A UWB-based intelligent mold opening positioning control system and method

Abstract

The invention discloses an intelligent mold opening positioning control system and method based on UWB, which specifically relates to the technical field of positioning control and is used to solve the problem of low positioning control accuracy. The invention sets an ultra-wideband transmitting end and a receiving end, uses different channel models for communication transmission, performs ranging and positioning between the transmitting end and the receiving end according to a clock offset method and a time difference arrival positioning method, combines multipath component analysis with filtering technology to determine indoor mold opening positioning conditions, combines the ultra-wideband with an inertial measurement unit to optimize indoor mold opening positioning accuracy, analyzes characteristic matching information generated in the indoor mold opening positioning process and generates different signals, and performs different mold opening positioning control management on different models.

Description

Technical Field

[0001] The present invention relates to the field of positioning control technology, and more specifically, to a UWB-based intelligent mold opening positioning control system and method. Background Art

[0002] Ultra-wideband (UWB) is a wireless communication technology known for its wideband characteristics (usually over 500MHz). UWB transmits data by emitting extremely short pulses, which gives it extremely high spatial resolution and is very suitable for precise positioning and tracking applications. The main advantages of UWB technology include high transmission rate, low power consumption, and the ability to effectively penetrate obstacles such as walls, making it particularly suitable for use in complex environments.

[0003] Mold positioning control mainly refers to the technology of controlling the precise placement and alignment of molds in production activities that require the use of molds during the manufacturing process, especially in the fields of plastic injection molding, metal die-casting, and precision molding. Mold positioning control may use various sensors, machine vision systems or position control software to achieve precise movement and positioning of molds.

[0004] Deficiencies of existing technologies:

[0005] When using ultra-wideband for positioning in an indoor NLOS (non-line-of-sight) environment, the signal cannot reach the receiver directly from the transmitter, but needs to be transmitted through reflection, refraction or diffraction, which leads to signal attenuation and enhanced multipath effect. As a result, these factors work together to make the distance information obtained from the time delay measurement inaccurate, thereby affecting the positioning accuracy of the entire system, especially for molds that require high-precision placement. When the positioning is not accurate enough, it is easier to produce defective products that do not meet the standards, which in turn causes low production efficiency. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, the present invention provides an intelligent mold opening positioning control system and method based on UWB to solve the problem of low production efficiency caused by inaccurate mold opening positioning indoors.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] An intelligent mold opening positioning control method based on UWB includes the following steps:

[0009] Set up the UWB transmitter and receiver, and use different channel models for communication transmission according to the characteristics of signal transmission and environmental complexity;

[0010] The distance and positioning between the transmitter and the receiver are measured and located according to the clock offset method and the time difference arrival positioning method, and the multipath component analysis and filtering technology are combined to determine the indoor mold opening positioning situation;

[0011] If the indoor mold opening positioning meets the requirements, the ultra-wideband is combined with the inertial measurement unit to optimize the indoor mold opening positioning accuracy and analyze the characteristic matching information generated during the indoor mold opening positioning process;

[0012] The data adaptation status is determined based on the generated characteristic matching information and a signal is generated, and corresponding mold opening positioning control management is performed based on the generated signal.

[0013] In a preferred embodiment, different channel models are used for communication transmission according to the characteristics of signal transmission and the complexity of the environment. The specific process is as follows:

[0014] The channel model includes single-path linear channel model, single-path nonlinear channel model and multipath channel model.

[0015] Use a single-path linear channel model in a direct and unobstructed signal propagation path;

[0016] Use a single-path nonlinear channel model in a direct and nonlinear signal propagation path;

[0017] In the signal propagation path where multipath effects exist, a multipath channel model is used.

[0018] In a preferred embodiment, the distance measurement and positioning between the transmitter and the receiver are performed according to the clock offset method and the time difference arrival positioning method. The specific process is as follows:

[0019] The clock offset method is to determine the time point of transmitting and receiving the signal at a known time point, and calculate the clock deviation between the transmitting and receiving signals, and calculate the distance of signal propagation based on the clock deviation;

[0020] The time difference of arrival positioning method is to deploy receivers at different known locations. The receivers record the exact time of signal arrival, select one receiver as a reference, calculate the time difference between the remaining receivers and the reference receiver receiving the signal, and use the time difference and the known position of the receiver to estimate the position of the signal source through solution.

[0021] In a preferred implementation, multipath component analysis is combined with filtering technology to determine the indoor mold opening positioning situation. The specific process is as follows:

[0022] Collect signal data of the indoor environment and pre-process the collected signal data, including noise removal and normalization processing;

[0023] Using principal component analysis, the preprocessed signal data is constructed into a matrix form, and the covariance matrix is ​​calculated based on the data matrix. Based on the standardized data, the covariance matrix is ​​constructed to quantitatively determine the correlation between variables;

[0024] Use Kalman filtering technology to define the system state model and measurement model, determine the initial state estimate and initial error covariance matrix, use the system state model to predict the state and initial error covariance at the next moment, and update the state estimate to determine and eliminate signal data deviation;

[0025] The indoor mold opening positioning performance is determined based on positioning accuracy, positioning stability and system robustness.

