System for autonomous calibration of mechanical assemblies using sensor-based orientation detection

Abstract

A system for the autonomous calibration of mechanical assemblies by means of sensor-based alignment detection, wherein the system comprises: a support frame configured to support a plurality of interconnected mechanical components, including at least one shaft, at least one coupling interface, and at least one bearing housing arranged along a predefined alignment axis; a plurality of sensor units mounted at predetermined locations on the frame, each sensor unit comprising a displacement sensor for measuring linear position deviations, an angle sensor for detecting rotational misalignments, and a strain sensor element for detecting alignment changes caused by deformation;a signal acquisition unit electrically connected to the plurality of sensor units, wherein the signal acquisition unit comprises an analog-to-digital conversion circuit and a signal conditioning circuit configured to generate digitized sensor data; a processing unit operationally coupled to the signal acquisition unit, wherein the processing unit comprises at least one processor and a memory that stores executable instructions configured to calculate alignment parameters including parallel offset, angular deviation, and concentricity error based on the digitized sensor data;a plurality of actuator units mechanically connected to adjustable mounting surfaces of the mechanical components, each actuator unit comprising a motor-driven positioning mechanism configured to impart controlled translational and rotational movement to the mechanical components; and an electrically coupled control interface between the processing unit and the actuator units configured to transmit control signals generated by the processing unit to the actuator units to perform closed-loop alignment correction based on continuously updated sensor measurements.

Description

AREA OF INVENTION The present invention relates generally to precision mechanical systems and automated calibration technologies, in particular a system for the autonomous calibration of mechanical assemblies in industrial machines by means of integrated sensor-based alignment detection, real-time feedback processing, and adaptive correction mechanisms. The invention is applicable to manufacturing plants, robot assemblies, rotating machines, and mechanical structures that require highly precise alignment during installation, operation, or maintenance. BACKGROUND OF THE INVENTION Mechanical assemblies, consisting of multiple interconnected components such as shafts, couplings, bearings, frames, and structural parts, require precise alignment to ensure efficient operation, low wear, and a long service life. Conventional alignment methods typically rely on manual measuring instruments, optical alignment systems, or offline calibration procedures, which are time-consuming, error-prone, and do not allow for continuous monitoring. Existing automated solutions often fail to dynamically detect misalignments under operating conditions, especially when thermal expansion, vibrations, load changes, and structural deformations affect alignment accuracy. Many known systems are also limited to uniaxial measurements and lack integrated correction functions. Therefore, there is a need for a structurally integrated system that autonomously detects alignment deviations in real time and implements corrective actions within the mechanical assembly. Mechanical assemblies in industrial machinery, robotic systems, turbines, and precision manufacturing equipment are highly dependent on the precise alignment of interconnected components such as shafts, couplings, bearings, and frames. Correct alignment ensures efficient power transmission, minimizes vibrations, reduces friction losses, and prevents premature wear or total failure. However, maintaining proper alignment presents a constant challenge due to factors such as assembly inaccuracies, thermal expansion, dynamic loads, material fatigue, and environmental influences. Therefore, incorrect alignment remains one of the primary causes of reduced operational efficiency and increased maintenance in mechanical systems. Conventional alignment methods rely primarily on manual measuring tools such as dial gauges, rulers, feeler gauges, and laser alignment devices. While laser-based alignment systems offer higher measurement accuracy than conventional methods, they still require manual setup, calibration, and operator expertise. These procedures are typically performed during installation or scheduled maintenance intervals, meaning that alignment is not continuously monitored during operation. Consequently, misalignments caused by dynamic factors during operation often go undetected until they lead to performance degradation or failure. Furthermore, manual methods are time-consuming and prone to errors, especially with complex multi-axis assemblies where multiple alignment parameters must be considered simultaneously. To overcome these limitations, some systems utilize electronic sensors such as proximity sensors, displacement transducers, and vibration sensors for indirect alignment monitoring. While these sensor-based systems provide real-time data, they are often limited in their application range and do not offer comprehensive multidimensional alignment detection. Vibration-based monitoring systems, for example, can indicate misalignments but cannot precisely quantify their nature or extent—such as angular deviations versus parallel displacements. Similarly, single-axis displacement transducers do not detect complex spatial deviations across multiple degrees of freedom. Therefore, these systems primarily serve diagnostic purposes rather than correction and require subsequent manual intervention to restore alignment. Advanced machine condition monitoring systems have also been developed, integrating data acquisition units and sensor signal analysis tools. While these systems improve fault detection, they are generally designed for predictive maintenance rather than proactive