set value.

[0020] Furthermore, the judgment conditions for the complete machining process also include: the machine tool lubrication system and hydraulic system working, as well as the feed system retraction and spindle stoppage before releasing the parts after feeding; the operating state of the machine tool components when the machine tool lubrication system is working includes the lubrication pump relay node closing and the lubrication system pipeline pressure reaching the set value; the operating state of the machine tool components when the hydraulic system is working includes the hydraulic pump relay node closing and the hydraulic system pipeline pressure reaching the set value.

[0021] The present invention provides a technical solution for an old machine tool capacity detection system, comprising a processor, wherein the processor is used to execute instructions for implementing the old machine tool capacity detection method as described above.

[0022] The beneficial effects of this invention are as follows: For the production capacity testing of old machine tools, there is no need to rely on manual statistical data. By collecting data reflecting the operating status of machine tool components from old equipment, the complete number of processing times of parts can be statistically determined through cross-verification. The testing efficiency is high and the accuracy is high, which improves the level of intelligence and reduces labor intensity.

[0023] At the same time, the operating status of each machine tool component meets the processing requirements, and the operating status of each machine tool component as a whole in a single processing operation is also logical and meets the process requirements, thus improving the accuracy of production capacity statistics.

[0024] The system further adds relevant parameters of the basic operating conditions of the machine tool as criteria for determining whether it is a complete machining process. For example, whether the lubrication system is working properly and whether the hydraulic system has established sufficient pressure for the normal operation of the machine tool. This further improves the accuracy of production capacity statistics and avoids the problem of inaccurate statistical data caused by the actions of related components triggered by the debugging, maintenance or cleaning of the machine tool being identified as machining processes. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of an industrial big data system for old automatic lathes in an embodiment of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0027] Machine tools without automatic control systems generally operate on relatively simple or outdated control principles. Each component can only perform its own simple actions, lacking intelligent control systems and information collection and transmission capabilities. The concept of this invention lies in collecting the operational states and related parameters of electrical components or moving parts involved in each key stage of machine tool processing. By analyzing the changing characteristics of these operational states and parameters, the operating state of the machine tool at a corresponding moment can be reflected. This allows for analysis to determine the start and end of each stage, thereby obtaining the processing progress of the part currently being processed. Furthermore, it can statistically analyze the number of times the machine tool executes a complete processing stage within a certain time period, thus obtaining the number of parts processed within that time period, and finally calculating the processing capacity of the corresponding parts.

[0028] The current operating status of a machine tool can be obtained by analyzing the operating states and related parameters of electrical components or moving parts. Examples include: 1) Start by analyzing the nodes of the electrical components on the equipment to obtain the current operating status of the machine tool. For example, by energizing / de-energizing and engaging / releasing the contactor coil, the corresponding motor rotation / stop status can be obtained. In this way, node signals can be collected from the auxiliary contacts of the contactor to obtain the current working status, working time, and number of operations of the equipment.

[0029] 2) Signal acquisition from auxiliary points of thermal relays used for machine tool thermal protection reveals the current protection status of the equipment. For example, if the current in the main circuit of the machine tool is too high and the heat generated exceeds the setting value of the thermal relay, the thermal relay will activate, the control circuit will be de-energized, the main circuit will lose power, and the equipment will stop working. This is the traditional overheat protection process for older machine tools. From an external perspective, one can only know that the machine tool has stopped, but not the reason for the stop, let alone why the machine tool triggered thermal protection. However, by acquiring the action of the auxiliary contacts of the thermal relay, it can be determined that the current state of the machine tool is due to the shutdown caused by the triggering of thermal protection. This provides the overheat alarm signal of the machine tool. Combined with other data acquired at the same time, such as the main circuit current data, it can be further determined that the machine tool triggered thermal protection due to overcurrent in the main circuit.

[0030] 3) Various instruments and sensors can be added to key locations on the machine tool. The data collected by these instruments and sensors can be output to a data acquisition box to obtain the sensor's action signals, digital signals, or analog signals, as well as the instrument's analog or digital signals. For example, when a frequency converter controls the speed of a motor, pressing the start button outputs a set frequency (this frequency can be externally set or given via a potentiometer). By acquiring the frequency output by the frequency converter through a sensor, the motor's speed, current, and torque can be obtained. Therefore, simply importing the start signal from the start button and the signal output from the frequency converter into the signal acquisition box is sufficient to obtain the current operating status of the equipment.

[0031] 4) In addition, pressure sensors are installed in the hydraulic system to convert physical pressure changes into electrical signals to measure and monitor the hydraulic system, thereby determining whether the hydraulic actuators perform the corresponding actions.