[0026] In a preferred embodiment, the characteristic matching information generated during the indoor mold opening and positioning process is analyzed, and the specific process is as follows:

[0027] The characteristic matching information includes signal quality information and path direction information;

[0028] The signal quality information includes a signal consistency index, and the path direction information includes a direction accuracy response index;

[0029] The obtained signal consistency index and directional accuracy response index are calculated jointly to obtain the positioning control coefficient.

[0030] In a preferred embodiment, the data adaptation is determined according to the generated characteristic matching information and a signal is generated, and the corresponding mold opening positioning control management is performed according to the generated signal. The specific process is as follows:

[0031] Compare the positioning control coefficient with the positioning control threshold;

[0032] If the positioning control coefficient is greater than or equal to the positioning control threshold, an adaptive positioning stabilization signal is generated without making any control adjustments;

[0033] If the positioning control coefficient is less than the positioning control threshold, an adaptive positioning deviation signal is generated to prompt the operator or system administrator to take measures to check and adjust the positioning process.

[0034] A UWB-based intelligent mold opening positioning control system, used for the above-mentioned UWB-based intelligent mold opening positioning control method, comprising:

[0035] The transceiver selection module is used to set the ultra-wideband transmitter and receiver, and use different channel models for communication transmission according to the characteristics of signal transmission and environmental complexity;

[0036] The positioning data processing module is used to measure the distance and position between the transmitter and the receiver according to the clock offset method and the time difference arrival positioning method, and combine the multipath component analysis with the filtering technology to determine the indoor mold opening positioning situation;

[0037] Positioning process analysis module: if the indoor mold opening positioning meets the requirements, the ultra-wideband is combined with the inertial measurement unit to optimize the indoor mold opening positioning accuracy and analyze the characteristic matching information generated by the indoor mold opening positioning process;

[0038] The control module is used to determine the data adaptation status and generate a signal according to the generated characteristic matching information, and perform corresponding mold opening positioning control management according to the generated signal.

[0039] Technical effects and advantages of the present invention:

[0040] The present invention sets an ultra-wideband transmitting end and a receiving end. We should select a suitable channel model for communication transmission according to the characteristics of signal transmission and the complexity of the environment. By using the clock offset method and the time difference arrival positioning method, accurate ranging and positioning can be performed between the transmitting end and the receiving end. Combined with multipath component analysis and filtering technology, the accuracy of indoor mold opening positioning can be further improved. If the positioning result meets the preset standard, the ultra-wideband can be combined with the inertial measurement unit to further optimize the accuracy of indoor mold opening positioning. By analyzing the characteristic matching information generated in the positioning process, the adaptation of the data can be effectively determined. According to these analysis results, corresponding signals are generated to guide the control and management of mold opening positioning, thereby achieving more efficient and precise operation control. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The present invention is a flow chart of an intelligent mold opening positioning control method based on UWB.

[0042] Figure 2 The schematic diagram is a structural diagram of a UWB-based intelligent mold opening and positioning control system of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Example 1: Figure 1 As shown, a UWB-based intelligent mold opening positioning control method, the method comprising:

[0045] Set up the UWB transmitter and receiver, and use different channel models for communication transmission according to the characteristics of signal transmission and environmental complexity;

[0046] The distance and positioning between the transmitter and the receiver are measured and located according to the clock offset method and the time difference arrival positioning method, and the multipath component analysis and filtering technology are combined to determine the indoor mold opening positioning situation;

[0047] If the indoor mold opening positioning meets the requirements, the ultra-wideband is combined with the inertial measurement unit to optimize the indoor mold opening positioning accuracy and analyze the characteristic matching information generated during the indoor mold opening positioning process;

[0048] The data adaptation status is determined based on the generated characteristic matching information and a signal is generated, and corresponding mold opening positioning control management is performed based on the generated signal.

[0049] To set up the UWB transmitter and receiver, follow these steps:

[0050] First, you need to select appropriate UWB devices. These devices should support the required transmission frequency and power. The transmitter and receiver can be the same model, or different models with specific functions can be selected according to needs.

[0051] Installed in a fixed location or on a moving object, such as a mobile robot or vehicle, multiple receivers may need to be deployed to cover the entire area or improve positioning accuracy, depending on the design of the positioning system;

[0052] Configure each device, including setting the communication frequency, power output and synchronization protocol to ensure the clocks of all devices are synchronized. After the equipment is installed, perform preliminary communication tests to ensure that the signal strength and quality between the sender and receiver meet the expectations.