fault correction. They rely on predefined thresholds and historical data patterns for anomaly detection, potentially overlooking real-time changes or evolving system dynamics. Furthermore, these systems often operate in isolation from mechanical adjustment mechanisms and therefore cannot autonomously implement corrective actions. This separation between detection and correction introduces delays and reduces the overall responsiveness of the system. Another category of existing solutions comprises automated alignment platforms with motorized adjustment platforms and external measuring instruments. These systems are typically used in high-precision environments such as semiconductor manufacturing or optical assembly. While they offer higher accuracy, they are often expensive, complex, and limited to controlled environments. Their reliance on external measuring systems makes them less suitable for integration into general industrial machinery, especially where space constraints, harsh operating conditions, and continuous operation are critical factors. A significant drawback of existing solutions is the lack of integrated, closed-loop control systems capable of continuously detecting, analyzing, and correcting alignment deviations within the mechanical assembly. Most approaches focus either on measurement without correction or on correction without adaptive, real-time feedback. Furthermore, many systems fail to adequately account for transient effects such as thermal expansion, load-induced deformation, or vibration-induced displacements, as these can dynamically alter alignment conditions during operation. This gap highlights the need for a structurally integrated system that combines multi-sensor data acquisition, computer-aided real-time analysis, and actuator-based correction within a unified framework.Such a system would enable the continuous, autonomous calibration of mechanical assemblies, thus overcoming the limitations of existing technologies and significantly improving operational safety and efficiency. SUMMARY OF THE INVENTION The present invention relates to a system for the autonomous calibration of mechanical assemblies. It comprises a structural framework with integrated distributed sensor elements, signal acquisition units, processing units, and actuator-controlled alignment correction mechanisms. The system is configured to continuously detect positional, angular, and dimensional deviations between interconnected mechanical components and generate correction signals to restore alignment within predefined tolerances. The system integrates multimodal sensors, including displacement sensors, angle encoders, strain gauges, and inertial measurement units, positioned at critical interfaces of the mechanical assembly. The acquired data is processed by computing units that implement algorithms for alignment determination, error modeling, and compensation strategies. Based on the calculated alignment error parameters, the system actuates mechanical adjustment components such as micro-positioning actuators, adjustable bearings, or servo-controlled alignment interfaces to achieve precise calibration without manual intervention. The present invention relates to a system for the autonomous calibration of mechanical assemblies using sensor-based alignment detection. The system continuously monitors and ensures the precise alignment of interconnected mechanical components without manual intervention. The invention aims to achieve highly precise alignment by integrating multiple sensor elements into the assembly, which detect positional, angular, and deformation deviations in real time. A further objective of the invention is to provide a structurally integrated calibration arrangement for detecting misalignments across multiple axes and degrees of freedom. This overcomes the limitations of conventional uniaxial or indirect monitoring methods. The system serves to establish a uniform reference frame for the interpretation of sensor data and enables the precise determination of alignment parameters such as parallel offset, angular deviation, and concentricity error in complex mechanical configurations. A further objective of the invention is to provide a system with a signal acquisition and processing unit for real-time data fusion, error estimation, and predictive compensation. The processing unit is designed to analyze sensor outputs under various operating conditions, including thermal expansion, dynamic loading, and vibration effects, thereby ensuring that alignment corrections respond to both static and transient deviations. A further objective of the invention is to provide a system with actuator-based adjustment mechanisms that are mechanically coupled to the assembly. The actuators are configured to perform fine position corrections based on calculated alignment parameters. The invention aims to realize a closed-loop control configuration in which continuous acquisition and control enable an iterative approach to the optimal alignment without interrupting machine operation. A further objective of the invention is to provide a calibration system that can be used in real-time industrial environments, including conditions with high temperatures, mechanical stress, and continuous motion, while ensuring measurement accuracy and system reliability. The system is suitable for both initial calibration during installation and ongoing alignment maintenance during operation. A further objective of the invention is to provide a modular and scalable structural configuration that enables integration into a variety of mechanical assemblies, including rotating machines, robotic systems, and supporting structures, without requiring a substantial redesign of the base system. The system is also intended to support the retrofitting of existing machines to improve alignment monitoring and correction. Another objective of the invention is to provide a system equipped with a communication interface configured to transmit alignment data, calibration status and diagnostic information to external control systems, thereby