[0032] In general, dry contact signals are all switching signals, with only two states—on and off. These signals allow us to determine the current status of the machine tool, such as whether the machine tool is currently running, whether the spindle is rotating, and whether the pressure is in place.

[0033] Analog signals are signals whose values ​​change continuously (digital signals can also reflect signals whose values ​​change continuously). By continuously acquiring data, we can observe the changes in the continuous operation status of a machine tool.

[0034] The specific approach involves establishing a big data system to collect operating parameters of key electrical components and moving parts in each critical stage of machining. The collected data is then aggregated on a server. The server, based on the actions of representative electrical components and moving parts in each stage of the machine tool's machining process, determines whether the machining of a part has been completed and calculates the number of parts processed within a certain time period. This allows for the use of the big data system to statistically analyze part production capacity. The actions of electrical components and moving parts can be determined through changes in specific circuit electrical parameters, auxiliary contact actions, limit switch actions, and changes in hydraulic pressure.

[0035] The solution of this invention eliminates the need for manual statistics for old machine tools, enabling automated and intelligent production capacity statistics with high efficiency, accuracy, and low error rate.

[0036] Method Implementation Examples: The following description uses a common old-style automatic lathe as an example to further illustrate the present invention's method for detecting the production capacity of old machine tools.

[0037] First, an industrial big data system is established to collect the operational status and related parameters of electrical components or moving parts. Industrial big data refers to the collective term for various types of data and related technologies and applications generated throughout the entire product lifecycle, from sales, planning, design, manufacturing, supply, and operation and maintenance, under the intelligent manufacturing model. Its characteristics include large volume, diversity, rapid processing, and low value density, while also possessing timeliness, strong correlation, accuracy, and strong closed-loop characteristics. For manufacturing enterprises, big data can be used to improve operational efficiency and enhance the strategic management perspective of enterprise managers.

[0038] The old machine tool capacity detection method in this embodiment is based on the data accumulation generated by the industrial big data system during the workshop production process, and uses the same cyclic data generated by the machine tool during the processing process extracted from this data as a basis to calculate the capacity.

[0039] The principle of industrial big data system for old automatic lathes is as follows: Figure 1 As shown, signals are collected from several key components, including the machine tool lubrication pump, hydraulic oil pump, spindle motor, feed motor, and hydraulic chuck. Specifically, the lubrication pump's actuation signal is uploaded through its contactor I / O point (or auxiliary contact); for the hydraulic oil pump, a pressure gauge is installed on the hydraulic oil circuit at the output end, and the pressure value is uploaded through the pressure gauge's serial port, while the hydraulic oil pump's contactor actuation signal is collected and uploaded through its contactor I / O point (or auxiliary contact); a current meter is installed on the spindle motor bus, and the current value is uploaded through the meter's communication port, while the spindle motor's contactor actuation signal is collected and uploaded through its contactor I / O point (or auxiliary contact); the feed motor works similarly to the spindle motor, collecting and uploading the bus current and contactor actuation signal; the hydraulic chuck's actuation signal is collected and uploaded through the hydraulic chuck relay's I / O point (or auxiliary contact).

[0040] The uploaded data is collected by a data acquisition box and then uploaded to an industrial big data server. The data acquisition box collects various communication data and I / O signals from the machine tool and converts them into identifiable engineering quantity data for uploading to the server. Dry contact action signals, specifically the closing and opening of the contacts, are uploaded to the server by the acquisition box in the form of 1s and 0s. Continuously changing values, such as analog quantities, are first converted into digital quantities and then uploaded to the acquisition server as binary strings. The industrial big data server is responsible for data storage, analysis, and calculation, and transmits the results to an IoT platform (Internet of Things platform). The IoT platform is used to display the data and calculation results for third-party access.

[0041] The server collects the relevant upload signals from the above components and can calculate the production capacity based on the following principle.

[0042] 1) The operation of the hydraulic oil circuit or air circuit of the machine tool, the pressure (analog signal) is the power that drives the machine tool parts to move, and can be used as an element to calculate the production capacity of the machine tool.

[0043] 2) During machine tool operation, it is necessary to clamp or firmly adhere to the workpiece. This requires the operation of corresponding contactors, relays, and disk-type electrical components. When these components operate, the coils engage, and the contacts actuate. The corresponding auxiliary contact actuation signals are then considered as a point in the production capacity data analysis. It can serve as a signal indicating the completion of a workpiece processing; however, this does not definitively prove that the workpiece processing is complete, but only as an auxiliary judgment. For example, during trial runs or when cleaning debris, the actuation may be triggered multiple times manually.

[0044] 3) The operation of the spindle that holds the workpiece (or tool) and rotates continuously, and the operation time is within the range of the machining process, can be used as a factor to determine the production capacity.