[0053] In communications, different channel models are usually used to simulate and analyze signal propagation according to the characteristics of signal transmission and the complexity of the environment. That is, there are multiple ultra-wideband channel models, including single-path linear, single-path nonlinear, and multipath channel models. Each channel model has different specific usage scenarios.

[0054] The single-path linear channel model (S ISO) is suitable for situations where the environment is simple and the signal propagation path is direct and unobstructed, such as open outdoor environments or straight-line line-of-sight transmission in indoor environments. The single-path linear model assumes that the signal propagation does not suffer any form of attenuation or distortion. It is suitable for idealized signal transmission analysis, such as in laboratory tests to obtain baseline performance data;

[0055] The single-path nonlinear channel model (SI SO-NL) is applicable to environments where the signal propagation path is direct but some nonlinear effects may be encountered during the transmission process, such as in a specific type of medium (such as underwater) or in special signal amplification equipment. The model takes into account the nonlinear effects that the signal may encounter during the propagation process, such as nonlinear distortion during signal amplification, which helps to design and adjust the communication systems used in these environments.

[0056] The multipath (MIMO) channel model is very suitable for urban or indoor environments, where the signal may propagate through multiple paths to reach the receiver, such as multipath effects caused by wall reflection and building diffraction. MIMO (Multiple Input Multiple Output) technology uses this multipath effect to increase signal redundancy by using multiple antennas at the transmitter and receiver, thereby improving the speed and reliability of data transmission. This model has been widely used in modern wireless communication systems such as Wi-Fi, LTE and 5G;

[0057] In indoor open-mode positioning control, the use of single-path linear, single-path nonlinear, and multipath channel models depends on the specific application requirements and environmental conditions. Under certain specific conditions, only one channel model may be used. For example, if the indoor environment is relatively simple and there are no multiple reflection and scattering paths (such as a large open space without many obstacles), a single-path linear model may be sufficient. On the contrary, if there are specific nonlinear characteristics in the environment, such as signal distortion caused by nonlinear amplification or special materials, a single-path nonlinear model may be used alone;

[0058] In more complex indoor environments, it may be necessary to use multiple models in combination to obtain the best positioning effect. For example, the multipath model can be used to deal with multiple reflection and scattering paths, while the single-path model can be used to deal with the impact of the direct path or the main path. By combining them, the advantages of each model can be utilized to more accurately simulate and calculate the actual signal propagation and positioning;

[0059] At the same time, the most appropriate channel model can be dynamically selected based on the environmental data analyzed in real time. This method requires high computing resources and intelligent algorithms to adjust the model used in real time according to the current propagation conditions;

[0060] The ultra-wideband channel model is usually manifested as a channel model with multipath characteristics, in which each path has its own specific attenuation and delay. The impulse response function of the UWB channel can usually be expressed as a series of pulses, each pulse represents a path and has its own amplitude, delay and phase. The specific mathematical expression is as follows: Where h(t) is the impulse response of the channel, N is the number of multipath components, and a i is the amplitude of the ith path, τ iis the delay of the ith path, φ i is the phase of the ith path, δ(t) is the Dirac delta function, which is used to represent the i The impact of

[0061] In practical applications, the amplitude a of each path i Usually depends on the attenuation of the path, the delay τ i reflects the time of signal propagation, phase φ i It can be determined by the physical characteristics of the path and the propagation environment, which helps to analyze and design the performance of UWB systems, especially in complex multipath environments.

[0062] Use the clock offset method to perform TOF (Time of Flight) ranging to determine the distance from the signal transmitter to the receiver. The specific steps are as follows:

[0063] Signal transmission, transmitting a signal (usually an electromagnetic wave, such as a radio wave or a light wave) at a known time point t0;

[0064] Signal reception: The signal is received by the receiver after traveling a certain distance, and the receiver records the time t1 when the signal is received.

[0065] Calculate the clock deviation between signal transmission and reception: Δt=t1-t0, calculate the distance the signal propagates: d=c*Δt, where d is the distance the signal propagates, and c is the speed of the signal in the propagation medium, usually the speed of light.

[0066] The time difference of arrival positioning method (TDOA) is used for positioning. The TDOA positioning method involves using multiple receivers to measure the difference in the arrival time of signals from the same signal source to determine the location of the signal source. The specific steps are as follows:

[0067] Deploy multiple receivers at different known locations. The signal source transmits a signal, such as a radio wave. Each receiver records the precise time of arrival of the signal. Select one receiver as a reference, calculate the time difference between the signals received by the other receivers and the reference receiver, and use the time difference and the known location of the receiver to estimate the location of the signal source through solution.