enabling remote monitoring, data logging and integration into industrial automation architectures. Another objective of the invention is to reduce mechanical wear, energy losses and maintenance costs associated with misalignments by ensuring continuous and precise alignment control, thereby improving the overall efficiency of the system, its service life and reliability. BRIEF DESCRIPTION OF THE DRAWING These and other features, aspects and advantages of the present invention will be better understood if the following detailed description is read with reference to the accompanying drawing, in which the same symbols represent the same parts: Fig. 1 shows a block diagram of a system for the autonomous calibration of mechanical assemblies by means of sensor-based orientation detection. Furthermore, those skilled in the art will recognize that the elements in the drawing are simplified and not necessarily drawn to scale. For example, the flowcharts illustrate the process by highlighting the main steps to facilitate understanding of the present disclosure. With regard to the construction of the device, one or more components may be represented in the drawing by conventional symbols. The drawing may show only those specific details relevant to understanding the embodiments of the present disclosure, so as not to clutter the drawing with details that are already apparent to those skilled in the art from the description contained herein. DETAILED DESCRIPTION OF THE INVENTION To facilitate understanding of the principles of the invention, reference is made below to the embodiment shown in the drawing, which is described using specific terms. It is understood, however, that this does not limit the scope of protection of the invention. Rather, modifications and further developments of the depicted system, as well as further applications of the inventive principles shown therein, are conceivable, insofar as they would normally occur to a person skilled in the art in the field of the invention. It will be clear to those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not to be understood as a limitation thereof. References to “an aspect”, “another aspect”, or similar phrases in this description mean that a particular feature, structure, or property described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, phrases such as “in one embodiment”, “in another embodiment”, and similar expressions in this description may, but do not necessarily, all refer to the same embodiment. The terms "includes," "comprehensive," or similar expressions denote non-exclusive inclusion. Thus, a procedure or method containing a list of steps does not only include those steps but may also include further steps not explicitly listed or inherent in the procedure or method. Likewise, the statement "includes..." for one or more devices, subsystems, elements, structures, or components, without further limitations, does not preclude the existence of other devices, subsystems, elements, structures, or components. Unless otherwise defined, all technical and scientific terms used herein have the same meanings generally known to those skilled in the art in the field to which this invention belongs. The systems, methods, and examples described herein serve only for illustration and are not to be understood as limiting. Embodiments of the present disclosure are described in detail below with reference to the attached drawing. Fig. 1 shows a block diagram of a system for the autonomous calibration of mechanical assemblies using sensor-based alignment detection. The system comprises: a frame 102 for accommodating several interconnected mechanical components, including at least one shaft, at least one coupling interface, and at least one bearing housing, arranged along a predefined alignment axis; several sensor units 104, mounted at predetermined positions on the frame, each comprising a displacement sensor 106 for measuring linear position deviations, an angle sensor 108 for detecting rotational misalignments, and a strain gauge 110 for detecting deformation-induced changes in alignment; a signal acquisition unit 112, electrically connected to the sensor units, comprising an analog-to-digital conversion circuit and a signal conditioning circuit for generating digitized sensor data;a processing unit 114, which is operationally connected to the signal acquisition unit and comprises at least one processor and a memory for storing executable instructions for calculating alignment parameters such as parallel offset, angular deviation, and concentricity error based on the digitized sensor data; a plurality of actuator units 116, which are mechanically connected to adjustable mounting surfaces of the mechanical components, each actuator unit comprising a motor-driven positioning mechanism configured to impart controlled translational and rotational movement to the mechanical components;and a control interface 118, which is electrically coupled between the processing unit and the actuator units, wherein the control interface is configured to transmit control signals generated by the processing unit to the actuator units in order to perform a closed-loop alignment correction based on continuously updated sensor measurements. In one embodiment, each displacement sensor 106 comprises a non-contact optical displacement transducer mounted on a calibrated bracket aligned with a reference axis of the structural frame, wherein the optical displacement transducer is configured to measure position deviations in the micrometer range between adjacent mechanical components. In one embodiment, each angle sensor 108 comprises a rotary encoder connected to a rotary interface of the shaft or coupling, wherein the rotary encoder is configured to detect an angular misalignment between connected components with a resolution of less than one degree. In one embodiment, the strain gauge 110 comprises a strain gauge mounted on a surface of the structural frame near the bearing housing. The strain gauge is configured to detect deformation errors caused by load changes and thermal