[0045] 4) The working time of the electrical components responsible for the feed motor is also a factor in determining the production capacity when it is within the process range.

[0046] In summary: after the machine tool's hydraulic and pneumatic circuits are operational (resulting in pressure signals), and the chuck (or other fixing devices) clamps the workpiece, the spindle's movement and feed actions all fall within the specified timeframe. Once these conditions are met, the server can determine that one machining cycle has been completed. The corresponding signals can be obtained from the relevant uploaded signals collected by the data acquisition box. By analyzing and extracting such time periods from the large amount of data acquired daily by the industrial big data system, the number of parts processed that day can be determined, thus yielding the daily production capacity.

[0047] When processing data, the server requires that the relevant data be accurate and timely. Because the data is highly correlated, any error or delay in a single signal will prevent the formation of a closed loop in the machine tool processing data. Using timely and accurate signals from multiple dimensions to judge the same action and to complement or verify each other can improve the method's anti-interference ability, reduce misjudgments, and increase the accuracy of capacity determination.

[0048] Specifically, in combination Figure 1 The big data system of the old automatic lathe shown has a lubrication pump that lubricates various parts of the machine tool after power-on. This operation serves as a starting point for the machine tool's operation (its action is determined by the closing signal of its relay node; in other embodiments, the lubrication system pressure value can also be collected for verification or as an independent indicator of the lubrication system's operation). Then, the hydraulic oil pump starts (determined by the closing signal of its relay node) and maintains a certain pressure (determined by the hydraulic system pressure value). This pressure value is a key factor in determining whether machining can begin (without pressure or with insufficient pressure, the machine tool cannot operate; this pressure acting on the chuck jaws reflects the clamping force on the workpiece. Generally, the hydraulic chuck pressure value should not be lower than 4 MPa; below this pressure, the workpiece is not firmly clamped). If the workpiece clamping force is insufficient, the machining conditions cannot be met, indicating that machining has stopped.

[0049] Once both of the above conditions are met, the hydraulic chuck can close (determined by the closing signal of the jaw action relay node) to clamp the workpiece, start the spindle rotation (determined by the closing signal of the spindle motor relay node, which can be verified by the spindle motor bus current value), and start the feed motor (the feed motor relay node closing signal is uploaded, which can be verified by the feed motor bus current value). After a certain period of time, one part is machined; the tool returns to the origin, the spindle stops rotating, the chuck is released, and the workpiece is removed, thus completing one workpiece machining process. Based on this, each cycle of clamping, rotating, feeding, retraction, stopping, and releasing can be considered as the completion of machining one workpiece.

[0050] The number of workpieces processed within a certain period of time, such as one day, is counted to calculate the lathe's production capacity.

[0051] In addition to the hydraulic system pressure value acting on the chuck and the action value of the chuck relay dry contact mentioned above, the conditions for determining whether the chuck is clamping or releasing the workpiece can also be the action signal of the chuck clamping solenoid valve (obtained through the auxiliary contact of the solenoid valve), or the current signal of the chuck clamping solenoid valve coil, etc. At the same time, the principle requirement for chuck clamping judgment is that the relevant signal continues until the end of machining. This is because the chuck is definitely continuously clamping the workpiece during machining. Short-term signals may be triggered by machine tool self-check actions or debris removal, while instantaneous signals may be interference.

[0052] The judgment conditions reflecting the operation of the spindle motor or feed motor can also be related signals from the motor inverter or driver. Inverters and drivers have both dry contacts, communication ports, and analog ports. Their dry contact signals (such as start and stop signals) also enter through the I / O nodes of the signal acquisition box, are converted into binary data, and are uploaded to the server for processing. Communication ports and analog ports can upload data such as the inverter output frequency through various protocols such as Modbus, PROFIBUS, TCP / IP Ethernet, Unitelway, FIPWAY, FIPIO, AS-I, and Interbus-S.

[0053] The embodiments of this invention are based on industrial big data. They collect various parameters and status changes from electrical components on older equipment, analyze the big data to identify mutually corroborating data reflecting a complete processing cycle, and record the entire process to achieve capacity monitoring. Based on industrial big data, enterprises can implement intelligent management and intelligent production without incurring any additional hardware costs; it simply adds another way to utilize basic data, thus improving the data utilization rate of industrial big data.

[0054] Alternatively, an industrial big data system can be omitted, and a large amount of redundant data and signals can be avoided. Instead, only data and signals related to the corresponding component's actions can be collected. By using the data and signals to determine whether the corresponding component's actions constitute a complete clamping, rotating, feeding, retracting, stopping, and releasing process, the processing of one component can be considered complete. The number of components processed within a set time is then counted, thus obtaining the processing capacity of the corresponding component.