[0068] Assume the receiving time of the reference receiver is t ref , the receiving time of other receivers is t i , the distance from the signal source to the reference receiver is d ref , the distance to the i-th receiver is d i , the time difference is: Δt i =t i -t ref , the distance difference is: Δd i =d i-d ref ;

[0069] For a given receiver coordinate (x ref ,y ref , z ref ) and (x i ,y i , z i ), the position of the signal source is (x, y, z), then: By combining the above distance equation with the time difference equation, solving (x, y, z) can get the location of the signal source. Numerical methods such as Newton iteration method or least squares method are used to solve this type of nonlinear equations. This requires sufficient computing resources and algorithm optimization to ensure the accuracy and stability of the solution;

[0070] Understand and evaluate the specific environmental conditions where the mold positioning will be deployed to identify factors that may affect the mold positioning performance, record key physical and electronic characteristics, such as room layout, wall material, existing mechanical equipment, etc., and detect possible signal interference sources, such as radio frequency interference, electromagnetic interference, etc.;

[0071] Perform multipath effect analysis to identify possible sources of reflection and scattering, such as walls, large equipment, etc., which may cause multipath propagation of signals, and consider possible dynamic changes in the environment, such as mobile devices, personnel flow, etc., which may affect positioning accuracy.

[0072] Use multipath component analysis and filtering technology to reduce the impact of multipath effects on indoor positioning. The specific steps are as follows:

[0073] Use UWB devices to collect signal data in indoor environments at multiple points, and pre-process the collected signal data, including noise removal and normalization, to ensure that the mean of each variable is 0 and the standard deviation is 1;

[0074] Applying principal component analysis (PCA), data matrix construction, constructing the preprocessed signal data into a matrix form, and calculating the covariance matrix based on the data matrix, based on the standardized data, constructing the covariance matrix to quantify the correlation between variables;

[0075] The data matrix X is an n-row p-column matrix, where m represents the number of samples and p represents the number of features. The covariance matrix is ​​calculated as follows: C is a p×p matrix, representing the covariance between features, X T represents the transpose of X;

[0076] Solve to obtain the eigenvalues ​​and eigenvectors of the covariance matrix, select the main components according to the size of the eigenvalues, select the first few main components for analysis and data dimensionality reduction, and the selected components usually correspond to the signals of the direct path;

[0077] Perform eigenvalue decomposition, the expression is Cv = λv, where v represents the eigenvector and λ represents the corresponding eigenvalue. Each eigenvector represents the direction of a principal component, and the corresponding eigenvalue represents the importance of that direction (i.e., the variance of the variable in that direction);

[0078] Combined with the Kalman filter technology, first, the system state model and measurement model are defined. The system state model describes the time evolution of the state variables, and the measurement model describes how to generate measurement data from the state variables.

[0079] Determine the initial state estimate and initial error covariance matrix, use the system state model to predict the state and error covariance at the next moment, and update the state estimate using the new measurement data. This step involves calculating the Kalman gain, updating the state estimate, and correcting the initial error covariance.

[0080] These techniques were tested in a simulated environment to evaluate their effectiveness in reducing multipath interference and improving signal quality.

[0081] The estimated value and covariance matrix expression in the state prediction process are: P k|k-1 =AP k|k-1 A T +Q k , where A represents the system matrix, A T represents the transpose of the matrix, B k represents the control matrix, u k represents the control input, Q k represents the process noise covariance matrix;

[0082] Update the state estimate and covariance matrix according to the measured value, that is, update the state of the prediction result and determine the Kalman gain matrix: K k =P k|k-1 H T (HP k|k-1 H T +R k ) -1 , P k =(IK k H)P k|k-1 , where H represents the observation matrix, R k represents the observation noise covariance matrix, K k represents the Kalman gain matrix, z krepresents the observation value at the kth moment, and I represents the unit matrix.

[0083] The Kalman filter can continuously correct the position estimate by dynamically predicting and updating the signal transmission path in real time, eliminating deviations caused by environmental changes or device movement.

[0084] Multipath component analysis helps to identify and distinguish the direct path and reflected path of the signal. By giving priority to the signal component of the direct path, the errors caused by reflection and scattering can be reduced, thereby improving the overall positioning accuracy. The Kalman filter can continuously correct the position estimate and eliminate the deviation caused by environmental changes or equipment movement through dynamic prediction and real-time update of the signal transmission path.