expansion. In one embodiment, the signal acquisition unit 112 further comprises a multiplex circuit configured to sequentially sample signals from the numerous sensor units, and a filter circuit configured to attenuate noise components from the sensor signals prior to digitization. In one embodiment, the processing unit 114 is configured to transform sensor data into a unified coordinate system and execute an alignment estimation algorithm that incorporates geometric transformation matrices to determine multi-axis misalignment parameters. In one embodiment, each actuator unit 116 comprises a threaded spindle mechanism driven by a servo motor and coupled to an adjustable mounting plate, wherein the threaded spindle mechanism is configured to allow fine adjustment of the position along at least one linear axis. In one embodiment, the actuator units 116 are arranged in a multi-axis configuration that allows simultaneous correction of the translational displacement and the angular orientation of the mechanical components relative to the structural frame. In one embodiment, the system further comprises a calibration reference unit with a precision reference geometry fixed in the structural frame, wherein the calibration reference unit is configured to provide basic alignment data for the initialization and recalibration of the sensor units. In one embodiment, the system further comprises a communication interface coupled to the processing unit, configured to transmit alignment data, actuator status and diagnostic information to an external control system via a wired or wireless communication protocol. The described system is fully realized through physically constructed mechanical, electrical, and electromechanical elements integrated into a machine structure. The frame is a rigid, load-bearing structure made of metal or composite material, supporting shafts, coupling interfaces, and bearing housings. The sensor units are implemented as discrete hardware components, including optical displacement transducers on calibrated mounts, rotary encoders on rotating interfaces, and strain gauges on the structural surfaces. Each of these components generates measurable electrical signals corresponding to physical parameters. The signal acquisition unit comprises dedicated electronic circuits with amplifiers, filters, multiplexers, and analog-to-digital converters, mounted on printed circuit boards for real-time signal conditioning and conversion.The processing unit is implemented as a hardware computer with a processor and memory elements on a control board for executing electrical operations. The actuators are mechanical positioning units with servo motors, lead screws, and adjustable mounting plates for physically repositioning the components. Electrical connections, cabling, and control interfaces enable the direct transmission of electrical signals between these hardware elements, thus ensuring that orientation detection and correction occur through concrete physical interactions within the system. The system for the autonomous calibration of mechanical assemblies comprises a structural assembly that supports several mechanical components, such as rotating shafts, coupling interfaces, bearing housings, and rigid frame elements, in a predefined spatial arrangement. The structural assembly features mounting interfaces that can accommodate sensors and adjustment mechanisms without compromising its mechanical integrity. Several sensor units are distributed at predetermined positions along the structural assembly, corresponding to critical alignment surfaces. Each sensor unit comprises at least one displacement sensor for measuring linear deviations between adjacent components, an angle sensor element for detecting rotational misalignments, and a strain sensor element for detecting alignment changes caused by deformation. The sensor units are mechanically attached to the structural assembly by means of calibrated mounts to ensure consistent reference positioning. The sensor units are electrically connected to a signal acquisition unit, which includes analog-to-digital converters and signal conditioning circuits for noise filtering, normalization of the sensor outputs, and conversion of analog signals into digital data streams. The signal acquisition unit is also connected to a processing unit, which contains one or more processors and memory elements for executing orientation detection algorithms. The processing unit is programmed to calculate alignment parameters by correlating multisensor data, including linear displacement vectors, angular deviations, and strain distributions. The calculation involves transforming the sensor data into a common coordinate reference system, followed by estimating misalignment parameters such as parallel offset, angular deviation, and concentricity error. The processing unit also integrates predictive compensation models that account for thermal expansion, load-induced deformation, and dynamic vibration effects. Based on the calculated alignment parameters, the processing unit generates control signals to several actuator units, which are mechanically connected to adjustable components of the assembly. Each actuator unit comprises a micro-positioning mechanism with a motorized threaded spindle, a piezoelectric actuator, or a servo-controlled adjustment interface for the stepwise repositioning of the associated mechanical component. The actuator units are arranged to allow controlled movement along multiple degrees of freedom, thereby correcting both translational and rotational misalignments. The control signals are dynamically updated in a closed-loop control system, with the sensor units continuously monitoring the changes in orientation caused by actuator settings, thus enabling an iterative approach to the optimal alignment. The system also includes a communication interface configured to transmit alignment data, calibration status, and diagnostic information to an external monitoring system or user interface. The communication interface can support wired or wireless data transmission protocols