[0055] The above embodiments use a lathe as an example to illustrate the method of the present invention. Those skilled in the art should understand that other old-fashioned machine tools, such as grinding machines, planers, boring machines, drilling machines, and milling machines, also include the process of fixing and clamping the workpiece, rotating the spindle that drives the grinding wheel or drill bit, feeding and retracting the tool, grinding wheel, or drill bit, stopping the spindle, and releasing the workpiece. The corresponding data acquisition and production capacity statistics methods are the same as those for lathes, and will not be listed and described in detail in this embodiment.

[0056] Furthermore, for example, a planer, the machining process of its parts does not involve the rotation of the parts or the tool. In this case, the spindle rotation should be considered as the rotation of the main rotating component. The spindle rotation is not the spindle that drives the parts or the tool in the narrow sense.

[0057] The method of the present invention can also be used in manual machine tools with machine tool components as described in the above embodiments. The operator manually presses the button or operates the handle to control the machine tool to perform the corresponding processing. The corresponding control signal triggers, for example, the chuck relay to act, the hydraulic pressure of the drive jaws to increase, the spindle motor relay to act, the spindle motor current to increase, etc., which can also be collected and then the production capacity can be statistically analyzed using the method of the present invention.

[0058] System Implementation Example: The industrial big data system (which may not require an IoT platform) described in the method embodiments, or the system described at the end of the method embodiments that only collects data and signals related to the judgment of corresponding component actions and performs corresponding capacity calculations, both constitute the old machine tool capacity detection system of the present invention. The relevant hardware components and capacity calculation methods have been described clearly enough in the method embodiments, and will not be repeated in this embodiment.

Claims

1. A method for detecting the production capacity of old machine tools, applicable to machine tools without an automatic control system, characterized in that, The system obtains the operational status of machine tool components involved in each stage of the corresponding part processing: It collects the operation signals of the machine tool lubrication pump contactor, hydraulic oil pump contactor, hydraulic oil circuit pressure, spindle motor contactor, feed motor contactor, and hydraulic chuck relay. Based on the operational status of the corresponding machine tool components that meet the process requirements, it determines whether the machine tool has completed a complete processing cycle: the closure of the machine tool lubrication pump contactor indicates the start of the lubrication pump operation, the closure of the hydraulic oil pump contactor indicates the start of the hydraulic oil pump, and the hydraulic oil circuit pressure value indicates the start of the hydraulic oil pump operation. Maintaining a certain pressure, the hydraulic chuck relay determines whether the chuck is clamping the workpiece, and the signal continues until the workpiece is finished. The spindle motor contactor closes to determine spindle rotation, and the feed motor contactor closes to determine feed motor operation. The duration of spindle rotation and feed motor operation must conform to the machining process range until the spindle stops and the chuck releases, at which point the machining of one workpiece is considered complete. Analyze the collected signals to obtain data that reflects a complete machining process and that can be mutually verified, and record a complete machining process. By counting the number of complete machining processes completed by the machine tool within a certain time period, the current machining capacity of the corresponding parts can be obtained.

2. The method for detecting the production capacity of old machine tools according to claim 1, characterized in that, A pressure gauge is installed on the hydraulic oil circuit at the output end of the hydraulic oil pump to obtain the pressure value of the hydraulic oil circuit.

3. The method for detecting the production capacity of old machine tools according to claim 1, characterized in that, The pressure values ​​of the lubrication system are also collected to verify the judgment of the lubrication system's operation.

4. The method for detecting the production capacity of old machine tools according to claim 1, characterized in that, The spindle motor bus current value is used as a verification of spindle rotation.

5. The method for detecting the production capacity of old machine tools according to claim 1, characterized in that, The results are transmitted to the IoT platform, which is used to display the data and make it available for third-party use.

6. The method for detecting the production capacity of old machine tools according to claim 1, characterized in that, The feed motor bus current value is used as a verification of the feed motor's operation.

7. The method for detecting the production capacity of old machine tools according to claim 1, characterized in that, The hydraulic oil pump maintains a certain pressure to ensure that the set pressure of the hydraulic chuck is not less than 4 MPa.

8. The method for detecting the production capacity of old machine tools according to claim 1, characterized in that, The criteria for determining whether the chuck clamps or releases the workpiece can also be the action signal of the chuck clamping solenoid valve, or the current signal of the chuck clamping solenoid valve coil.

9. The method for detecting the production capacity of old machine tools according to claim 1, characterized in that, The judgment conditions reflecting the operation of the spindle motor or feed motor can also be the dry contacts, communication ports, or analog port signals of the motor inverter or driver.

10. A system for detecting the production capacity of old machine tools, characterized in that, Includes a processor for executing instructions to implement the old machine tool capacity detection method as described in any one of claims 1 to 9.

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