[0085] When using multipath component analysis and filtering technology to determine indoor positioning, whether the indoor mold opening positioning meets the requirements is mainly based on the following criteria:

[0086] Positioning accuracy,Accuracy is one of the most critical factors in evaluating the performance of a positioning system. Usually, the accuracy standard is pre-set according to application requirements. For example, in some high-precision manufacturing scenarios, positioning accuracy may need to reach the centimeter level or even the millimeter level. For example, if a system requires that the position error must not exceed 5 cm, then the average position error measured in the test must be less than or equal to this value;

[0087] Positioning stability: the positioning results should not fluctuate randomly or suddenly. A system with good stability can maintain consistent performance during continuous operation. For example, by monitoring the positioning results for a long time, confirm that its variation range remains within the acceptable error threshold;

[0088] System robustness: the system can still provide accurate and reliable positioning information in the face of environmental interference, such as non-line-of-sight (NLOS) conditions. For example, the positioning system can accurately identify the device location even when there are walls or other obstacles blocking it;

[0089] Through these criteria, the performance of indoor mold opening positioning can be systematically evaluated and verified to meet the predetermined requirements. If these criteria are met, the data adaptation analysis of ultra-wideband and inertial measurement unit can be carried out to optimize system performance and improve positioning accuracy.

[0090] After confirming that multipath component processing technology and filtering technology can effectively improve signal quality, UWB and inertial measurement unit (IMU) technology are further integrated, using UWB for precise distance measurement and IMU to provide direction and acceleration information, enhancing the continuity and stability of positioning, and optimizing positioning accuracy and response speed;

[0091] IMU can provide several key functions to enhance the overall performance of the positioning system. IMU includes gyroscope, which can measure the rotation angle of the device in space, which is very important for determining the orientation of the device or vehicle.

[0092] The accelerometer inside the IMU can measure acceleration along each axis, helping to analyze the motion state and dynamic changes of the device. Combined with the data from the gyroscope and accelerometer, the IMU can provide precise information about the device's attitude, which is critical data in control and navigation applications.

[0093] By combining these features of the IMU with the precise distance measurement capabilities of UWB, the positioning accuracy, reliability, and versatility of the system can be significantly improved.

[0094] Analyze the data optimization and adaptation of the indoor open-mode positioning process combined with ultra-wideband and inertial measurement unit, obtain the characteristic matching information generated in the analysis process, determine whether the data optimization and data adaptation combined with ultra-wideband and inertial measurement unit technology are normal, and comprehensively evaluate the data optimization and adaptation of the indoor positioning system combined with UWB and IMU technology. If the data consistency is good, within the error range, the response is fast and the system runs stably, it can be considered that the data optimization and adaptation work is normal, so that reliable and accurate indoor positioning services can be provided. The characteristic matching information includes signal quality information and path direction information;

[0095] The signal quality information includes a signal consistency index, and the path direction information includes a direction accuracy response index;

[0096] The signal consistency index in the signal quality information is an indicator used to measure the degree of change of the ultra-wideband signal strength and the inertial measurement unit data within a certain period of time. It is used to evaluate the stability and consistency of the signal over a period of time, especially in dynamic and complex environments. This indicator is very critical to improving the performance of indoor mold opening positioning. It can identify and adjust problems in signal transmission and ensure the accuracy and reliability of data. It mainly includes:

[0097] Optimize device configuration: Using the analysis results of the signal consistency index, you can adjust and optimize the system configuration, such as adjusting the signal transmission power, improving the signal processing algorithm, or rearranging the sensor position to improve the overall system performance;

[0098] Increased reliability: In wireless communication systems, by monitoring SCI, the stability of signal transmission can be evaluated to prevent communication interruption and data loss, which is especially important for critical applications that require high reliability (such as emergency communications or control systems).

[0099] Through these effects, the signal consistency index can be used to evaluate and optimize the positioning and mold opening technology system. Through continuous monitoring and optimization, the technical team can ensure high performance and stable operation in complex and changing positioning environments.

[0100] The logic for obtaining the signal consistency index is:

[0101] Continuously collect the signal strength data of the ultra-wideband within a certain period of time, and calculate the average value of the collected signal strength data: Calculate the standard deviation of the signal strength: Where si is the i-th signal strength value, N is the total number of data points of signal strength data, and the variation value of signal strength data is calculated using the expression: CV = BS / QDav g

[0102] Perform a fast Fourier transform on the signal strength data to obtain the frequency domain signal: S(f) = FFT(s(j)), where s(j) is the time domain signal, FFT represents the fast Fourier transform algorithm, and the power spectral density of each frequency component is calculated: P(f) = |S(f)| 2 , and normalize it: Use the normalized power spectral density to calculate the spectral entropy: Where p(f) is the value of the normalized power spectral density at frequency f;

[0103] Analyze the signal strength data and calculate the autocorrelation value of the signal at each delay time h. The calculation expression is: Where x(T) is the signal value at time point T, the autocorrelation value R(0) at zero delay is obtained, the value R(zero) of the first zero crossing point of the autocorrelation function is obtained, and the signal consistency index is calculated. The calculation expression is:

[0104] It should be noted that the signal strength data is input as the original signal, and the original signal is subjected to a fast Fourier transform to convert the original signal from the time domain to the frequency domain; the zero delay value and the first zero crossing point of the autocorrelation are determined, because the autocorrelation value is the largest at zero delay, and the autocorrelation value at zero delay represents the similarity when the signal completely coincides with itself, and the position of the first zero crossing point of the autocorrelation function is determined, that is, the position where the autocorrelation function first passes through zero.