for integration into industrial control systems. In one embodiment, the system includes a calibration reference unit with a precise reference geometry or baseline alignment template against which the sensor measurements are compared during initialization and recalibration operations. The reference unit ensures consistent calibration accuracy during repeated operations. The system design allows for both retrofitting existing mechanical assemblies and integration into newly manufactured systems. Operating in real time, the system enables continuous monitoring of alignment and automatic correction during machine operation. This minimizes downtime and increases operational efficiency. The system for the autonomous calibration of mechanical assemblies using sensor-based orientation detection is implemented as an integrated electromechanical arrangement within a support frame that accommodates interconnected components such as shafts, couplings, and bearing housings. The support frame provides rigid mounting surfaces for sensor and actuator units, ensuring that all measurements and corrections are referenced to a stable coordinate system. The sensor units are strategically positioned at critical alignment interfaces, such as shaft-coupling connections and bearing surfaces, to detect deviations in position, angle, and structural deformation with high precision. Each sensor unit generates continuous analog signals representing linear displacement, angular orientation, and strain-induced deformation. The signal acquisition unit receives these analog signals and performs signal conditioning steps such as amplification, filtering, and noise reduction to ensure signal integrity. A multiplexer within the signal acquisition unit sequences the sensor inputs to optimize sampling efficiency. Subsequently, analog-to-digital converters generate synchronized digital representations of the sensor outputs. These digitized signals are transmitted to the processing unit, where computational routines are executed to determine the real-time alignment conditions. The processing unit executes an orientation detection algorithm that begins with coordinate normalization. This transforms the raw data from the spatially distributed sensors into a uniform reference coordinate system associated with the structure. This transformation is performed using pre-calibrated geometric relationships and transformation matrices that map the sensor measurement axes to the global coordinate system. Following normalization, the algorithm fuses the data from multiple sensors by correlating displacement vectors, angle measurements, and strain values ​​to create a comprehensive representation of the relative position of the mechanical components. The algorithm calculates the alignment parameters by solving geometric equations that describe the spatial relationships between the components. Parallel misalignment is determined by evaluating the translational deviations between corresponding reference points of adjacent components, while angular misalignment is calculated by comparing the orientation vectors detected by angle sensors. Concentricity error is estimated by analyzing radial displacement patterns and deviations from rotational symmetry. Additionally, the algorithm integrates compensation models that account for dynamic influences such as thermal expansion and load-induced deformation. These models utilize strain measurements and temperature-dependent coefficients stored in memory to adjust the alignment calculations in real time. Once the alignment parameters are set, the processing unit generates correction vectors that represent the amount and direction of the required position adjustments. These correction vectors are converted into actuator control signals using inverse kinematics, which assign the desired component movements to the actuator displacements. The actuator units, each comprising a motor-driven threaded spindle or an equivalent positioning mechanism, receive these control signals and perform fine adjustments along one or more axes. The arrangement of the actuator units enables coordinated multi-axis correction and thus the simultaneous compensation of translational and rotational misalignments. The system operates in a closed-loop control system, with sensor units continuously monitoring the effects of actuator adjustments. The updated sensor data is repeatedly processed by the alignment detection algorithm, enabling iterative refinement of the alignment parameters. The processing unit's control logic uses convergence criteria based on predefined tolerance thresholds, gradually reducing actuator operation as the alignment approaches optimal conditions. This iterative feedback mechanism ensures stable and precise calibration without overshoot or oscillation. The calibration reference unit serves as a geometric reference standard against which the sensor measurements are initially calibrated. During system initialization, the processing unit compares the measured values ​​with the reference data to determine calibration coefficients for each sensor unit. These coefficients are then used to correct measurement deviations and ensure long-term accuracy. Periodic recalibrations can be performed automatically by referencing the calibration reference unit to compensate for sensor drift or structural changes. The communication interface enables bidirectional data exchange between the system and the external control infrastructure. Alignment parameters, actuator positions, and diagnostic indicators are transmitted for monitoring and logging, while configuration inputs such as tolerance limits and calibration settings can be received from higher-level systems. The integration of sensors, data processing, and actuators in a unified structural framework allows the system to perform continuous, real-time alignment calibration under operating conditions. This increases mechanical efficiency, reduces wear, and extends the assembly's service life. The drawing and the preceding description illustrate embodiments. Those skilled in the art will recognize