[0105] The direction accuracy response index in the path direction information is used to evaluate the accuracy between the direction data output by the inertial measurement unit and the actual direction.

[0106] In indoor mold opening positioning, accurate directional data is crucial to ensure the correct placement of the mold. By monitoring and optimizing the directional accuracy response index, it can be ensured that the mold moves accurately along the predetermined trajectory during the manufacturing process, thereby reducing manufacturing errors.

[0107] In the scenario where multiple machines and equipment work together, precise directional control of each device is necessary. A high level of directional accuracy response index can ensure more coordinated actions between devices and improve the collaborative efficiency of the entire production line.

[0108] The optimization of the directional accuracy response index not only improves production efficiency and product quality, but also brings higher reliability and efficiency to the entire indoor mold positioning system. In practical applications, continuous monitoring and optimization of this indicator is the key to ensuring the long-term stable operation of the equipment.

[0109] The direction accuracy response index is obtained as follows:

[0110] Collect continuous direction data from the inertial measurement unit and record the actual direction data at the same time. For each measurement moment, calculate the expected measured direction of the inertial measurement unit and the actual direction, and calculate the angle error. The calculation expression is: ER(t) = |θ me (t)-θ ac (t)|, where θ me (t) is the measured angle at time t, θ ac (t) is the actual angle, calculate the angle error value, the calculation expression is: JD = Get the time t at which the response starts start The stable time point of the output is t end , calculate the direction accuracy response index, the calculation expression is:

[0111]

[0112] It should be noted that continuous orientation data is collected from the IMU, which is usually expressed in the form of quaternions or Euler angles. The orientation data can be obtained through a high-precision reference system (such as an optical tracking system).

[0113] A larger directional accuracy response index indicates that the inertial measurement unit or corresponding measurement equipment can measure and report directional data very accurately, which means that the actual measured directional data is very close to the true direction with a small error. The larger the directional accuracy response index, the higher the accuracy and reliability of the device in measuring direction, and it is suitable for a wider range of high-precision application scenarios. This is especially important for high-tech industries that rely on precise movement and positioning.

[0114] The obtained signal consistency index and direction accuracy response index are calculated jointly to obtain the positioning control coefficient, which is expressed as follows: Where D x is the positioning control coefficient, α and β are the preset proportional coefficients of the signal consistency index XHY and the direction accuracy response index FXJ, and both α and β are greater than 0.

[0115] It should be noted that the size of the preset proportional coefficient is a specific value obtained by quantifying each parameter. In order to facilitate subsequent comparison, the size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding preset proportional coefficient for each set of sample data by technical personnel in this field. It is not unique, as long as it does not affect the proportional relationship between the parameter and the quantized value, such as the proportional relationship between the directional accuracy response index and the positioning control coefficient.

[0116] The smaller the signal consistency index and the smaller the directional accuracy response index, that is, the smaller the performance value of the positioning control coefficient, in the process of indoor mold positioning, this indicates that the data integration of the ultra-wideband and inertial measurement unit is poor, resulting in reduced positioning accuracy, affecting the reliability and stability of the overall system. Inconsistency and large errors in the data may make it more difficult for the system to achieve precise control, thereby increasing errors and defects in the production process. In addition, the relevant control system may require frequent adjustments and calibrations to maintain operational efficiency, which not only increases maintenance costs, but may also lead to longer downtime and affect production efficiency. Therefore, it becomes particularly important to improve the quality of data fusion and adjust the sensor configuration to ensure efficient and accurate indoor mold positioning;

[0117] By comprehensively considering the signal consistency index and the directional accuracy response index, the positioning control coefficient can more comprehensively evaluate the status of the mold opening positioning process.

[0118] When the signal consistency index and directional accuracy response index are high, this generally indicates that in the indoor open-mode positioning system, the integration of ultra-wideband and inertial measurement unit data is very effective. A high signal consistency index means that the data output by the UWB and IMU sensors shows a high degree of stability and reliability over a period of time, and the signal volatility is low, which helps to reduce errors and improve the accuracy of the system.

[0119] At the same time, a high directional accuracy response index indicates that the directional data is very close to the actual physical direction, which means that the system is very accurate in directional control and can work reliably in more complex or dynamic environments, while reducing production defects caused by directional or position errors and reducing the frequency and cost of system maintenance because less calibration and adjustment need to be performed during operation, thereby improving operational efficiency and production line continuity.

[0120] Compare the generated positioning control coefficient with the positioning control threshold, generate different control signals, and adjust the corresponding control strategy according to the generated control signals;

[0121] After obtaining the positioning control coefficient, the positioning control coefficient is compared with the positioning control threshold;

[0122] If the positioning control coefficient is greater than or equal to the positioning control threshold, an adaptive positioning stability signal is generated, indicating that the set performance standard has been met or exceeded, the positioning accuracy and stability meet the standards, and no additional control is performed. In indoor mold opening positioning control, the equipment can accurately perform its intended tasks, such as precisely placing or moving to a specific position, without errors or drift;

[0123] If the positioning control coefficient is less than the positioning control threshold, an adaptive positioning deviation signal is generated, which means that the positioning performance does not meet the preset minimum standard, the positioning accuracy is insufficient, and positioning cannot be performed accurately enough, which may lead to a decrease in operating accuracy and affect the final work quality or product quality. There may be fluctuations or instabilities in the positioning process, and further investigation is needed to find the cause, such as sensor errors, data processing problems, or external environmental interference.

[0124] Therefore, the generation of the adaptation positioning deviation signal is a warning, prompting the operator or system administrator to take measures and make necessary checks and adjustments to ensure that the mold opening positioning returns to a normal working state and avoid possible production problems or safety accidents. This requires timely diagnosis and correction of the system to ensure that all components are working properly, the environment is suitable, and the software and hardware are configured correctly.

[0125] It should be noted that the setting of the positioning control threshold can be determined according to specific scenarios and needs, and is usually adjusted and optimized based on historical data, performance indicators and other factors.

[0126] The present invention sets an ultra-wideband transmitting end and a receiving end. We should select a suitable channel model for communication transmission according to the characteristics of signal transmission and the complexity of the environment. By using the clock offset method and the time difference arrival positioning method, accurate ranging and positioning can be performed between the transmitting end and the receiving end. Combined with multipath component analysis and filtering technology, the accuracy of indoor mold opening positioning can be further improved. If the positioning result meets the preset standard, the ultra-wideband can be combined with the inertial measurement unit to further optimize the accuracy of indoor mold opening positioning. By analyzing the characteristic matching information generated in the positioning process, the adaptation of the data can be effectively determined. According to the analysis results, the corresponding signal is generated to guide the control and management of mold opening positioning, thereby achieving more efficient and precise operation control.

[0127] Embodiment 2, this embodiment is a system embodiment of embodiment 1, which is used to implement a UWB-based intelligent mold opening positioning control method introduced in embodiment 1, such as Figure 2 As shown, specifically including:

[0128] The transceiver selection module is used to set the ultra-wideband transmitter and receiver, and use different channel models for communication transmission according to the characteristics of signal transmission and environmental complexity;

[0129] The positioning data processing module is used to measure the distance and position between the transmitter and the receiver according to the clock offset method and the time difference arrival positioning method, and combine the multipath component analysis with the filtering technology to determine the indoor mold opening positioning situation;

[0130] Positioning process analysis module: if the indoor mold opening positioning meets the requirements, the ultra-wideband is combined with the inertial measurement unit to optimize the indoor mold opening positioning accuracy and analyze the characteristic matching information generated by the indoor mold opening positioning process;

[0131] The control module is used to determine the data adaptation status and generate a signal according to the generated characteristic matching information, and perform corresponding mold opening positioning control management according to the generated signal.

[0132] The above formulas are all dimensionless and calculated numerically. Specific dimension removal can be achieved by various means such as standardization, which will not be elaborated here. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0133] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, an ATA hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state ATA hard disk.

[0134] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean 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 the present application.

[0135] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0136] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0137] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0138] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0139] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A UWB-based intelligent mold opening positioning control method, It is characterized in that The steps include: Set up the UWB transmitter and receiver, and use different channel models for communication transmission according to the characteristics of signal transmission and environmental complexity; The distance and positioning between the transmitter and the receiver are measured and located according to the clock offset method and the time difference arrival positioning method, and the multipath component analysis and filtering technology are combined to determine the indoor mold opening positioning situation; If the indoor mold opening positioning meets the requirements, the ultra-wideband is combined with the inertial measurement unit to optimize the indoor mold opening positioning accuracy and analyze the characteristic matching information generated during the indoor mold opening positioning process; Determine the data adaptation status and generate a signal based on the generated characteristic matching information, and perform corresponding mold opening positioning control management based on the generated signal; The multipath component analysis is combined with filtering technology to determine the indoor mold opening positioning. The specific process is as follows: Collect signal data of the indoor environment and pre-process the collected signal data, including noise removal and normalization processing; Using principal component analysis, the preprocessed signal data is constructed into a matrix form, and the covariance matrix is ​​calculated based on the data matrix. Based on the standardized data, the covariance matrix is ​​constructed to quantitatively determine the correlation between variables; Use Kalman filtering technology to define the system state model and measurement model, determine the initial state estimate and initial error covariance matrix, use the system state model to predict the state and initial error covariance at the next moment, and update the state estimate to determine and eliminate signal data deviation; Determine the indoor mold opening positioning performance based on positioning accuracy, positioning stability, and system robustness; The characteristic matching information generated during the indoor mold opening and positioning process is analyzed. The specific process is as follows: The characteristic matching information includes signal quality information and path direction information; The signal quality information includes a signal consistency index, and the path direction information includes a direction accuracy response index; The direction accuracy response index is used to indicate the accuracy between the direction data output by the inertial measurement unit and the actual direction; The signal consistency index indicates the degree of change of the UWB signal strength and the IMU data within a certain period of time; The obtained signal consistency index and directional accuracy response index are calculated jointly to obtain the positioning control coefficient.