that one or more of the described elements can be combined to form a single functional element. Alternatively, certain elements can be divided into several functional elements. Elements of one embodiment can be added to another. For example, the process flows described here can be modified and are not limited to the manner described herein. Furthermore, the actions of a flowchart need not be performed in the sequence shown; nor do all actions necessarily need to be carried out. Actions that do not depend on other actions can be performed in parallel with the other actions. The scope of protection of the embodiments is in no way limited by these specific examples. Numerous variations, whether explicitly stated in the description or not, such as...Differences in structure, dimensions, and materials are possible. The scope of protection of the embodiments is at least as comprehensive as described by the following claims. The advantages, other benefits, and problem solutions have been described above with reference to specific embodiments. However, the advantages, benefits, problem solutions, and any components that can effect or enhance an advantage, benefit, or solution are not to be construed as critical, necessary, or essential features or components of the claims. REFERENCES 100 A system for the autonomous calibration of mechanical assemblies using sensor-based orientation detection. 102 Supporting frame 104 Multiple sensor units 106 Displacement sensor 108 Angle sensor 110 Strain gauge 112 Signal acquisition unit 114 Processing unit 116 Multiple actuator units 118 Control interface

Claims

A system for the autonomous calibration of mechanical assemblies by means of sensor-based alignment detection, wherein the system comprises: a support frame configured to support a plurality of interconnected mechanical components, including at least one shaft, at least one coupling interface, and at least one bearing housing arranged along a predefined alignment axis; a plurality of sensor units mounted at predetermined locations on the frame, each sensor unit comprising a displacement sensor for measuring linear position deviations, an angle sensor for detecting rotational misalignments, and a strain sensor element for detecting alignment changes caused by deformation;a signal acquisition unit electrically connected to the plurality of sensor units, wherein the signal acquisition unit comprises an analog-to-digital conversion circuit and a signal conditioning circuit configured to generate digitized sensor data; a processing unit operationally coupled to the signal acquisition unit, wherein the processing unit comprises at least one processor and a memory that stores executable instructions configured to calculate alignment parameters including parallel offset, angular deviation, and concentricity error based on the digitized sensor data;a plurality of actuator units mechanically connected to adjustable mounting surfaces of the mechanical components, each actuator unit comprising a motor-driven positioning mechanism configured to impart controlled translational and rotational movement to the mechanical components; and an electrically coupled control interface between the processing unit and the actuator units configured to transmit control signals generated by the processing unit to the actuator units to perform closed-loop alignment correction based on continuously updated sensor measurements. System according to claim 1, wherein each displacement sensor comprises a non-contact optical displacement transducer mounted on a calibrated mount aligned with a reference axis of the structural frame, wherein the optical displacement transducer is configured to measure position deviations in the micrometer range between adjacent mechanical components. System according to claim 1, wherein each angle sensor comprises a rotary encoder connected to a rotary interface of the shaft or coupling, wherein the rotary encoder is configured to detect an angular misalignment between connected components with a resolution of less than one degree. System according to claim 1, wherein the strain measuring element comprises a strain gauge mounted on a surface of the structural frame near the bearing housing, wherein the strain gauge is configured to detect deformation misalignments caused by load changes and thermal expansion. System according to claim 1, wherein the signal acquisition unit further comprises a multiplex circuit for sequential sampling of signals from the plurality of sensor units and a filter circuit for attenuating noise components from the sensor signals prior to digitization. System according to claim 1, wherein the processing unit is configured to transform sensor data into a unified coordinate system and executes an alignment estimation algorithm incorporating geometric transformation matrices to determine multi-axis misalignment parameters. System according to claim 1, wherein each actuator unit comprises a threaded spindle mechanism driven by a servo motor and coupled to an adjustable mounting plate, wherein the threaded spindle mechanism is configured to allow fine adjustment of the position along at least one linear axis. System according to claim 1, wherein the actuator units are arranged in a multi-axis configuration that enables simultaneous correction of the translational displacement and the angular orientation of the mechanical components relative to the structural frame. System according to claim 1, further comprising a calibration reference unit with a precision reference geometry fixed in the structural frame, wherein the calibration reference unit is configured to provide basic alignment data for the initialization and recalibration of the sensor units. The system according to claim 1 further comprises a communication interface coupled to the processing unit, wherein the communication interface is configured to transmit alignment data, actuator status and diagnostic information to an external control system via a wired or wireless communication protocol.

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