2. According to the UWB-based intelligent mold opening positioning control method of claim 1, Features: According to the characteristics of signal transmission and the complexity of the environment, different channel models are used for communication transmission. The specific process is as follows: The channel model includes a single-path linear channel model, a single-path nonlinear channel model and a multipath channel model; Use a single-path linear channel model in an unobstructed signal propagation path; A single-path nonlinear channel model is used for signal propagation paths along nonlinear routes; The multipath channel model is used in the signal propagation path where multipath effects exist.

3. According to the UWB-based intelligent mold opening positioning control method of claim 2, Features: The distance measurement and positioning between the transmitter and the receiver are performed based on the clock offset method and the time difference arrival positioning method. The specific process is as follows: The clock offset method is to determine the time point of transmitting and receiving the signal at a known time point, and calculate the clock deviation between the transmitting and receiving signals, and calculate the distance of signal propagation based on the clock deviation; The time difference of arrival positioning method is to deploy receivers at different known locations. The receivers record the exact time of signal arrival, select one receiver as a reference, calculate the time difference between the remaining receivers and the reference receiver receiving the signal, and use the time difference and the known position of the receiver to estimate the position of the signal source through solution.

4. According to the UWB-based intelligent mold opening positioning control method of claim 3, Features: The data adaptation is determined based on the generated characteristic matching information and a signal is generated. The corresponding mold opening positioning control management is performed based on the generated signal. The specific process is as follows: Compare the positioning control coefficient with the positioning control threshold; If the positioning control coefficient is greater than or equal to the positioning control threshold, an adaptive positioning stabilization signal is generated without making any control adjustments; If the positioning control coefficient is less than the positioning control threshold, an adaptive positioning deviation signal is generated to prompt the operator or system administrator to take measures to check and adjust the positioning process.

5. A UWB-based intelligent mold opening positioning control system, used to implement a UWB-based intelligent mold opening positioning control method as described in any one of claims 1 to 4, It is characterized in that include: The transceiver selection module is used to set the ultra-wideband transmitter and receiver, and use different channel models for communication transmission according to the characteristics of signal transmission and environmental complexity; The positioning data processing module is used to measure the distance and position between the transmitter and the receiver according to the clock offset method and the time difference arrival positioning method, and combine the multipath component analysis with the filtering technology to determine the indoor mold opening positioning situation; Positioning process analysis module: if the indoor mold opening positioning meets the requirements, the ultra-wideband is combined with the inertial measurement unit to optimize the indoor mold opening positioning accuracy and analyze the characteristic matching information generated by the indoor mold opening positioning process; A control module is used to determine the data adaptation status and generate a signal according to the generated characteristic matching information, and perform corresponding mold opening positioning control management according to the generated signal; The multipath component analysis is combined with filtering technology to determine the indoor mold opening positioning. The specific process is as follows: Collect signal data of the indoor environment and pre-process the collected signal data, including noise removal and normalization processing; Using principal component analysis, the preprocessed signal data is constructed into a matrix form, and the covariance matrix is ​​calculated based on the data matrix. Based on the standardized data, the covariance matrix is ​​constructed to quantitatively determine the correlation between variables; Use Kalman filtering technology to define the system state model and measurement model, determine the initial state estimate and initial error covariance matrix, use the system state model to predict the state and initial error covariance at the next moment, and update the state estimate to determine and eliminate signal data deviation; Determine the indoor mold opening positioning performance based on positioning accuracy, positioning stability, and system robustness; The characteristic matching information generated during the indoor mold opening and positioning process is analyzed. The specific process is as follows: The characteristic matching information includes signal quality information and path direction information; The signal quality information includes a signal consistency index, and the path direction information includes a direction accuracy response index; The obtained signal consistency index and directional accuracy response index are calculated jointly to obtain the positioning control coefficient.

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